Sunday, August 9th
Set-Up Day
8:30am
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Big Data Summit
8:30am - 6:00pm Level 2 - State Room
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4:00pm |
Registration
4:00pm - 6:00pm Level 3 - Registration Desk (Marble Side)
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6:00pm |
Monday, August 10th
Workshop & Tutorial Day
- Monday, August 10th Registration desk: 7:00am - 6:00pm (Level 3 - Registration Desk)
- KDD15 Exhibitor Set-Up: 12:00pm - 5:00pm (Level 3 - Exhibition Area)
7:30am
8:00am |
Arrival Coffee
7:30am - 8:00am | Level 2 & Level 4 Pre-Function Areas |
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Morning Break
10:30am - 11:00am Level 2 & Level 4 Pre-Function Areas |
Big Data Summit
8:30am - 6:00pm Level 2 - State Room
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Full-day Workshops
Workshop 1
Workshop on Outlier Definition, Detection, and Description (ODDx3)
9:30am - 5:45pm Level 2 - Room 4
Workshop 7
Workshop on Interactive Data Exploration and Analytics (IDEA))
8:50am - 5:20pm Level 4 - Room 1
Workshop 10
The 14th International Workshop on Data Mining in Bioinformatics (BIOKDD)
8:00am - 6:00pm Level 1 - Room 6
Workshop 11
The 1st International Workshop on Population Informatics for Big Data (PopInfo)
9:15am - 5:15pm Level 1 - Room 5
Workshop 12
The 4th International Workshop on Urban Computing (UrbComp)
8:30am - 5:50pm Level 1 - Room 3
Workshop 14
The 4nd International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications (BigMine)
8:00am - 6:00pm Level 4 - Room 3
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Morning Workshops
Workshop 2
The 2nd International Workshop on Data Mining for Brain Science (BrainKDD)
8:00am - 12:30pm Level 4 - Room 4
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Morning Tutorials
R1 (Tutorial 1)
VC-Dimension and Rademacher Averages: From Statistical Learning Theory to Sampling Algorithms
9:00am - 12:30pm Level 1 - Room 2
R2 (Tutorial 2)
Graph-Based User Behavior Modeling: From Predicition to Fraud Detection
9:00am - 12:30pm Level 2 - Room 6
R5 (Tutorial 5)
Automatic Entity Recognition and Typing from Massive Test Corpora: A Phrase and Network Mining Approach
9:00am - 12:30pm Level 1 - Room 7
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12:30pm
1:30pm |
Lunch
12:30pm - 1:30pm | Level 2 & Level 4 Pre-Function Areas |
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Afternoon Break
3:00pm - 3:30pm Level 2 & Level 4 Pre-Function Areas |
Big Data Summit
(continues) Level 2 - State Room
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Full-day Workshops
(continues) |
Afternoon Workshops
Workshop 6
Workshop on Mining and Learning from Time Series (MiLeTS)
1:30pm - 6:00pm Level 4 - Room 5
Workshop 8
Workshop on Issues of Sentiment Discovery and Opinion Mining (WISDOM)
1:30pm - 6:00pm Level 2 - Room 5
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Afternoon Tutorials
R3 (Tutorial 3)
A New Look at the System, Algorithm and Theory Foundations of Large Scale Distributed Machine Learning
1:30pm - 5:00pm Level 1 - Room 2
R7 (Tutorial 7)
Big Data Analytics: Social Media Anomaly Detection: Challenges and Solutions
1:30pm - 5:00pm Level 1 - Room 4
R8 (Tutorial 8)
Diffusion in Social and Information Networks: Problems, Models and Machine Learning Methods
1:30pm - 5:00pm Level 1 - Room 7
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5:30pm | KDD15 Pre-Opening Reception Snack 5:30pm - 6:30pm | Exhibit Hall |
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6:30pm |
KDD15 Opening Ceremony & Awards 6:30pm - 8:00pm | Grand Ballroom A&B |
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8:00pm |
Microsoft’s KDD Kick-Off Reception 8:00pm - 10:00pm | Hilton Zeta Bar |
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10:00pm |
Tuesday, August 11th - Thursday, August 13th
Main KDD Conference
Tuesday, August 11th
- Tuesday, August 11th Registration desk: 8:00am - 6:00pm (Level 3 - Registration Desk)
- BESydney Networking Event (Invitation Only): 7:30am - 8:45am (Level 4 - Room 1)
- KDD15 Networking Lounge (Please drop in!): 10:20am - 6:00pm (Level 1 - Room 3 & 4)
- KDD15 Exhibit Hall: 8:00am - 6:00pm (Level 3 - Exhibition Area)
8:00am
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Arrival Coffee
8:00am - 9:00am | Level 3 - Exhibition Area |
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8:45am |
KEYNOTE 1: Ronny Kohavi, Microsoft Online Controlled Experiments: Lessons from Running A/B/n Tests for 12 Years 8:45am - 9:50am | Grand Ballroom A&B |
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9:50am
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Morning Break
9:50am - 10:20am | Level 2 Pre-Function Area; Level 3 Exhibit Hall; Level 4 Pre-Function Area |
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10:20am | Level 1 - Room 5 & 6 | Level 2 - State Room | Level 2 - Room 3 & 4 | Level 3 - Ballroom A | Level 3 - Ballroom B | Level 4 - Room 2 & 3 | Level 4 - Room 4 & 5 |
S1 (Tutorial 10) Large Scale Distributed Data Science Using Apache Spark
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RT03 Topic Models and Tensors
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RT04 Interactivity and Learning
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RT01 Social and Graphs 1
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RT02 Mining Rich Data Types
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IG01 Big Data
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IG02 E-Commerce and IR
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12:00pm |
Lunch
12:00pm - 1:00pm | Level 2 Pre-Function Area; Level 3 Exhibit Hall; Level 4 Pre-Function Area |
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1:00pm | Level 1 - Room 5 & 6 | Level 2 - State Room | Level 2 - Room 2 | Level 2 - Room 3 & 4 | Level 3 - Ballroom B | Level 4 - Room 2 & 3 | Level 4 - Room 4 & 5 |
S2 (Tutorial 11) Data-Driven Product Innovation
1:00pm - 2:40pm
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Invited Talks
Clouded Intelligence (Joseph Sirosh)
How Artificial Intelligence and Big Data Created Rocket Fuel: A Case Study (George John)
Powering Realtime Decision Engines in Finance and Healthcare using Open Source Software (Bassel Ojjeh/Greg Makowski)
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RT06 Social & Graphs 2
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RT07 Applications
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RT05 Big Data
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RT08 Unsupervised Learning
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IG03 Applications
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3:00pm
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Afternoon Break
3:00pm-3:20pm | Level 2 Pre-Function Area; Level 3 Exhibit Hall; Level 4 Pre-Function Area |
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3:20pm | Level 1 - Room 5 & 6 | Level 2 - State Room | Level 2 - Room 2 | Level 2 - Room 3 & 4 | Level 2 - Room 5&6 | Level 4 - Room 2 & 3 | Level 4 - Room 4 & 5 |
S3 (Tutorial 12) Web Personlization and Recommender Systems
3:20pm - 5:00pm
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Invited Talks
Data Science from the Lab to the Field to the Enterprise (Christopher White)
Hadoop's Impact on the Future of Data Management (Amr Awadallah)
User Modeling in Telecommunications and Internet Industry (Qiang Yang)
3:20pm - 5:20pm
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RT09 Web Mining
3:20pm - 5:00pm
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RT10 Applications 2
3:20pm - 5:00pm
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RT11 Sampling and Streams
3:20pm - 5:00pm
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RT12 Security and Privacy
3:20pm - 5:00pm
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IG04 Business, Sales, Marketing, Advertising
3:20pm - 5:00pm
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5:15pm
5:45pm |
Poster Presenters Set-Up (Must Have Poster In-Hand)
5:15pm-5:45pm | Grand Ballroom A&B |
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6:00pm |
Poster Reception 6:00pm - 9:00pm | Grand Ballroom A&B |
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9:00pm |
Wednesday, August 12th
- Wednesday, August 12th Registration desk: 8:15am - 6:00pm (Level 3 - Registration Desk)
- KDD15 Networking Lounge: 10:20am - 6:00pm (Level 1 - Room 3 & 4)
- KDD15 Exhibit Hall: 8:00am - 6:00pm (Level 3 - Exhibition Area)
8:00am
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Arrival Coffee
8:00am - 9:00am | Level 3 - Exhibition Area |
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8:45am |
KEYNOTE 2: Hugh Durrant-Whyte, University of Sydney Data, Knowledge and Discovery: Machine Learning meets Natural Science 8:45am - 9:50am | Grand Ballroom A&B |
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9:50am
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Morning Break
9:50am - 10:20am | Level 2 Pre-Function Area; Level 3 Exhibit Hall; Level 4 Pre-Function Area |
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10:20am | Level 2 - State Room | Level 2 - Room 3 & 4 | Level 3 - Ballroom A | Level 3 - Ballroom B | Level 4 - Room 2 & 3 | Level 4 - Room 4 & 5 | |
RT15 Healthcare and Medicine 1
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RT16 Knowledge Discovery
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RT13 Mining Rich Data Types 2
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RT14 Crowds and Users
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IG05 Social Networks
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IG06 Business and IR
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12:00pm |
Lunch
