Tutorial: Incentives for Collaborative Learning and Data Sharing, Part I @SimonsInstitute

Tutorial: Incentives for Collaborative Learning and Data Sharing, Part I @SimonsInstitute

Uploaded February 2026 | Updated September 2026, 2 weeks ago

Han Shao (UMD),
Sai Praneeth Karimireddy (USC)
https://simons.berkeley.edu/talks/han-shao-umd-2026-01-29
Federated and Collaborative Learning Boot Camp

Tutorial: Incentives for Collaborative Learning and Data Sharing, Part I

Exact Unlearning of Finetuning Data via Model Merging at Scale

Computational Challenges and Opportunities in DNA Methylation Analysis

Talk by Inioluwa Deborah Raji (UC Berkeley)

Latent Variable models and Subset Smoothing

Approximately Packing Dijoins Via Nowhere-Zero Flows

Panel on the future of scientific research and education

Clinical Trials, EMR and AI: next steps

On Machine Learning for Prediction and Prioritization in the Allocation of Scarce Societal Resources

Unfamiliar Terrain

Constant depth pseudoentanglement - Shallow circuits, deep backstory

Can AI do research math?

Simons Institute for the Theory of Computing |

Tutorial: Incentives for Collaborative Learning and Data Sharing, Part I