{"id":568,"date":"2024-05-10T05:22:20","date_gmt":"2024-05-10T05:22:20","guid":{"rendered":"https:\/\/kdd2024.kdd.org\/?page_id=568"},"modified":"2024-07-22T15:42:41","modified_gmt":"2024-07-22T15:42:41","slug":"tutorials","status":"publish","type":"page","link":"https:\/\/kdd2024.kdd.org\/tutorials\/","title":{"rendered":"Tutorials"},"content":{"rendered":"\n

Tutorials<\/strong><\/h1>\n\n\n\n
ID<\/strong><\/th>Tutorial Title<\/th>Format<\/th>Date<\/th>Time<\/strong><\/th><\/tr><\/thead>
HO-6<\/td>Multi-modal Data Processing for Foundation Models: Practical Guidances and Use Cases<\/td>Hands-on<\/td>Sunday, August 25<\/td>10:00 AM – 1:00 PM<\/td><\/tr>
HO-7<\/td>A Tutorial on Multi-Armed Bandit Applications for Large Language Models<\/td>Hands-on<\/td>Sunday, August 25<\/td>10:00 AM – 1:00 PM<\/td><\/tr>
LS-1<\/td>A Review of Graph Neural Networks in Epidemic Modeling<\/td>Lecture-Style<\/td>Sunday, August 25<\/td>10:00 AM – 1:00 PM<\/td><\/tr>
LS-3<\/td>Advances in Human Event Modeling: From Graph Neural Networks to Language Models<\/td>Lecture-Style<\/td>Sunday, August 25<\/td>10:00 AM – 1:00 PM<\/td><\/tr>
LS-4<\/td>Automated Mining of Structured Knowledge from Text in the Era of Large Language Models<\/td>Lecture-Style<\/td>Sunday, August 25<\/td>10:00 AM – 1:00 PM<\/td><\/tr>
LS-5<\/td>Bias and Unfairness in Information Retrieval Systems: New Challenges in the LLM Era<\/td>Lecture-Style<\/td>Sunday, August 25<\/td>10:00 AM – 1:00 PM<\/td><\/tr>
LS-7<\/td>Decoding the AI Pen: Techniques and Challenges in Detecting AI-Generated Text<\/td>Lecture-Style<\/td>Sunday, August 25<\/td>10:00 AM – 1:00 PM<\/td><\/tr>
LS-8<\/td>Explainable Artificial Intelligence on Biosignals for Clinical Decision Support<\/td>Lecture-Style<\/td>Sunday, August 25<\/td>10:00 AM – 1:00 PM<\/td><\/tr>
LS-10<\/td>Graph Intelligence with Large Language Models and Prompt Learning<\/td>Lecture-Style<\/td>Sunday, August 25<\/td>10:00 AM – 1:00 PM<\/td><\/tr>
LS-13<\/td>Heterogeneous Contrastive Learning for Foundation Models and Beyond<\/td>Lecture-Style<\/td>Sunday, August 25<\/td>10:00 AM – 1:00 PM<\/td><\/tr>
LS-16<\/td>Modern Recommender Systems Leveraging Generative AI: Fundamentals, Challenges and Opportunities<\/td>Lecture-Style<\/td>Sunday, August 25<\/td>10:00 AM – 1:00 PM<\/td><\/tr>
LS-17<\/td>Multimodal Pretraining, Adaptation, and Generation for Recommendation: A Tutorial<\/td>Lecture-Style<\/td>Sunday, August 25<\/td>10:00 AM – 1:00 PM<\/td><\/tr>
LS-18<\/td>RAG Meets LLMs: Towards Retrieval-Augmented Large Language Models<\/td>Lecture-Style<\/td>Sunday, August 25<\/td>10:00 AM – 1:00 PM<\/td><\/tr>
LS-20<\/td>Recent and Upcoming Developments in Randomized Numerical Linear Algebra for Machine Learning<\/td>Lecture-Style<\/td>Sunday, August 25<\/td>10:00 AM – 1:00 PM<\/td><\/tr>
LS-23<\/td>Symbolic Regression: A Pathway to Interpretability Towards Automated Scientific Discovery<\/td>Lecture-Style<\/td>Sunday, August 25<\/td>10:00 AM – 1:00 PM<\/td><\/tr>