12:00pm - 1:00pm | Level 2 Pre-Function Area; Level 3 Exhibit Hall; Level 4 Pre-Function Area |
Demo:
Internet of Things with Microsoft Cortana Analytics 12:15pm - 12:40pm | Level 3 Ballroom A & B (Split Rooms) |
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1:00pm | Level 2 - State Room | Level 2 - Room 3 & 4 | Level 3 - Ballroom A | Level 3 - Ballroom B | Level 4 - Room 2 & 3 | Level 4 - Room 4 & 5 | Level 4 - Room 1 |
RT18 Clustering and Text
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RT19 Semi-Supervised Learning and Kernels
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Invited Talks
Data Science at Visa (Waqar Hasan & Min Wang)
Optimizing Marketing Impact Through Data Driven Decisioning (Anil Kamath)
Scaling Machine Learning and Statistics for Web Applications (Deepak Agarwal)
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RT17 Social and Graphs 3
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IG07 Social Good
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IG08 Health
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Organizing Committee Transfer Meeting | |
3:00pm
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Afternoon Break
3:00pm-3:20pm | Level 2 Pre-Function Area; Level 3 Exhibit Hall; Level 4 Pre-Function Area |
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3:20pm | Level 2 - State Room | Level 2 - Room 3 & 4 | Level 3 - Ballroom A | Level 3 - Ballroom B | Level 4 - Room 2 & 3 | Level 4 - Room 4 & 5 | |
RT21 Pattern Mining
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RT22 Transfer Learning
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Panel
Data Driven Science (Moderators:Katharina Morik & Hugh Durrant-Whyte)
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RT20 Recommender Systems 1
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IG09 E-Commerce
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IG10 Anomaly Detection
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5:00pm
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6:00pm |
Banquet & Business Meeting 6:00pm - 11:30pm | Dockside Pavilion - Darling Harbour |
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11:30pm |
Thursday, August 13th
- Thursday, August 13th Registration desk: 8:30am - 4:00pm (Level 3 - Registration Desk)
- KDD15 Networking Lounge: 10:20am - 4:00pm (Level 1 - Room 3 & 4)
- KDD15 Exhibit Hall: 8:00am - 1:30pm (Level 3 - Exhibition Area)
- KDD15 Exhibitor Move-Out: 1:30pm - 5:00pm (Level 3 - Exhibition Area)
8:00am
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Arrival Coffee
8:00am - 9:00am | Level 3 - Exhibition Area |
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8:45am |
KEYNOTE 3: Daphne Koller, Coursera MOOCS: What Have We Learned? 8:45am - 9:50am | Grand Ballroom A&B |
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9:50am
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Morning Break
9:50am - 10:20am | Level 2 Pre-Function Area; Level 3 Exhibit Hall; Level 4 Pre-Function Area |
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10:20am | Level 2 - State Room | Level 2 - Room 2 | Level 3 - Ballroom A | Level 3 - Ballroom B | Level 4 - Room 2 & 3 | Level 4 - Room 4 & 5 |
RT25 Dimensionality Reduction and Clustering
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RT26 Healthcare and Medicine 2
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RT23 Applications 3
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RT24 Recommender Systems 2
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IG11 Social Media
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IG12 Marketing and Advertising
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12:00pm |
Lunch
12:00pm - 1:00pm | Level 2 Pre-Function Area; Level 3 Exhibit Hall; Level 4 Pre-Function Area |
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1:00pm | Level 2 - State Room | Level 2 - Room 2 | Level 3 - Ballroom A | Level 3 - Ballroom B | Level 4 - Room 2 & 3 | Level 4 - Room 4 & 5 |
RT28 Dimensionality Reduction and Clustering
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RT29 Supervised Learning
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Invited Talks
Should You Trust Your Money to a Robot? (Vasant Dhar)
Building A Global Platform for Natural Disaster Resilience (Julie Batch)
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RT27 Social and Graphs 4
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RT30 Similarity and Hashing
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IG13 Applications
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2:20pm |
Panel
What Does It Take to Bring Big Data Analytics to the Mainstream? Pragmatism not Theory or Hype (Moderator: Usama Fayyad, Barclays)
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3:00pm
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Afternoon Break
3:00pm-3:30pm | Level 2 Pre-Function Area; Level 3 Exhibit Hall; Level 4 Pre-Function Area |
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3:30pm |
KEYNOTE 4: Susan Athey, Stanford Graduate School of Business Machine Learning and Causal Inference for Policy Evaluation 3:30pm - 4:30pm | Grand Ballroom A&B |
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4:30pm |
Concluding & Feedback 4:30pm - 5:00pm | Grand Ballroom A&B |
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5:00pm |
Accepted Papers by Session
Research Session RT01: Social and Graphs 1
Tuesday 10:20 am–12:00 pm | Level 3 – Ballroom A
Chair: Tanya Berger-Wolf
Efficient Algorithms for Public-Private Social NetworksFlavio Chierichetti,Sapienza University of Rome; Alessandro Epasto,Brown University; Ravi Kumar,Google; Silvio Lattanzi,Google; Vahab Mirrokni,Google
(Paper ID:563)
Locally Densest Subgraph Discovery
Lu Qin,University of Technology Sydney; Rong-Hua Li,Shenzhen University; Lijun Chang,The University of New South Wales; Chengqi Zhang,University of Technology Sydney
(Paper ID:236)
Influence at Scale: Distributed Computation of Complex Contagion in Networks
Brendan Lucier,Microsoft Research; Joel Oren,University of Toronto; Yaron Singer,Harvard University
(Paper ID:442)
A Learning-based Framework to handle Multi-round Multi-party influence maximization on social networks
Su-Chen Lin,National Taiwan University; Shou-De Lin,National Taiwan University; Ming-Syan Chen,National Taiwan University
(Paper ID:754)
Virus Propagation in Multiple Profile Networks
Angeliki Rapti,University of Patras; Kostas Tsichlas,Aristotle University of Thessaloniki; Spyros Sioutas,Ionian University; Giannis Tzimas,Technological Educational Institute of Western Greece
(Paper ID:721)
Research Session RT02: Mining Rich Data Types 1
Tuesday 10:20 am–12:00 pm | Level 3 – Ballroom B
Chair: Kyuseok Shim
Facets: Fast Comprehensive Mining of Co-evolving High-order Time SeriesYongjie Cai,The Graduate Center, CUNY; Hanghang Tong,Arizona State University; Wei Fan,Baidu USA; Ping Ji,The Graduate Center, CUNY; Qing He,University at Buffalo, SUNY
(Paper ID:497)
Data-Driven Activity Prediction: Algorithms, Evaluation Methodology, and Applications
Bryan Minor,Washington State University; Janardhan Rao,Doppa; Washington State University Diane,J; Cook Washington State Universit
(Paper ID:860)
RSC: Mining and Modeling Temporal Activity in Social Media
Alceu Ferraz Costa,University of S?o Paulo; Yuto Yamaguchi,University of Tsukuba; Agma Juci Machado Traina,University of S?o Paulo; Caetano Traina Jr.,University of S?o Paulo; Christos Faloutsos,Carnegie Mellon University
(Paper ID:197)
Query Workloads for Data-Series Indexes
Kostas Zoumpatianos,University of Trento; Yin Lou,LinkedIn Corporation; Themis Palpanas,Paris Descartes University; Johannes Gehrke,Microsoft Corporation
(Paper ID:715)
Organizational Chart Inference
Jiawei Zhang,University of Illinois at Chicago; Philip S. Yu,University of Illinois at Chicago, Tsinghua University; Yuanhua Lv,Microsoft Research
(Paper ID:41)
Research Session RT03: Topic Models and Tensors
Tuesday 10:20 am–12:00 pm | Level 2 – State Room
Chair: Amr Ahmed
Towards Interactive Construction of Topical Hierarchy: A Recursive Tensor Decomposition ApproachChi Wang,Microsoft Research; Xueqing Liu,University of Illinois at Urbana-Champaign; Yanglei Song,University of Illinois at Urbana-Champaign; Jiawei Han,University of Illinois at Urbana-Champaign
(Paper ID:177)
Rubik: Knowledge Guided Tensor Factorization and Completion for Health Data Analytics
Yichen Wang,Georgia Institute of Technology; Robert Chen,Georgia Institute of Technology; Joydeep Ghosh,University of Texas, Austin; Joshua C,Denny; Vanderbilt University Abel,Kho; Northwestern University You,Chen; Vanderbilt University Bradley,A; Malin Vanderbilt University,Jimeng; Sun Georgia Institute of Technolog
(Paper ID:790)
Simultaneous Discovery of Common and Discriminative Topics via Joint Nonnegative Matrix Factorization
Hannah Kim,Georgia Tech; Jaegul Choo,Korea University; Jingu Kim,Netflix, Inc.; Chandan K.,Reddy; Wayne State University Haesun,Park; Georgia Tec
(Paper ID:453)
Levaraging Social Context for Topic Evolution
Janani Kalyanam,University of California, San Diego; Amin Mantrach,Yahoo Labs; Diego Saez-Trumper,Yahoo Labs; Hossein Vahabi,Yahoo Labs; Gert Lanckriet,University of California, San Diego
(Paper ID:336)
Bayesian Poisson Tensor Factorization for Inferring Multilateral Relations from Sparse Dyadic Event Counts
Aaron Schein,University of Massachusetts Amherst; John Paisley,Columbia University; David M,Blei; Columbia University Hanna,Wallach; Microsof
(Paper ID:897)
Research Session RT04: Interactivity and Learning
Tuesday 10:20 am–12:00 pm | Level 2 – Room 3 & 4
Chair: Bernhard Pfahringer
Structured Hedging for Resource Allocations with LeverageNicholas Johnson,University of Minnesota; Arindam Banerjee,University of Minnesota
