LANS Seminar
Abstract: Data is the most important factor determining the quality of an AI system. However, the data commons that current AI relies on is fast collapsing. This issue is only exacerbated when considering more valuable data (e.g. healthcare) which are firmly locked behind privacy and incentive barriers.
We will examine how tools from optimization, statistics, and economics can be combined to reimagine AI infrastructure and build sustainable data ecosystems. This talk will be largely based on these three papers:
- SCAFFOLD: Stochastic Controlled Averaging for Federated Learning (arxiv)
- Evaluating and Incentivizing Diverse Data Contributions in Collaborative Learning (arxiv)
- Data Acquisition via Experimental Design for Decentralized Data Markets (arxiv)
Bio: Sai Praneeth Karimireddy is an Assistant Professor in the Thomas Lord Department of Computer Science at USC.