HO-8<\/td>Domain-Driven LLM Development: Insights into RAG and Fine-Tuning Practices<\/td>Hands-on<\/td>Sunday, August 25<\/td>2:00 PM – 5:00 PM<\/td><\/tr>
HO-9<\/td>Tutorial on Graph Reasoning with LLMs (GReaL)<\/td>Hands-on<\/td>Sunday, August 25<\/td>2:00 PM – 5:00 PM<\/td><\/tr>
LS-2<\/td>A Survey on Hypergraph Neural Networks: An In-Depth and Step-By-Step Guide<\/td>Lecture-Style<\/td>Sunday, August 25<\/td>2:00 PM – 5:00 PM<\/td><\/tr>
LS-6<\/td>Causal Inference with Latent Variables: Recent Advances and Future Prospectives<\/td>Lecture-Style<\/td>Sunday, August 25<\/td>2:00 PM – 5:00 PM<\/td><\/tr>
LS-11<\/td>Graph Machine Learning Meets Multi-Table Relational Data<\/td>Lecture-Style<\/td>Sunday, August 25<\/td>2:00 PM – 5:00 PM<\/td><\/tr>
LS-14<\/td>Inference Optimization of Foundation Models on AI Accelerators<\/td>Lecture-Style<\/td>Sunday, August 25<\/td>2:00 PM – 5:00 PM<\/td><\/tr>
LS-15<\/td>Large Language Models for Graphs: Progresses and Directions<\/td>Lecture-Style<\/td>Sunday, August 25<\/td>2:00 PM – 5:00 PM<\/td><\/tr>
LS-19<\/td>Reasoning and Planning with Large Language Models in Code Development<\/td>Lecture-Style<\/td>Sunday, August 25<\/td>2:00 PM – 5:00 PM<\/td><\/tr>
LS-21<\/td>Safe Multi-Modal Machine Learning<\/td>Lecture-Style<\/td>Sunday, August 25<\/td>2:00 PM – 5:00 PM<\/td><\/tr>
LS-25<\/td>Towards Urban General Intelligence Through Urban Foundation Models<\/td>Lecture-Style<\/td>Sunday, August 25<\/td>2:00 PM – 5:00 PM<\/td><\/tr>
HO-1<\/td>Practical Machine Learning for Streaming Data<\/td>Hands-on<\/td>Monday, August 26<\/td>10:00 AM – 1:00 PM<\/td><\/tr>
HO-4<\/td>Breaking Barriers: A Hands-On Tutorial on AI-Enabled Accessibility to Social Media Content<\/td>Hands-on<\/td>Monday, August 26<\/td>10:00 AM – 1:00 PM<\/td><\/tr>
HO-2<\/td>A Hands-on Introduction to Time Series Classification and Regression<\/td>Hands-on<\/td>Monday, August 26<\/td>2:00 PM – 5:00 PM<\/td><\/tr>
HO-3<\/td>DARE to Diversify: DAta Driven and Diverse LLM REd Teaming<\/td>Hands-on<\/td>Monday, August 26<\/td>2:00 PM – 5:00 PM<\/td><\/tr>
LS-12<\/td>Grounding and Evaluation for Large Language Models: Practical Challenges and Lessons Learned<\/td>Lecture-Style<\/td>Monday, August 26<\/td>2:00 PM – 5:00 PM<\/td><\/tr>
HO-5<\/td>Privacy-Preserving Federated Learning using Flower Framework<\/td>Hands-on<\/td>Thursday, August 29<\/td>10:00 AM – 1:00 PM<\/td><\/tr>
LS-9<\/td>Foundation Models for Time Series Analysis: A Tutorial and Survey<\/td>Lecture-Style<\/td>Thursday, August 29<\/td>11:00 AM – 3:00 PM<\/td><\/tr>
LS-22<\/td>Sharing is Caring: A practical guide to FAIR(ER) open data release<\/td>Lecture-Style<\/td>Thursday, August 29<\/td>11:00 AM – 3:00 PM<\/td><\/tr>
LS-24<\/td>Systems for Scalable Graph Analytics and Machine Learning: Trends and Methods<\/td>Lecture-Style<\/td>Thursday, August 29<\/td>11:00 AM – 3:00 PM<\/td><\/tr><\/tbody><\/table><\/figure>\n","protected":false},"excerpt":{"rendered":"

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