(Paper ID:698)
BatchRank: A Novel Batch Mode Active Learning Framework for Hierarchical Classification
Shayok Chakraborty,Carnegie Mellon University; Vineeth Balasubramanian,Indian Institute of Technology; Adepu Ravi,Sankar; Indian Institute of Technology Sethuraman,Panchanathan; Arizona State University Jieping,Ye; University of Michiga
(Paper ID:232)
Discovering Valuable Items from Massive Data
Hastagiri P,Vanchinathan; ETH Zurich Andreas,Marfurt; ETH Zurich Charles-Antoine,Robelin; Amadeus IT group SA Donald,Kossmann; ETH Zurich Andreas,Krause; ETH Zuric
(Paper ID:593)
Extreme States Distribution Decomposition Method for Search Engine Online Evaluation
Kirill Nikolaev,Yandex; Alexey Drutsa,Yandex; Ekaterina Gladkikh,Yandex; Alexander Ulianov,Yandex; Gleb Gusev,Yandex; Pavel Serdyukov,Yandex
(Paper ID:900)
Website Optimization Problem and Its Solutions
Shuhei Iitsuka,The University of Tokyo; Yutaka Matsuo,The University of Tokyo
(Paper ID:516)
Research Session RT05: Big Data
Tuesday 1:00 pm–3:00 pm | Level 3 – Ballroom B
Chair: Ron Bekkerman
Large-Scale Distributed Bayesian Matrix Factorization using Stochastic Gradient MCMCSUNGJIN AHN,University of California Irvine; ANOOP KORATTIKARA,Google; NATHAN LIU,Yahoo Labs; SUJU RAJAN,Yahoo Labs; MAX WELLING,University of Amsterdam
(Paper ID:668)
Scaling Up Stochastic Dual Coordinate Ascent
Kenneth Tran,Uber; Saghar Hosseini,University of Washington; Lin Xiao,Microsoft; Thomas Finley,Microsoft; Mikhail Bilenko,Microsoft
(Paper ID:879)
Accelerated Alternating Direction Method of Multipliers
Mojtaba Kadkhodaie,University of Minnesota; Konstantina Christakopoulou,University of Minnesota; Maziar Sanjabi,University of Minnesota; Arindam Banerjee,University of Minnesota
(Paper ID:813)
Network Lasso: Clustering and Optimization in Large-Scale Graphs
David Hallac,Stanford University; Jure Leskovec,Stanford University; Stephen Boyd,Stanford University
(Paper ID:316)
Petuum: A new Platform for Distributed Machine Learning on Big Data
Eric P,Xing; Carnegie Mellon University Qirong,Ho; Institute for Infocomm Research Wei,Dai; Carnegie Mellon University Jin-Kyu,Kim; Carnegie Mellon University Jinliang,Wei; Carnegie Mellon University Seunghak,Lee; Carnegie Mellon University Xun,Zheng; Carnegie Mellon University Pengtao,Xie; Carnegie Mellon University Abhimanu,Kumar; Carnegie Mellon University Yaoliang,Yu; Carnegie Mellon Universit
(Paper ID:361)
Performance Modeling and Scalability Optimization of Distributed Deep Learning Systems
Feng Yan,College of William and Mary; Olatunji Ruwase,Microsoft Research; Yuxiong He,Microsoft Research; Trishul Chilimbi,Microsoft Research
(Paper ID:65)
Research Session RT06: Social and Graphs 2
Tuesday 1:00 pm–3:00 pm | Level 2 – Room 2
Chair: Yang Yang
CoupledLP: Link Prediction in Coupled NetworksYuxiao Dong,University of Notre Dame; Jing Zhang,Tsinghua University; Jie Tang,Tsinghua University; Nitesh V.,Chawla; University of Notre Dame Bai,Wang; Beijing University of Posts and Telecommunication
(Paper ID:417)
Efficient Latent Link Recommendation in Signed Networks
Dongjin Song,University of California San Diego; David A.,Meyer; University of California San Diego Dacheng,Tao; University of Technology, Sydne
(Paper ID:583)
Flexible and Robust Multi-Network Clustering
Jingchao Ni,Case Western Reserve University; Hanghang Tong,Arizona State University; Wei Fan,Baidu Research Big Data Lab; Xiang Zhang,Case Western Reserve University
(Paper ID:25)
An Evaluation of Parallel Eccentricity Estimation Algorithms on Real-World Graphs
Julian Shun,Carnegie Mellon University
(Paper ID:434)
Integrating Vertex-centric Clustering with Edge-centric Clustering for Meta Path Graph Analysis
Yang Zhou,Georgia Institute of Technology; Ling Liu,Georgia Institute of Technology; David Buttler,Lawrence Livermore National Laboratory
(Paper ID:411)
Collective Opinion Spam Detection: Bridging Review Networks and Metadata
Shebuti Rayana,Stony Brook University; Leman Akoglu,Stony Brook University
(Paper ID:655)
Research Session RT07: Applications 1
Tuesday 1:00 pm–3:00 pm | Level 2 – Room 3 & 4
Chair: Shou-De Lin
Anatomical Annotations for Drosophila Gene Expression Patterns via Multi-Dimensional Visual Descriptors IntegrationHongchang Gao,University of Texas at Arlington; Lin Yan,Shanghai Jiao Tong University; Weidong Cai,University of Sydney; Heng Huang,University of Texas at Arlington
(Paper ID:718)
Multi-Task Learning for Spatio-Temporal Event Forecasting
Liang Zhao,Virginia Polytechnic Institute and State University; Qian Sun,Arizona State University; Jieping Ye,University of Michigan; Feng Chen,University at Albany - SUNY; Chang-Tien Lu,Virginia Polytechnic Institute and State University; Naren Ramakrishnan,Virginia Polytechnic Institute and State University
(Paper ID:693)
A Deep Hybrid Model for Weather Forecasting
Aditya Grover,Indian Institute of Technology Delhi; Ashish Kapoor,Microsoft Research; Eric Horvitz,Microsoft Research
(Paper ID:98)
Real Estate Ranking via Mixed Land-use Latent Models
Yanjie Fu,Rutgers University; Guannan Liu,Tsinghua University; Spiros Papadimitriou,Rutgers University; Hui Xiong,Rutgers University; Yong Ge,UNC Charlotte; Hengshu Zhu,Baidu Research; Chen Zhu,University of Science and Technology of China
(Paper ID:717)
Structural Graphical Lasso for Learning Mouse Brain Connectivity
Sen Yang,IDST at Alibaba Group; Qian Sun,Arizona State University; Shuiwang Ji,Old Dominion University; Peter Wonka,King Abdullah University of Science and Technology; Ian Davidson,University of California; Jieping Ye,University of Michigan
(Paper ID:753)
Deep Learning Architecture with Dynamically Programmed Layers for Brain Connectome Prediction
Vivek Veeriah,University of Central Florida; Rohit Durvasula,University of Central Florida; Guo-Jun Qi,University of Central Florida
(Paper ID:805)
Research Session RT08: Unsupervised Learning
Tuesday 1:00 pm–3:00 pm | Level 4 – Room 2 & 3
Chair: Ian Davidson
L∞Error and Bandwidth Selection for Kernel Density Estimates of Large DataYan Zheng,University of Utah; Jeff M.,Phillips; University of Uta
(Paper ID:577)
An Efficient Semi-Supervised Clustering Algorithm with Sequential Constraints
Jinfeng Yi,IBM Thomas J. Watson Research Center; Lijun Zhang,Nanjing University; Tianbao Yang,University of Iowa; Wei Liu,IBM Thomas J. Watson Research Center; Jun Wang,Alibaba Group
(Paper ID:732)
Real-time Top-R Topic Detection on Twitter with Topic Hijack Filtering
Kohei Hayashi,National Institute of Informatics; Takanori Maehara,Shizuoka University; Masashi Toyoda,The University of Tokyo; Ken-ichi Kawarabayashi,National Institute of Informatics
(Paper ID:829)
Stochastic Divergence Minimization for Online Collapsed Variational Bayes Zero Inference of Latent Dirichlet Allocation
Issei Sato,The University of Tokyo; Hiroshi Nakagawa,The University of Tokyo
(Paper ID:564)
Linear Time Samplers for Supervised Topic Models using Compositional Proposals
Xun Zheng,Carnegie Mellon University; Yaoliang Yu,Carnegie Mellon University; Eric P.,Xing; Carnegie Mellon Universit
(Paper ID:656)
SAME but Different: Fast and High-Quality Gibbs Parameter Estimation
Huasha Zhao,UC Berkeley; Biye Jiang,UC Berkeley; John F,Canny; UC Berkeley Bobby,Jaros; Yahoo In
(Paper ID:905)
Research Session RT09: Web Mining
Tuesday 3:20 pm–5:00pm | Level 2 – Room 2
Chair: Mohak Shah
Dynamic Topic Modeling for Monitoring Market Competition from Online Text and Image DataHao Zhang,Carnegie Mellon University; Gunhee Kim,Seoul National University; Eric P,Xing; Carnegie Mellon Universit
(Paper ID:192)
ClusType: Effective Entity Recognition and Typing by Relation Phrase-Based Clustering
Xiang Ren,University of Illinois at Urbana-Champaign; Ahmed El-Kishky,University of Illinois at Urbana-Champaign; Chi Wang,Microsoft Research; Fangbo Tao,University of Illinois at Urbana-Champaign; Clare R.,Voss; Army Research Laboratory Jiawei,Han; University of Illinois at Urbana-Champaig
(Paper ID:611)
TimeMachine: Timeline Generation for Knowledge-Base Entities
Tim Althoff,Stanford University; Xin Luna Dong,Google; Kevin Murphy,Google; Safa Alai,Google; Van Dang,Google; Wei Zhang,Google
(Paper ID:394)
Entity Matching across Heterogeneous Sources
Yang Yang,Tsinghua University; Yizhou Sun,Northeastern University; Jie Tang,Tsinghua University; Bo Ma,Tsinghua University; Juanzi Li,Tsinghua University
(Paper ID:548)
COSNET: Connecting Heterogeneous Social Networks with Local and Global Consistency
Yutao Zhang,Tsinghua University; Jie Tang,Tsinghua University; Zhilin Yang,Tsinghua University; Jian Pei,Simon Fraser University; Philip S.,Yu; University of Illinois at Chicag
(Paper ID:54)
Research Session RT10: Applications 2
Tuesday 3:20 pm–5:00 pm | Level 2 – Room 3 & 4
Chair: Hui Xiong
An Effective Marketing Strategy for Revenue Maximization with a Quantity ConstraintYa-Wen Teng,National Taiwan University; Chih-Hua Tai,National Taipei University; Philip S.,Yu; University of Illinois at Chicago & Tsinghua University, Beijing, China Ming-Syan,Chen; National Taiwan Universit
(Paper ID:130)
Set Cover at Web Scale
Stergios Stergiou,Yahoo! Labs; Kostas Tsioutsiouliklis,Yahoo! Labs
(Paper ID:321)
Algorithmic Cartography: Placing Points of Interest and Ads on Maps
Mohammad Mahdian,Google; Okke Schrijvers,Stanford University; Sergei Vassilvitskii,Google
(Paper ID:675)
Predicting Winning Price in Real Time Bidding with Censored Data
Wush Chi-Hsuan,Wu; National Taiwan Univ. Mi-Yen,Yeh; Academia Sinica Ming-Syan,Chen; National Taiwan Univ
(Paper ID:112)
Statistical Arbitrage Mining for Display Advertising
Weinan Zhang,University College London; Jun Wang,University College London
(Paper ID:56)
Research Session RT11: Sampling and Streams
Tuesday 3:20 pm–5:00 pm | Level 2 – Room 5 & 6
Chair: Saharon Rosset
