| Tutorial Number |
Title |
Planned Length |
Topic |
| T01 |
Deep Learning for Brain Encoding and Decoding: Principles, Practices and Beyond |
1 |
Neuro |
| T02 |
Systems for Scalable Graph Analytics and Machine Learning: Trends and Methods |
0.25 |
Graphs, DM, ML |
| T03 |
Enhancing Graph Representation Learning through Subgraph Strategies |
0.25 |
Graphs, DM, ML |
| T04 |
Continual Learning on Graphs: Challenges, Solutions, and Opportunities |
0.25 |
Graphs, DM, ML |
| T05 |
Graph Machine Learning under Distribution Shifts: Adaptation, Generalization and Extension to LLM |
0.25 |
Graphs, DM, ML |
| T06 |
All You Ever Need to Know About Counterfactual Explanations: Fundamentals, Methods, & User Studies for XAI |
1 |
XAI |
| T07 |
Knowledge Editing for Large Language Models |
0.5 |
NLP |
| T08 |
Beyond Human Creativity: A Tutorial on Advancements in AI Generated Content |
0.5 |
NLP |
| T09 |
AI and Multi-Agent Techniques for Decentralised Energy Systems |
0.5 |
MAS |
| T10 |
AI for Financial Markets – Agent based models applied to Bond Markets: Can we build a better market using ABMs? |
0.25 |
ABM |
| T11 |
Mechanism Design without Money: Facility Location Problems |
0.25 |
OPT, GTEP |
| T12 |
Machine Learning for Streaming Data |
0.5 |
ML |
| T13 |
Deep Variational Learning |
0.5 |
ML |
| T14 |
Visually-Rich Document Understanding and Intelligence: Recent Advances and Benchmarks |
0.5 |
NLP |
| T15 |
Recommender Systems in the Era of Large Language Models (LLMs) |
0.5 |
REC, NLP |
| T16 |
Private Information Retrieval for Personalization Tutorial |
0.5 |
IR, SEC |
| T17 |
Machine ethics. A tutorial for prospective researchers |
0.5 |
ETH |
| T18 |
Automated Reasoning for Social Choice Theory |
0.5 |
GTEP |
| T19 |
Tournaments in Computational Social Choice |
0.25 |
GTEP |
| T20 |
Generative AI for Education (GAIED): Advances, Opportunities, and Challenges |
0.25 |
Education |
| T21 |
Trustworthy Machine Learning under Imperfect Data |
0.5 |
ML, SEC |
| T22 |
Strategic ML: How to Learn With Data That ‘Behaves’ |
0.5 |
ML, SEC, ETH |
| T23 |
AI Meets Values: History, Essence, and Recent Advances of Big Model’s Value Alignment |
0.5 |
ETH |
| T24 |
Demystifying RL for Large Language Models: A training paradigm shift? |
0.5 |
NLP, RL |
| T25 |
Advances in Fairness-aware Reinforcement Learning: Theory and Applications |
0.5 |
RL, ETH |
| T26 |
Toward Mitigating Misinformation and Social Media Manipulation in Foundation Model Era |
0.25 |
SEC, NLP |
| T27 |
A Copyright War: Authentication for Large Language Models |
0.25 |
NLP |
| T28 |
Towards Causal Reinforcement Learning: Empowering Agents with Causality |
0.25 |
RL |
| T29 |
Safe Reinforcement Learning: Algorithms, Theory and Applications |
0.25 |
RL, SEC |
| T30 |
Probing Machine Learning Models in Angluin’s Style |
0.25 |
ETH |
| T31 |
Curriculum Learning: Theories, Approaches, Applications, Tools, and Future Directions in the Era of Large Language Models |
0.25 |
ML |
