Conventional Tutorials

We have a fantastic lineup of hands-on and conventional tutorials to be held in conjunction with KDD 2017.

Check back as we get closer to the conference for more detailed program information.

	Title	Organizers
	Large Scale Hierarchical Classification: Foundations, Algorithms and Applications	Huzefa Rangwala (George Mason University) Azad Naik (Microsoft Corporation)
	Mining Entity-Relation-Attribute Structures from Massive Text Data	Jingbo Shang (University of Illinois, Urbana-Champain) Xiang Ren (University of Illinois, Urbana-Champain) Meng Jiang (University of Illinois, Urbana-Champain) Jiawei Han (University of Illinois, Urbana-Champain)
	Deep Learning for Personalized Search and Recommender Systems	Ganesh Venkataraman Nadia Fawaz Saurabh Kataria Benjamin Le Liang Zhang (LinkedIn Corp.)
	A/B Testing at Scale: Accelerating Software Innovation	Alex Deng (Microsoft) Pavel Dmitriev (Microsoft) Somit Gupta (Microsoft) Ron Kohavi (Microsoft) Paul Raff (Microsoft) Lukas Vermeer (Booking.com)
	Learning Representations of Large-scale Networks	Jian Tang Cheng Li Qiaozhu Mei (Umich)
	Network Embedding- Enabling Network Analytics and Inference in Vector Space	Peng Cui (Tsinghua University) Jian Pei (Simon Fraser) Wenwu Zhu (Tsinghua University)
	Smart Analytics for Big Time-series Data	Yasushi Sakurai (Kumamoto University) Yasuko Matsubara (Kumamoto University) Christos Faloutsos (Carnegie Mellon University)
	Safe Data Analytics: Theory, Algorithms, and Applications	Jun Huan (KU) Chao Lan (KU) Xiaoli Li (KU)
	Recent Advances in Feature Selection: A Data Perspective	Jundong Li (Arizona State University) Jiliang Tang (Michigan State University) Huan Liu (Arizona State University)
	Making Better Use of the Crowd	Jennifer Wortman Vaughan (Microsoft Research)
	Time Series data Mining Using the Matrix Profile: A Unifying View of Motif Discovery, Anomaly Detection, Segmentation, Classification, Clustering and Similarity Joins	Abdullah Mueen (University of New Mexico) Eamonn Keogh (University of California Riverside)
	Data Mining in Unusual Domains with Information-rich Knowledge Graph Construction, Inference and Search	Mayank Kejriwal (USC-ISI Pedro Szekely (USC-ISI)
	A Critical Review of Online Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries	Alexandra Olteanu (IBM Research, US) Emre Kıcıman (Microsoft Research, US) Carlos Castillo (Eurecat, Spain) Fernando Diaz (Microsoft Research, US)
	Non-IID Learning in Big Data	Longbing Cao (UTS) Philip Yu (UIC) Guangsong Pang (UTS) Chengzhang Zhu (UTS)
	System Event Mining: Algorithms and Applications	Tao Li (Florida International University, USA) Larisa Shwartz (IBM T.J. Watson Research Center, USA) Genady Ya. Grabarnik (St. John's University, USA)
	IoT in Practice: Case Studies in Data Analytics, with Issues in Privacy and Security	Albert Bifet (Telecom ParisTech) Latifur Khan (University of Texas at Dallas) Joao Gama (University of Porto) Wei Fan (Baidu Research Big Data Lab)
	Context-Rich Recommendation via Information Network Analysis Approach	Yizhou Sun (University of California, Los Angeles) Xiang Ren (University of Illinois at Urbana-Champaign) Hongzhi Yin (The University of Queensland, Australia)
	Urban Computing: Enabling Intelligent Cities with Big Data	Yu Zheng (Microsoft Research)
	From Theory to Data Product: Applying Data Science Methods to Effect Business Change	Danielle Leighton (T4G Limited) Lindsay Brin (T4G Limited) Janet Forbes (T4G Limited)
	Data-Driven Approaches towards Malicious Behavior Modeling	Meng Jiang (University of Notre Dame) Srijan Kumar (Stanford University) VS Subrahmanian (University of Maryland, College Park) Christos Faloutsos (CMU)
	Machine Learning for Survival Analysis: Theory, Algorithms and Applications	Chandan K. Reddy (Virginia Tech) Yan Li (University of Michigan, Ann Arbor)
	Athlytics: Data Mining and Machine Learning for Sports Analytics	Konstantinos Pelechrinis (University of Pittsburgh) Evangelos Papalexakis (University of California, Riverside) Benjamin Alamar (ESPN)