Monitoring Least Squares Models of Distributed StreamsMoshe Gabel,Technion - Israel Institute of Technology; Daniel Keren,Haifa University; Assaf Schuster,Technion - Israel Institute of Technology
(Paper ID:508)
Stream Sampling for Frequency Cap Statistics
Edith Cohen,Google Research
(Paper ID:118)
On the Discovery of Evolving Truth
Yaliang Li,SUNY Buffalo; Qi Li,SUNY Buffalo; Jing Gao,SUNY Buffalo; Lu Su,SUNY Buffalo; Bo Zhao,LinkedIn; Wei Fan,Baidu Big Data Lab; Jiawei Han,University of Illinois
(Paper ID:116)
Efficient Online Evaluation of Big Data Stream Classifiers
Albert Bifet,Huawei; Gianmarco de Francisci Morales,Aalto University; Jesse Read,Aalto University; Geoff Holmes,University of Waikato; Bernhard Pfahringer,University of Waikato
(Paper ID:663)
A PCA-Based Change Detection Framework for Multidimensional Data Streams
Abdulhakim A,Qahtan; King Abdullah University of Science and Technology Basma,Alharbi; King Abdullah University of Science and Technology Suojin,Wang; Texas A\&M University Xiangliang,Zhang; King Abdullah University of Science and Technolog
(Paper ID:592)
Research Session RT12: Security and Privacy
Tuesday 3:20 pm–5:00 pm | Level 4 – Room 2 & 3
Chair: Arno Siebes
VEWS: A Wikipedia Vandal Early Warning SystemSrijan Kumar,University of Maryland; Francesca Spezzano,University of Maryland; V.S. Subrahmanian,University of Maryland
(Paper ID:637)
Scalable Blocking for Privacy Preserving Record Linkage
Alexandros Karakasidis,Hellenic Open University; Georgia Koloniari,University of Macedonia; Vassilios S.,Verykios; Hellenic Open Universit
(Paper ID:183)
Differentially Private High-Dimensional Data Publishing via Sampling-Based Inference
Rui Chen,Samsung Research America; Qian Xiao,National University of Singapore; Yu Zhang,Hong Kong Baptist University; Jianliang Xu,Hong Kong Baptist University
(Paper ID:701)
On Estimating the Swapping Rate for Categorical Data
Daniel Kifer,Penn State University
(Paper ID:650)
Maximum Likelihood Postprocessing for Differential Privacy under Consistency Constraints
Jaewoo Lee,Penn State University; Yue Wang,Penn State University; Daniel Kifer,Penn State University
(Paper ID:626)
Research Session RT13: Mining Rich Data Types 2
Wednesday 10:20 am–12:00 pm | Level 3 – Ballroom A
Chair: Albert Bifet
Assembler: Efficient Discovery of Spatial Co-evolving Patterns in Massive Geo-sensory DataChao Zhang,University of Illinois at Urbana-Champaign; Yu Zheng,Microsoft Research; Xiuli Ma,Peking University; Jiawei Han,University of Illinois at Urbana-Champaign
(Paper ID:775)
TOPTRAC: Topical Trajectory Pattern Mining
Younghoon Kim,Hanyang University; Jiawei Han,University of Illinois at Urbana-Champaign; Cangzhou Yuan,Beihang University
(Paper ID:466)
Modeling User Mobility for Location Promotion in Location-based Social Networks
Wen-Yuan Zhu,National Chiao Tung University; Wen-Chih Peng,National Chiao Tung University; Ling-Jyh Chen,Academia Sinica; Kai Zheng,The University of Queensland; Xiaofang Zhou,The University of Queensland
(Paper ID:421)
A Decision Tree Framework for Spatiotemporal Sequence Prediction
Taehwan Kim,Toyota Technological Institute at Chicago; Yisong Yue,California Institute of Technology; Sarah Taylor,Disney Research Pittsburgh; Iain Matthews,Disney Research Pittsburgh
(Paper ID:570)
State-Driven Dynamic Sensor Selection and Prediction with State-Stacked Sparseness
Guo-Jun Qi,University of Central Florida; Charu Aggarwal,IBM T.J. Watson Research Center; Deepak Turaga,IBM T.J. Watson Research Center; Daby Sow,IBM T.J. Watson Research Center; Phil Anno,ConocoPhillips
(Paper ID:733)
Research Session RT14: Crowds and Users
Wednesday 10:20 am–12:00 pm | Level 3 – Ballroom B
Chair: Xiang Ren
Modeling Truth Existence in Truth DiscoveryShi Zhi,University of Illinois at Urbana-Champaign; Bo Zhao,LinkedIn; Wenzhu Tong,University of Illinois at Urbana-Champaign; Jing Gao,SUNY Buffalo; Dian Yu,Rensselaer Polytechnic Institute; Heng Ji,Rensselaer Polytechnic Institute; Jiawei Han,University of Illinois at Urbana-Champaign
(Paper ID:456)
Exploiting Relevance Feedback in Knowledge Graph Search
Yu Su,University of California, Santa Barbara; Shengqi Yang,University of California, Santa Barbara; Huan Sun,University of California, Santa Barbara; Mudhakar Srivatsa,IBM Research; Sue Kase,U.S. Army Research Laboratory; Michelle Vanni,U.S. Army Research Laboratory; Xifeng Yan,University of California, Santa Barbara
(Paper ID:340)
Graph Query Reformulation with Diversity
Davide Mottin,University of Trento; Francesco Bonchi,Yahoo Labs; Francesco Gullo,Yahoo Labs
(Paper ID:472)
FaitCrowd: Fine Grained Truth Discovery for Crowdsourced Data Aggregation
Fenglong Ma,SUNY Buffalo; Yaliang Li,SUNY Buffalo; Qi Li,SUNY Buffalo; Minghui Qiu,Singapore Management University; Jing Gao,SUNY Buffalo; Shi Zhi,University of Illinois Urbana-Champaign; Lu Su,SUNY Buffalo; Bo Zhao,LinkedIn; Heng Ji,Rensselaer Polytechnic Institute; Jiawei Han,University of Illinois Urbana-Champaign
(Paper ID:317)
Debiasing Crowdsourced Batches
Honglei Zhuang,University of Illinois at Urbana-Champaign; Aditya Parameswaran,University of Illinois at Urbana-Champaign; Dan Roth,University of Illinois at Urbana-Champaign; Jiawei Han,University of Illinois at Urbana-Champaign
(Paper ID:323)
Research Session RT15: Healthcare and Medicine 1
Wednesday 10:20 am-12:00 pm | Level 2 – State Room
Chair: Vincent S. Tseng
Hierarchical Graph-Coupled HMMs on Heterogeneity and Personalized HealthKai Fan,Duke University; Marisa Eisenberg,University of Michigan-School of Public Health, Ann Arbor; Alison Walsh,University of Michigan-School of Public Health, Ann Arbor; Allison Aiello,University of North Carolina-Chapel Hill; Katherine Heller,Duke University
(Paper ID:396)
Simultaneous Modeling of Multiple Diseases for Mortality Prediction in Acute Hospital Care
Nozomi Nori,Kyoto University; Hisashi Kashima,Kyoto University; Kazuto Yamashita,Kyoto University; Hiroshi Ikai,Kyoto University; Yuichi Imanaka,Kyoto University
(Paper ID:302)
Dynamically Modeling Patient?s Health State from Electronic Medical Records: A Time Series Approach
Karla L,Caballero Barajas; University of California Santa Cruz Ram,Akella; University of California Berkele
(Paper ID:178)
Instance Weighting for Patient-Specific Risk Stratification Models
Jen J.,Gong; Massachusetts Institute of Technology Thoralf,M.; Sundt Massachusetts General Hospital,James; D. Rawn,Brigham and Women's Hospital; John V.,Guttag; Massachusetts Institute of Technolog
(Paper ID:796)
Deep Computational Phenotyping
David Kale,University of Southern California; Zhengping Che,University of Southern California; Wenzhe Li,University of Southern California; Mohammad Taha,Bahadori; University of Southern California Yan,Liu; University of Southern Californi
(Paper ID:624)
Research Session RT16: Knowledge Discovery
Wednesday 10:20 am–12:00 pm | Level 2 – Room 3&4
Chair: Xiangliang Zhang
Optimal Kernel Group Transformation for Exploratory Regression Analysis and GraphicsChao Pan,Purdue University; Qiming Huang,Purdue University; Michael Zhu,Purdue University
(Paper ID:410)
Towards Decision Support and Goal Achievement: Identifying Action-Outcome Relationships from Social Media
Emre Kiciman,Microsoft Research; Matthew Richardson,Microsoft Research
(Paper ID:312)
Longitudinal LASSO: Jointly Learning Features and Temporal Contingency for Outcome Prediction
Tingyang Xu,University of Connecticut; Jiangwen Sun,University of Connecticut; Jinbo Bi,University of Connecticut
(Paper ID:830)
Trading Interpretability for Accuracy: Oblique Treed Sparse Additive Models
Jialei Wang,University of Chicago; Ryohei Fujimaki,NEC Laboratories America; Yosuke Motohashi,NEC Corporation
(Paper ID:855)
Portraying Collective Spatial Attention in Twitter
Amilien Antoine,Kyoto Sangyo University; Adam Jatowt,Kyoto University; Shoko Wakamiya,Kyoto Sangyo University; Yukiko Kawai,Kyoto Sangyo University; Toyokazu Akiyama,Kyoto Sangyo University
(Paper ID:927)
Research Session RT17: Social and Graphs 3
Wednesday 1:00 pm–3:00 pm | Level 3 – Ballroom B
Chair: Tina Eliassi-Rad
Edge-Weighted Personalized PageRank: Breaking A Decade-Old Performance BarrierWenlei Xie,Cornell University; David Bindel,Cornell University; Alan Demers,Cornell University; Johannes Gehrke,Cornell University
(Paper ID:117)
SEISMIC: A Self-Exciting Point Process Model for Predicting Tweet Popularity
Qingyuan Zhao,Stanford University; Murat A.,Erdogdu; Stanford University Hera,Y.; He Stanford University,Anand; Rajaraman Stanford University,Jure; Leskovec Stanford Universit
(Paper ID:819)
Beyond Triangles: A Distributed Framework for Estimating 3-profiles of Large Graphs
Ethan R.,Elenberg; The University of Texas Karthikeyan,Shanmugam; The University of Texas Michael,Borokhovich; The University of Texas Alexandros,G.; Dimakis The University of Texa
(Paper ID:896)
Scalable Large Near-Clique Detection in Large-Scale Networks via Sampling
Michael Mitzenmacher,Harvard University; Jakub Pachocki,Carnegie Mellon University; Richard Peng,MIT; Charalampos Tsourakakis,Harvard University; Shen Chen Xu,Carnegie Mellon University
(Paper ID:720)
Efficient PageRank Tracking in Evolving Networks
Naoto Ohsaka,The University of Tokyo; Takanori Maehara,Shizuoka University; Ken-ichi Kawarabayashi,National Institute of Informatics
(Paper ID:228)
MASCOT: Memory-efficient and Accurate Sampling for Counting Local Triangles in Graph Streams
Yongsub Lim,KAIST; U Kang,KAIST
(Paper ID:163)
Research Session RT18: Clustering and Text
Wednesday 1:00 pm–3:00 pm | Level 2 – State Room
Chair: Jiawei Han
Reconstructing Textual Documents from n-gramsMatthias Gall?,Xerox Research Centre Europe; Mat?as Tealdi,Universidad Nacional de C?rdoba
(Paper ID:605)
Incorporating World Knowledge to Document Clustering via Heterogeneous Information Networks
