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Privacy
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FDS/CADMY Research in Motion Colloquium: Nicolas Stier-Moses (Meta), “Pacing Mechanisms For Ad Auctions”
Research in Motion Series is co-hosted by the Center for Algorithms, Data, and Market Design at Yale (CADMY) and the Yale Institute for Foundations of Data Science (FDS). Abstract: Budgets play a significant role in real-world sequential auction markets such as those implemented by Internet companies. To maximize the value provided to auction participants, spending…
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FDS Seminar: Kumar Kshitij Patel (TTIC)
“Re-inventing Machine Learning for Multiple Distributions: Optimization, Privacy, and Incentives” Abstract: Federated Learning (FL) has emerged as a transformative framework for multi-distribution learning, driving breakthroughs in healthcare, research, finance, and consumer technologies. FL enables agents to train models on private data without sharing raw information, offering a basic yet crucial step toward safeguarding privacy while complying with…
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S&DS Seminar: Adam Smith (BU), “Privacy in Machine Learning and Statistical Inference”
Zoom Link: https://yale.zoom.us/j/94223816617 Meeting ID: 942 2381 6617 Abstract: The results of learning and statistical inference reveal information about the data they use. This talk discusses the possibilities and limitations of fitting machine learning and statistical models while protecting the privacy of individual records. I will begin by explaining what makes this problem difficult, using…