Chenguang Wang,Peking University; Yangqiu Song,University of Illinois at Urbana-Champaign; Ahmed El-Kishky,University of Illinois at Urbana-Champaign; Dan Roth,University of Illinois at Urbana-Champaign; Ming Zhang,Peking University; Jiawei Han,University of Illinois at Urbana-Champaign
(Paper ID:672)
Spectral Ensemble Clustering
Hongfu Liu,College of Engineering, Northeastern University; Tongliang Liu,University of Technology, Sydney; Junjie Wu,Beihang University; Dacheng Tao,University of Technology, Sydney; Yun Fu,College of Engineering, Northeastern University
(Paper ID:174)
PTE: Predictive Text Embedding through Large-scale Heterogeneous Text Networks
Jian Tang,Microsoft Research Asia; Meng Qu,Peking University; Qiaozhu Mei,University of Michigan
(Paper ID:292)
Diversifying Restricted Boltzmann Machine for Document Modeling
Pengtao Xie,Carnegie Mellon University; Yuntian Deng,Carnegie Mellon University; Eric Xing,Carnegie Mellon University
(Paper ID:33)
Dirichlet-Hawkes Processes with Applications to Clustering Continuous-Time Document Streams
Nan Du,Georgia Institute of Technology; Mehrdad Farajtabar,Georgia Institute of Technology; Amr Ahmed,Google Strategic Technologies; Alexander J.,Smola; Carnegie Mellon University Le,Song; Georgia Institute of Technolog
(Paper ID:876)
Research Session RT19: Semi-supervised Learning and Kernels
Wednesday 1:00 pm–3:00 pm | Level 2 – Room 3 & 4
Chair: Saharon Rosset
Reducing the Unlabeled Sample Complexity of Semi-Supervised Multi-View LearningChao Lan,University of Kansas; Jun Huan,University of Kansas
(Paper ID:869)
Robust Treecode Approximation for Kernel Machines
William B.,March; University of Texas Bo,Xiao; University of Texas Sameer,Tharakan; University of Texas Chenhan,D.; Yu University of Texas,George; Biros University of Texa
(Paper ID:80)
Deep Graph Kernels
Pinar Yanardag,Purdue University; SVN Vishwanathan,University of California, Santa Cruz
(Paper ID:921)
From Groups to Individual Labels using Deep Features
Dimitrios Kotzias,University of California Irvine; Misha Denil,University of Oxford; Nando de Freitas,University of Oxford; Padhraic Smyth,University of California Irvine
(Paper ID:705)
Using local spectral methods to robustify graph-based learning algorithms
David F,Gleich; Purdue University Michael,W; Mahoney University of California Berkele
(Paper ID:683)
Online Outlier Exploration Over Large Datasets
Lei Cao,Worcester Polytechnic Institute; Mingrui Wei,Worcester Polytechnic Institute; Di Yang,Oracle Corporation; Elke A,Rundensteiner; Worcester Polytechnic Institut
(Paper ID:723)
Research Session RT20: Recommender Systems 1
Wednesday 3:20 pm–5:00 pm | Level 3 – Ballroom B
Chair: U Kang
Matrix Completion with QueriesNatali Ruchansky,Boston University; Mark Crovella,Boston University; Evimaria Terzi,Boston University
(Paper ID:6)
Fast and Robust Parallel SGD Matrix Factorization
Jinoh Oh,POSTECH; Wook-Shin Han,POSTECH; Hwanjo Yu,POSTESCH; Xiaoqian Jiang,University of California at San Diego
(Paper ID:352)
Collaborative Deep Learning for Recommender Systems
Hao Wang,HKUST; Naiyan Wang,HKUST; Dit-Yan Yeung,HKUST
(Paper ID:88)
Dynamic Matrix Factorization with Priors on Unknown Values
Robin Devooght,IRIDIA, ULB; Nicolas Kourtellis,Telefonica Research; Amin Mantrach,Yahoo Labs
(Paper ID:486)
Real Time Recommendations from Connoisseurs
Noriaki Kawamae,Tokyo Denki University
(Paper ID:8)
Research Session RT21: Pattern Mining
Wednesday 3:20 pm– 5:00 pm | Level 2 – State Room
Chair: Bart Goethals
Accelerating Dynamic Time Warping Clustering with a Novel Admissible Pruning StrategyNurjahan Begum,University of California, Riverside; Liudmila Ulanova,University of California, Riverside; Jun Wang,University of Texas at Dallas; Eamonn Keogh,University of California, Riverside
(Paper ID:171)
Discovery of Meaningful Rules in Time Series
Mohammad Shokoohi-Yekta,University of California, Riverside; Yanping Chen,University of California, Riverside; Bilson Campana,University of California, Riverside; Bing Hu,University of California, Riverside; Jesin Zakaria,University of California, Riverside; Eamonn Keogh,University of California, Riverside
(Paper ID:290)
Fast and Memory-Efficient Significant Pattern Mining via Permutation Testing
Felipe Llinares-L?pez,ETH Z?rich; Mahito Sugiyama,Osaka University; Laetitia Papaxanthos,ETH Z?rich; Karsten Borgwardt,ETH Z?rich
(Paper ID:617)
Mining Frequent Itemsets through Progressive Sampling with Rademacher Averages
Matteo Riondato,Brown University; Eli Upfal,Brown University
(Paper ID:40)
Modeling Large Social Networks in Context
2015 SIGKDD Doctoral Dissertation Award (Runner-up)
Qirong Ho
Research Session RT22: Transfer Learning
Wednesday 3:20 pm–5:00 pm | Level 2 – Room 3&4
Chair: Dacheng Tao
Deep Model Based Transfer and Multi-Task Learning for Biological Image AnalysisWenlu Zhang,Old Dominion University; Rongjian Li,Old Dominion University; Tao Zeng,Old Dominion University; Qian Sun,Arizona State University; Sudhir Kumar,Temple University; Jieping Ye,University of Michigan; Shuiwang Ji,Old Dominion University
(Paper ID:272)
Adaptation Algorithm and Theory Based on Generalized Discrepancy
Corinna Cortes,Google Research; Mehryar Mohri,Courant Institute of Mathematical Sciences; Google Research; Andres Munoz Medina,Courant Institute of Mathematical Sciences
(Paper ID:646)
Learning Tree Structure in Multi-Task Learning
Lei Han,Hong Kong Baptist University; Yu Zhang,Hong Kong Baptist University
(Paper ID:773)
Transitive Transfer Learning
Ben Tan,Hong Kong University of Science and Technology; Yangqiu Song,University of Illinois at Urbana-Champaign; Erheng Zhong,Personalization Sciences, Yahoo Labs; Qiang Yang,Hong Kong University of Science and Technology
(Paper ID:205)
Model Multiple Heterogeneity via Hierarchical Multi-Latent Space Learning
Pei Yang,Arizona State University; Jingrui He,Arizona State University
(Paper ID:418)
Research Session RT23: Applications 3
Thursday 10:20 am– 12:00 pm | Level 3 – Ballroom A
Chair: Sofus Macskássy
Who supported Obama in 2012? Ecological inference through distribution regressionSeth R,Flaxman; Carnegie Mellon University Yu-Xiang,Wang; Carnegie Mellon University Alexander,J; Smola Carnegie Mellon Universit
(Paper ID:246)
Certifying and removing disparate impact
Michael Feldman,Haverford College; Sorelle A.,Friedler; Haverford College John,Moeller; University of Utah Carlos,Scheidegger; University of Arizona Suresh,Venkatasubramanian; University of Uta
(Paper ID:314)
Inside Jokes: Identifying Humorous Cartoon Captions
Dafna Shahaf,Microsoft Research; Eric Horvitz,Microsoft Research; Robert Mankoff,The New Yorker Magazine
(Paper ID:725)
Cinema Data Mining: The Smell of Fear
Jörg Wicker, Johannes Gutenberg-Universität Mainz; Nicolas Krauter, Johannes Gutenberg-Universität Mainz;Bettina Derstorff, Max-Planck-Institut für Chemie; Christof Stönner, Max-Planck-Institut für Chemie; Efstratios Bourtsoukidis, Max-Planck-Institut für Chemie; Thomas Klüpfel, Max-Planck-Institut für Chemie; Jonathan Williams, Max-Planck-Institut für Chemie;Stefan Kramer, Johannes Gutenberg-Universität Mainz
(Paper ID:833)
Co-Clustering based Dual Prediction for Cargo Pricing Optimization
Yada Zhu,IBM Research; Hongxia Yang,Yahoo! Inc; Jingrui He,Arizona State University
(Paper ID:452)
Research Session RT24: Recommender Systems 2
Thursday 10:20 am–12:00 pm | Level 3 – Ballroom B
Chair: Jana Doppa
A Collective Bayesian Poisson Factorization Model for Cold-start Local Event RecommendationWei Zhang,Tsinghua University; Jianyong Wang,Tsinghua University
(Paper ID:450)
Inferring Networks of Substitutable and Complementary Products
Julian McAuley,UC San Diego; Rahul Pandey,Pinterest; Jure Leskovec,Stanford University
(Paper ID:709)
SCRAM: A Sharing Considered Route Assignment Mechanism for Fair Taxi Route Recommendations
Shiyou Qian, Shanghai Jiao Tong University; Jian Cao, Shanghai Jiao Tong University; Frédéric Le Mouël, University of Lyon, INSA-Lyon; Issam Sahel, University of Lyon, INSA-Lyon; Minglu Li, Shanghai Jiao Tong University
(Paper ID:23)
Regularity and Conformity: Location Prediction Using Heterogeneous Mobility Data
Yingzi Wang,University of Science and Technology of China; Nicholas Jing Yuan,Microsoft Research; Defu Lian,Big Data Research Center, University of Electronic Science and Technology of China; Linli Xu,University of Science and Technology of China; Xing Xie,Microsoft Research; Enhong Chen,University of Science and Technology of China; Yong Rui,Microsoft Research
(Paper ID:515)
Geo-SAGE: A Geographical Sparse Additive Generative Model for Spatial Item Recommendation
Weiqing Wang,The University of Queensland; Hongzhi Yin,The University of Queensland; Ling Chen,University of Technology, Sydney; Yizhou Sun,Northeastern University; Shazia Sadiq,The University of Queensland; Xiaofang Zhou,The University of Queensland
(Paper ID:449)
Research Session RT25: Dimensionality Reduction and Clustering 1
Thursday 10:20 am–12:00 pm | Level 2 – State Room
Chair: Paul Beinat
Adaptive Message Update for Fast Affinity PropagationYasuhiro Fujiwara,NTT Software Innovation Center; Makoto Nakatsuji,NTT Service Evolution Laboratories; Hiroaki Shiokawa,NTT Software Innovation Center; Yasutoshi Ida,NTT Software Innovation Center; Machiko Toyoda,NTT Software Innovation Center
(Paper ID:127)
Turn Waste into Wealth: On Simultaneous Clustering and Cleaning over Dirty Data
Shaoxu Song,Tsinghua University; Chunping Li,Tsinghua University; Xiaoquan Zhang,Tsinghua University
(Paper ID:327)
A Clustering-Based Framework to Control Block Sizes for Entity Resolution
Jeffrey Fisher,Australian National University; Peter Christen,Australian National University; Qing Wang,Australian National University; Erhard Rahm,University of Leipzig
(Paper ID:791)
Estimating Local Intrinsic Dimensionality
Laurent Amsaleg,CNRS / IRISA Rennes; Oussama Chelly,National Institute of Informatics; Teddy Furon,INRIA / IRISA Rennes; St?phane Girard,INRIA Grenoble; Michael E,Houle; National Institute of Informatics Ken-ichi,Kawarabayashi; National Institute of Informatics Michael,Nett; Google Japa
(Paper ID:834)
Unsupervised Feature Selection with Adaptive Structure Learning
Liang Du,ISCAS; Yi-Dong Shen,ISCAS
(Paper ID:482)
Research Session RT26: Healthcare and Medicine 2
Thursday 10:20 am–12:00 pm | Level 2 – Room 2
Chair: Balaji Krishnapuram
Where to Deploy the Next Monitoring Station? A Joint Air Quality Inference and Recommendation System for Building New Measurement StationsHsun-Ping Hsieh,National Taiwan University; Shou-De Lin,National Taiwan University; Yu Zheng,Microsoft Research
(Paper ID:476)
LINKAGE: An Approach for Comprehensive Risk Prediction for Care Management
Zhaonan Sun,IBM T. J. Watson Research Center; Fei Wang,University of Connecticut; Jianying Hu,IBM T. J. Watson Research Center
(Paper ID:371)
Temporal Phenotyping from Longitudinal Electronic Health Records: A Graph Based Framework
Chuanren Liu,Drexel University; Fei Wang,University of Connecticut; Jianying Hu,IBM T. J. Watson Research Center; Hui Xiong,Rutgers University
(Paper ID:543)
Dynamic Poisson Autoregression for Influenza-Like-Illness Case Counts Prediction
Zheng Wang,University of Michigan, Ann Arbor; Prithwish Chakraborty,Virginia Tech; Sumiko R,Mekaru; Boston Children's Hospital John,S; Brownstein Boston Children's Hospital,Jieping; Ye University of Michigan, Ann Arbor,Naren; Ramakrishnan Virginia Tec
(Paper ID:186)
Unified and Contrasting Cuts in Multiple Graphs: Application to Medical Imaging Segmentation
Chia-Tung Kuo,University of California, Davis; Xiang Wang,Google; Peter Walker,Naval Medical Research Center; Owen Carmichael,University of California, Davis; Jieping Ye,University of Michigan, Ann Arbor; Ian Davidson,University of California, Davis
(Paper ID:333)
Research Session RT27: Social and Graphs 4
Thursday 1:00 pm–3:00 pm | Level 3 – Ballroom B
Chair: Matteo Riondato
Community Detection based on Distance DynamicsJunming Shao,University of Electronic Science and Technology of China; Zhichao Han,University of Electronic Science and Technology of China; Qinli Yang,University of Electronic Science and Technology of China; Tao Zhou,University of Electronic Science and Technology of China
(Paper ID:252)
Probabilistic Community and Role Model for Social Networks
Yu Han,Tsinghua University; Jie Tang,Tsinghua University
(Paper ID:91)
TimeCrunch: Interpretable Dynamic Graph Summarization
Neil Shah,Carnegie Mellon University; Danai Koutra,Carnegie Mellon University; Tianmin Zou,Carnegie Mellon University; Brian Gallagher,Lawrence Livermore National Laboratory; Christos Faloutsos,Carnegie Mellon University
(Paper ID:342)
Online Influence Maximization
Siyu Lei,University of Hong Kong; Silviu Maniu,Huawei Noah's Ark Lab; Luyi Mo,University of Hong Kong; Reynold Cheng,University of Hong Kong; Pierre Senellart,Telecom ParisTech
(Paper ID:77)
Reciprocity in Social Networks with Capacity Constraints
Bo Jiang,University of Massachusetts; Zhi-Li Zhang,University of Minnesota; Don Towsley,University of Massachusetts
(Paper ID:872)
Why It Happened: Identifying and Modeling the Reasons of the Happening of Social Events
Yu Rong,The Chinese University of Hong Kong; Hong Cheng,The Chinese University of Hong Kong; Zhiyu Mo,The Chinese University of Hong Kong
(Paper ID:276)
Research Session RT28: Dimensionality Reduction and Clustering 2
Thursday 1:00 pm–3:00 pm | Level 2 – State Room
Chair: Katharina Morik
Heterogeneous Network Embedding via Deep ArchitecturesShiyu Chang,University of Illinois at Urbana-Champaign; Wei Han,University of Illinois at Urbana-Champaign; Jiliang Tang,Arizona State University; Guo-Jun Qi,University of Central Florida; Charu C,Aggarwal; IBM T.J. Watson Research Center Thomas,S; Huang University of Illinois at Urbana-Champaig
(Paper ID:208)
On the formation of circles in co-authorship networks
Tanmoy Chakraborty,Indian Institute of Technology, Kharagpur; Sikhar Patranabis,Indian Institute of Technology, Kharagpur; Pawan Goyal,Indian Institute of Technology, Kharagpur; Animesh Mukherjee,Indian Institute of Technology, Kharagpur
(Paper ID:190)
Non-exhaustive, Overlapping Clustering via Low-Rank Semidefinite Programming
Yangyang Hou,Purdue University; Joyce Jiyoung,Whang; University of Texas at Austin David,F; Gleich Purdue University,Inderjit; S Dhillon,University of Texas at Austin
(Paper ID:798)
Subspace Clustering Using Log-determinant Rank Approximation
Chong Peng,Southern Illinois University Carbondale; Zhao Kang,Southern Illinois University Carbondale; Huiqing Li,Southern Illinois University Carbondale; Qiang Cheng,Southern Illinois University Carbondale
(Paper ID:271)
More Constraints, Smaller Coresets: Constrained Matrix Approximation of Sparse Big Data
Dan Feldman,University of Haifa; Tamir Tassa,The Open University
(Paper ID:315)
Dimensionality Reduction via Graph Structure Learning
Qi Mao,SUNY at Buffalo; Li Wang,University of Victoria; Steve Goodison,Mayo Clinic; Yijun Sun,SUNY at Buffalo
(Paper ID:304)
Research Session RT29: Supervised Learning
Thursday 1:00 pm–3:00 pm | Level 2 – Room 2
Chair: Paul Beinat
Quick sensitivity analysis for incremental data modification and its application to leave-one-out CV in linear classification problemsShota Okumura,Nagoya Institute of Technology; Yoshiki Suzuki,Nagoya Institute of Technology; Ichiro Takeuchi,Nagoya Institute of Technology
(Paper ID:496)
Warm Start for Parameter Selection of Linear Classifiers
Bo-Yu Chu,Dept. of Computer Science, National Taiwan Univ.; Chia-Hua Ho,Dept. of Computer Science, National Taiwan Univ.; Cheng-Hao Tsai,Dept. of Computer Science, National Taiwan Univ.; Chieh-Yen Lin,Dept. of Computer Science, National Taiwan Univ.; Chih-Jen Lin,Dept. of Computer Science, National Taiwan Univ.
(Paper ID:431)
Discovering and Exploiting Deterministic Label Relationships in Multi-Label Learning
Christina Papagiannopoulou,Aristotle University of Thessaloniki; Grigorios Tsoumakas,Aristotle University of Thessaloniki; Ioannis Tsamardinos,University of Crete - Institute of Computer Science, FORTH
(Paper ID:262)
Optimal Action Extraction for Random Forests and Boosted Trees
Zhicheng Cui,Washington University in St. Louis; Wenlin Chen,Washington University in St. Louis; Yujie He,Washington University in St. Louis; Yixin Chen,Washington University in St. Louis
(Paper ID:128)
The Child is Father of the Man: Foresee the Success at the Early Stage
Liangyue Li,Arizona State University; Hanghang Tong,Arizona State University
(Paper ID:459)
Learning with similarity functions on graphs using matchings of geometric embeddings
Fredrik D,Johansson; Chalmers University of Technology Devdatt,Dubhashi; Chalmers University of Technolog
(Paper ID:461)
Research Session RT30: Similarity and Hashing
Thursday 1:00 pm–3:00 pm | Level 4 – Room 2&3
Chair: Qi He
Panther: Fast Top-k Similarity Search on Large NetworksJing Zhang, Tsinghua University; Jie Tang, Tsinghua University; Cong Ma, Tsinghua University; Hanghang Tong, ASU; Yu Jing, Tsinghua University; Juanzi Li, Tsinghua University.
(Paper ID:53)
Cuckoo Linear Algebra
Li Zhou,Carnegie Mellon University; David G,Andersen; Carnegie Mellon University Mu,Li; Carnegie Mellon University Alexander,J; Smola Carnegie Mellon Universit
(Paper ID:26)
Selective Hashing: Closing the Gap between Radius Search and k-NN Search
Jinyang Gao,National University of Singapore; H. V. Jagadish,University of Michigan; Beng Chin Ooi,National University of Singapore; Sheng Wang,National University of Singapore
(Paper ID:154)
0-Bit Consistent Weighted Sampling
Ping Li,Rutgers University
(Paper ID:850)
Non-transitive Hashing with Latent Similarity Components
Mingdong Ou,Tsinghua National Laboratory for Information Science and Technology,Department of Computer Science and Technology, Tsinghua Univ; Peng Cui,Tsinghua National Laboratory for Information Science and Technology,Department of Computer Science and Technology, Tsinghua Univ; Fei Wang,Department of Computer Science and Engineering,School of Engineering,University of Connecticut; Jun Wang,Data Science, Alibaba Group; Wenwu Zhu,Tsinghua National Laboratory for Information Science and Technology,Department of Computer Science and Technology, Tsinghua Univ
(Paper ID:139)
Improved Bounds on the Dot Product under Random Projection and Random Sign Projection
Ata Kaban,University of Birmingham
(Paper ID:621)
Industry & Government Session IG01: Big Data
Tuesday 10:20 am–12:00 pm | Level 4 – Room 2 & 3
Chair: Ranga Vatsavai
An Architecture for Agile Machine Learning in Real-Time ApplicationsJohann Schleier-Smith, if(we) Inc.
(Paper ID: 198)
Proof Protocol for a Machine Learning Technique Making Longitudinal Predictions in Dynamic Contexts
Kevin Pratt, ZZAlpha Ltd.
(Paper ID: 88)
Distributed Personalization
Xu Miao, LinkedIn; Chun-te Chu, Microsoft; Lijun Tang, LinkedIn; yitong Zhou, LinkedIn; Joel Young, LinkedIn; Anmol Bhasin,
(Paper ID: 194)
Predicting Voice Elicited Emotions
Ying Li, Jobaline; Jose Contreras, Jobaline Inc.; Luis Salazar, Jobaline Inc.
(Paper ID: 165)
Traffic measurement and route recommendation system for Mass Rapid Transit (MRT)
Thomas Holleczek, Singtel; Han Leong Goh, Singtel; Antonatos Spyridon, Singtel; Dang The Anh, Singtel; Yunye Jin, Singtel; Samantha Low, Singtel; Amy Shi-Nash, Singtel; Shanyang Yin,
(Paper ID: 85)
Industry & Government Session IG02: E-Commerce and IR
Tuesday 10:20 am–12:00 pm | Level 4 – Room 4 & 5
Chair: Mohit Kumar
Leveraging Knowledge Bases for Contextual Entity ExplorationJoonseok Lee, Georgia Institute of Technolog; Bo Zhao, Microsoft Research; Yuanhua Lv, Microsoft Research; Ariel Fuxman, Google Inc.
(Paper ID: 17)
Stock Constrained Recommendation in Tmall
Wenliang Zhong, Alibaba Group; Rong Jin, Michigan State University; Cheng Yang,; XIaowei Yan,; Qi Zhang,; Qiang Li,
(Paper ID: 22)
Going In-depth: Finding Longform on the Web
Virginia Smith, UC Berkeley; Miriam Connor, Google Inc.; Isabelle Stanton, Google Inc
(Paper ID: 112)
Building Discriminative User Profiles for Large-scale Content Recommendation
Nathan Liu,; Erheng Zhong, Yahoo; Yue Shi,; Suju Rajan, Yahoo! Labs
(Paper ID: 139)
E-commerce in your Inbox: Cross-domain product recommendations at scale
Mihajlo Grbovic, Yahoo Labs; Vladan Radosavljevic, Yahoo Labs; Nemanja Djuric, Yahoo Labs; Narayan Bhamidipati, Yahoo Labs
(Paper ID: 195)
Industry & Government Session IG03: Applications
Tuesday 1:00 pm–3:00 pm | Level 4 – Room 4 & 5
Chair: Rohan Baxter
Efficient Long-Term Degradation Profiling in Time Series for Complex Physical SystemsLiudmila Ulanova, UC Riverside; Tan Yan, NEC Laboratories America; Haifeng Chen, NEC Research Lab; Geoff Jiang, NEC Laboratories America; Eamonn Keogh, UC Riverside; Kai Zhang, Lawrence Berkeley National Laboratory
(Paper ID: 34)
ALOJA-ML: A Framework for Automating Characterization and Knowledge Discovery in Hadoop Deployments
Josep Berral, Barcelona Supercomputing Cente; Nicolas Poggi, Barcelona Supercomputing Center; David Carrera, Barcelona Supercomputing Center; Aaron Call, Barcelona Supercomputing Center; Rob Reinauer, Microsoft Corporation; Daron Green, Microsoft Corporation
(Paper ID: 114)
Mining for Causal Relationships: A Data-Driven Study of the Islamic State
Andrew Stanton, Arizona State University; Amanda Thart, Arizona State University; Ashish Jain, Arizona State University; Priyank Vyas, Arizona State University; Arpan Chatterjee, Arizona State University; Paulo Shakarian, Arizona State University
(Paper ID: 86)
Spoken English Grading: Machine Learning with Crowd Intelligence
Vinay Shashidhar, Aspiring Minds; Nishant Pandey, Aspiring Minds; Varun Aggarwal, Aspiring Minds
(Paper ID: 100)
Exploiting Data Mining for Authenticity Assessment and Protection of High-Quality Italian Wines from Piedmont
Luigi Portinale, University of Eastern Piedmont; Giorgio Leonardi, University of Eastern Piedmont; Marco Arlorio, University of Eastern Piedmont; Jean Daniel Coisson, University of Eastern Piedmont; Monica Locatelli, University of Eastern Piedmont
(Paper ID: 107)
FrauDetector: A Graph-Mining-based Framework for Fraudulent Phone Call Detection
Vincent Tseng,; Jia-Ching Ying, National Cheng Kung University; Che-Wei Huang, National Cheng Kung University; Yimin Kao, Gogolook Co. Ltd.; Kuan-Ta Chen, Academia Sinica
(Paper ID: 187)
Industry & Government Session IG04: Business, Sales, Marketing, Advertising
Tuesday 3:20 pm–5:00 pm | Level 4 – Room 4 & 5
Chair: Warwick Graco
Probabilistic modeling of a sales funnel to prioritize leadsBrendan Duncan, UC San Diego; Charles Elkan, UC San Diego
(Paper ID: 61)
Interpreting Advertiser Intent in Sponsored Search
Bhanu Vattikonda, UCSD; Alex Snoeren, UCSD; Vacha Dave, Microsoft, Mountain View; Saikat Guha, Microsoft Research, India
(Paper ID: 23)
Click-through Prediction for Advertising in Twitter Timeline
Cheng Li, University of Michigan; Yue Lu, Twitter Inc; Qiaozhu Mei, University of Michigan; Dong Wang, Twitter Inc; Sandeep Pandey, Twitter Inc
(Paper ID: 68)
Promoting Positive Post-click Experience for In-Stream Yahoo Gemini Users
Mounia Lalmas, Yahoo! Labs Barcelona; Janette Lehmann, Universitat Pompeu Fabra; Guy Shaked, Yahoo Inc.; Fabrizio Silvestri, Yahoo Labs; Gabriele Tolomei, Yahoo Labs
(Paper ID: 67)
Real-Time Bid Prediction using Thompson Sampling-Based Expert Selection
Elena Ikonomovska, Turn Inc; Sina Jafarpour, Turn Inc; Ali Dasdan, Turn Inc
(Paper ID: 75)
Industry & Government Session IG05: Social Networks
Wednesday 10:20 am–12:00 pm | Level 4 – Room 2 & 3
Chair: Paulo Shakarian
When-To-Post on Social NetworksNemanja Spasojevic, Klout Inc.; Zhisheng Li, Klout Inc; Adithya Rao, Klout Inc; Prantik Bhattacharyya, Klout Inc
(Paper ID: 73)
On the Reliability of Profile Matching Across Large Online Social Networks
Oana Goga, MPI-SWS; Patrick Loiseau, EURECOM; Robin Sommer,; Renata Teixeira,; Krishna Gummadi,
(Paper ID: 115)
From Infrastructure to Culture: A/B Testing Challenges in Large Scale Social Networks
Ya Xu, LinkedIn Corp; Nanyu Chen,; Adrian Fernandez,; Omar Sinno,; Anmol Bhasin,
(Paper ID: 116)
Utilizing Text Mining on Online Medical Forums to Predict Label Change due to Adverse Drug Reactions
Aviv Peretz, Hebrew University of Jerusalem; Ronen Feldman, Hebrew University of Jerusalem; Oded Netzer, Columbia University; Binyamin Rosenfeld, Digital Trowel
(Paper ID: 133)
Online Topic-based Social Influence Analysis for the Wimbledon Championships
Varun Embar, IBM Research; Indrajit Bhattacharya, IBM Research; Vinayaka Pandit, IBM Research; Roman Vaculin, IBM Research
(Paper ID: 93)
Industry & Government Session IG06: Business and IR
Wednesday 10:20 am–12:00 pm | Level 4 – Room 4 & 5
Chair: Debbie Zhang
Annotating needles in the haystack without looking: Product information extraction from emailsWeinan Zhang, University College London; Amr Ahmed, Google; Jie Yang, Google; Vanja Josifovski, Google; Alexander Smola, Carnegie Mellon University
(Paper ID: 66)
Big Data System for Analyzing Risky Procurement Entities
Amit Dhurandhar, IBM TJ Watson Research Center; Rajesh Kumar Ravi, IBM TJ Watson Research Center; Bruce Graves, IBM Corporation; Gopikrishnan Maniachari, IBM TJ Watson Research Center; Markus Ettl, IBM TJ Watson Research Center
(Paper ID: 14)
Client Clustering for Hiring Modeling in Work Marketplaces
Vasilis Verroios, Stanford University; Panagiotis Papadimitriou, Elance-oDesk; Ramesh Johari, Stanford University; Hector Garcia-Molina, Stanford University
(Paper ID: 84)
Voltage Correlations in Smart Meter Data
Rajendu Mitra, IBM Research; Ramachandra Kota, IBM Research; Sambaran Bandyopadhyay, IBM Research; Vijay Arya, IBM Research; Brian Sullivan, DTE Energy; Richard Mueller, DTE Energy; Heather Storey, DTE Energy; Gerard Labut, DTE Energy
(Paper ID: 98)
Optimizing Service Time in Incident Resolution Through Data-Informed Dispatching
Mirela Botezatu, IBM Research; Jasmina Bogojeska, IBM Research; ioana Giurgiu, IBM Research; Hagen Voelzer, IBM Research; Dorothea Wiesmann, IBM Research
(Paper ID: 132)
Industry & Government Session IG07: Social Good
Wednesday 1:00 pm–3:00 pm | Level 4 – Room 2 & 3
Chair: Polo Chau
A Machine Learning Framework to Identify Students at Risk of Adverse Academic OutcomesHimabindu Lakkaraju, Stanford University; Everaldo Aguiar,; Carl Shan,; David Miller,; Nasir Bhanpuri,; Rayid Ghani, University of Chicago; Kecia Addison,
(Paper ID: 166)
Early Identification of Violent Criminal Gang Members
Elham Shaabani, Arizona State University; Ashkan Aleali, Arizona State University; Paulo Shakarian, Arizona State University; John Bertetto, Chicago Police Department
(Paper ID: 164)
Mining Administrative Data to Spur Urban Revitalization
Ben Green, Harvard University; Alejandra Caro, Carnegie Mellon University; Matthew Conway, University of Chicago; Robert Manduca, Harvard University; Tom Plagge, University of Chicago; Abby Miller, Innovation Delivery Team
(Paper ID: 26)
Forecasting Fine-Grained Air Quality Based on Big Data
Yu Zheng, Microsoft Research; Xiuwen Yi, Southwest Jiaotong University; Ming Li, Microsoft Research; Ruiyuan Li, Microsoft Research; Zhangqin Shan, Fudan University; Eric Chang, Microsoft Research; Tianrui Li, Southwest Jiaotong University
(Paper ID: 41)
Scalable Machine Learning Approaches for Neighborhood Classification Using Very High Resolution Remote Sensing Imagery
Manu Sethi, University of Florida; Yupeng Yan, University of Florida; Anand Rangarajan, University of Florida; Ranga Vatsavai, North Carolina State University; Sanjay Ranka, University of Florida
(Paper ID: 191)
Predictive Modeling for Public Health: Preventing Childhood Lead Poisoning
Eric Potash, University of Chicago; Joe Walsh, University of Chicago; Joe Brew, University of Florida; Alexander Loewi, Carnegie Mellon University; Subhabrata Majumdar, University of Minnesota; Andrew Reece, Harvard University; Eric Rozier, University of Cincinnati; Emile Jorgensen, Chicago Department of Public Health; Raed Mansour, Chicago Department of Public Health; Rayid Ghani, University of Chicago
(Paper ID: 208)
Industry & Government Session IG08: Health
Wednesday 1:00 pm–3:00 pm | Level 4 – Room 4 & 5
Chair: Lin Liu
Intelligible High-Accuracy Models in HealthCare: Predicting Pneumonia Risk and Hospital 30-day ReadmissionRich Caruana, Microsoft Research; Yin Lou, LinkedIn; Paul Koch, Microsoft; Johannes Gehrke, Microsoft; Marc Sturm, NYP
(Paper ID: 143)
Dynamic Hierarchical Classification for Patient Risk-of-Readmission
Senjuti Basu Roy*, University of Washington Tacoma; Ankur Teredesai, University of Washington Tacoma; Kiyana Zolfaghar, Microsoft; Rui Liu, University of Washington Tacoma; David Hazel, KenSci Inc.; Stacey Newman, University of Washington Tacoma, Albert Marinez, MultiCare Health System
(Paper ID: 74)
Predicting Ambulance Demand: A Spatio-Temporal Kernel Approach
Zhengyi Zhou, Cornell University; David Matteson, Cornell University
(Paper ID: 29)
Discovery of Glaucoma Progressive Patterns Using Hierarchical MDL-Based Clustering
SHIGERU MAYA, The University of Tokyo; Kai Morino,; Hiroshi Murata,; Ryo Asaoka,; Kenji Yamanishi,
(Paper ID: 45)
Early Prediction of Cardiac Arrest (Code Blue) using Electronic Medical Records
Sriram Somanchi, Carnegie Mellon University; Samrachana Adhikari, Carnegie Mellon University; Allen Lin, Harvard University; Elena Eneva, Accenture; Rayid Ghani, University of Chicago
(Paper ID: 82)
Predictive Approaches for Low-cost Preventive Medicine Program in Developing Countries
Yukino Baba, National Institute of Informatics; Hisashi Kashima, Kyoto University; Yasunobu Nohara,; Eiko Kai, Kyushu University; Partha Ghosh, Grameen Communications; Rafiqul Islam, Grameen Communications; Ashir Ahmed, Kyushu University; Masahiro Kuroda, National Institute of Information and Communications Technology; Sozo Inoue, Kyushu Institute of Technology; Tatsuo Hiramatsu, The University of Tokyo; Michio Kimura,; Shuji Shimizu, Kyushu University Hospital; Kunihisa Kobayashi, Fukuoka University Chikushi Hospital; Koji Tsuda, The University of Tokyo; Masashi Sugiyama, The University of Tokyo; Mathieu Blondel, NTT Communication Science Laboratories; Naonori Ueda, NTT Communication Science Laboratories; Masaru Kitsuregawa, National Institute of Informatics; Naoki Nakashima, Kyushu University Hospital
(Paper ID: 76)
Industry & Government Session IG09: E-Commerce
Wednesday 3:20 pm– 5:00 pm | Level 4 – Room 2 & 3
Chair: Yanchang Zhao
Life-stage Prediction for Product Recommendation in E-commercePeng Jiang, Alibaba Group; Yadong Zhu, Alibaba group; Yi Zhang, University of California; Quan Yuan, Alibaba Group
(Paper ID: 10)
Focusing on the Long-term: It's Good for Users and Business
Diane Tang, Google; Henning Hohnhold, Google; Deirdre O'Brien, Google
(Paper ID: 72)
Gender and Interest Targeting for Sponsored Post Advertising at Tumblr
Mihajlo Grbovic, Yahoo Labs; Vladan Radosavljevic, Yahoo Labs; Nemanja Djuric, Yahoo Labs; Narayan Bhamidipati, Yahoo Labs
(Paper ID: 160)
One-Pass Ranking Models for Low-Latency Product Recommendations
Antonino Freno, Zalando SE; Martin Saveski,; Rodolphe Jenatton, Amazon; Cédric Archambeau, Amazon
(Paper ID: 64)
Industry & Government Session IG10: Anomaly Detection
Wednesday 3:20 pm–5:00 pm | Level 4 – Room 4 & 5
Chair: Ted Senator
Transfer Learning for Bilingual Content ClassificationQian Sun, Arizona State University; Mohammad Amin, LinkedIn Corporation; Baoshi Yan, LinkedIn Corporation; Craig Martell, LinkedIn Corporation; Vita Markman, LinkedIn Corporation; Anmol Bhasin, LinkedIn Corporation; Jieping Ye, University of Michigan
(Paper ID: 47)
Generic and Scalable Framework for Automated Time-series Anomaly Detection
Nikolay Laptev, Yahoo Labs; Saeed Amizadeh, Yahoo Labs; Ian Flint, Yahoo Labs
(Paper ID: 140)
Learning a Hierarchical Monitoring System for Detecting and Diagnosing Service Issues
Vinod Nair, Microsoft Research; Ameya Raul, Microsoft Research Inda; Shwetabh Khanduja, Microsoft Research; Vikas Bahirwani, Microsoft; S. Sundararajan, Microsoft Research; Keerthi Selvaraj, Microsoft; Steve Herbert, Microsoft; Sudheer Dhulipalla, Microsoft; Qihong Shao, Microsoft
(Paper ID: 190)
Analyzing Invariants in Cyber-Physical Systems using Latent Factor Regression
Marjan Momtazpour, Virginia Tech; Jinghe Zhang,; Saifur Rahman,; Ratnesh Sharma,; Naren Ramakrishnan,
(Paper ID: 126)
Industry & Government Session IG11: Social Media
Thursday 10:20 am–12:00 pm | Level 4 – Room 2 & 3
Chair: Qi He
Discovering Collective Narratives of Theme Parks from Large Collections of Visitorsâ Photo StreamsGunhee Kim, Seoul National University; Leonid Sigal, Disney Research
(Paper ID: 27)
User Conditional Hashtag Prediction for Images
Emily Denton, New York University; Rob Fergus, Facebook AI Research; Jason Weston, Facebook AI Research; Manohar Paluri, Facebook AI Research; Lubomir Bourdev, Facebook AI Research
(Paper ID: 55)
Whither Social Networks for Web Search?
Rakesh Agrawal, Data Insights Laboratories; Behzad Golshan, Boston University; Evangelos Papalexakis, Carnegie Mellon University
(Paper ID: 30)
Collective Spammer Detection in Evolving Multi-Relational Social Networks
Shobeir Fakhraei, University of Maryland; James Foulds, University of California, Santa Cruz; Madhusudana Shashanka, if(we) Inc.; Lise Getoor, University of California, Santa Cruz
(Paper ID: 129)
Personalizing LinkedIn Feed
Qi He, LinkedIn; Deepak Agarwal, LinkedIn; Bee-Chung Chen, LinkedIn; Zhenhao Hua, LinkedIn; Guy Lebanon, LinkedIn; Yiming Ma, LinkedIn; Pannagadatta Shivaswamy, LinkedIn; Hsiao-Ping Tseng, LinkedIn; Jaewon Yang, LinkedIn; Liang Zhang, LinkedIn
(Paper ID: 150)
Industry & Government Session IG12: Marketing and Advertising
Thursday 10:20 am–12:00 pm | Level 4 – Room 4 & 5
Chair: Simeon Simoff
How to Build Your Fan Base? The Effectiveness of Promotional Events in Social MediaPanagiotis Adamopoulos, New York University; Vilma Todri, New York University
(Paper ID: 109)
Effective Audience Extension in Online Advertising
Jianqiang Shen, Turn Inc.; Sahin Geyik, Turn Inc.; Ali Dasdan, Turn Inc
(Paper ID: 123)
Smart Pacing for Effective Online Ad Campaign Optimization
Jian Xu, Yahoo Inc; Kuang-chih Lee, Yahoo; Wentong Li, Yahoo Inc; Hang Qi, Yahoo Inc; Quan Lu, Yahoo Inc
(Paper ID: 159)
Measuring causal impact of online actions via natural experiments: application to display advertising
Daniel N. Hill, Amazon.com, Inc.; Robert Moakler, Integral Ad Science & NYU Stern; Alan E. Hubbard, University of California Berkeley; Vadim Tsemekhman, OpenDSP; Foster Provost, Integral Ad Science & NYU Stern; Kiril Tsemekhman, Integral Ad Science
(Paper ID: 183)
Visual Search at Pinterest
Yushi Jing, Pinterest; David Liu, Pinterest; Dmitry Kislyuk, Pinterest; Andrew Zhai, Pinterest; Jiajing Xu, Pinterest; Jeff Donahue, Pinterest; Sarah Tavel,
(Paper ID: 178)
Industry & Government Session IG13: Applications
Thursday 1:00 pm–3:00 pm | Level 4 – Room 4 & 5
Chair: Dragos Margineantu
Gas Concentration Reconstruction for Coal-Fired Boilers Using Gaussian ProcessChao Yuan, Siemens
(Paper ID: 163)
Predicting Serves in Tennis using Style Priors
Xinyu Wei, QUT; Patrick Lucey, Disney Research; Stuart Morgan, Australian Institute of Sport; Peter Carr, Disney Research
(Paper ID: 110)
Discerning Tactical Patterns for Professional Soccer Teams: An Enhanced Topic Model with Applications
Qing Wang, Peking University; Hengshu Zhu, Big Data Lab, Baidu Research; Wei Hu, Big Data Lab, Baidu Research; Zhiyong Shen, Big Data Lab, Baidu Research; Yuan Yao, Peking University
(Paper ID: 60)
Probabilistic Graphical Models of Dyslexia
Yair Lakretz, Tel-Aviv university; Gal Chechik, Bar-Ilan University; Naama Friedmann, Tel-Aviv University; Michal Rosen-Zvi, IBM research department
(Paper ID: 124)
Predicting Future Scientific Discoveries Based on a Networked Analysis of the Past Literature
Meenakshi Nagarajan, IBM; Angela Wilkins, Baylor College of Medicine; Benjamin Bachman, Baylor College of Medicine; Ilya Novikov, Baylor College Of Medicine; Sheng Hua Bao, IBM; Peter Haas, IBM; Maria Terron, Baylor College of Medicine; Sumit Bhatia, IBM; Anbu Adikesavan, Baylor College of Medicine; Jacques Labrie, IBM; Sam Regenbogen, Baylor College of Medicine; Christrie Buchovecky, Baylor College of Medicine; Curtis Pickering, 2The University of Texas MD Anderson Cancer Center; Linda Kato, IBM; Andreas Lisewski, Baylor College of Medicine; Ana Lelescu, IBM; Houyin Zhang, Baylor College of Medicine; Stephen Boyer, IBM; Griff Weber, IBM; Ying Chen, IBM; Lawrence Donehower, Baylor College of Medicine; Scott Spangler, IBM; Olivier Lichtarge, Baylor College of Medicine
(Paper ID: 137)
Tornado Forecasting with Multiple Markov Boundaries
Kui Yu, Simon Fraser University; Dawei Wang, University of Massachusetts Boston; Wei Ding, University of Massachusetts Boston; David Small, Tufts University; Jian Pei, Simon Fraser University; Xindong Wu, University of Vermont; Shafiqul Islam, Tufts Universit
(Paper ID: 142)