Fairness in Machine Learning
FDS/CADMY Research in Motion Colloquium: Aranyak Mehta (Google Research), “From Theory to Practice, and Back: Ad Auctions and Online Matching”
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 […]
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 […]
FDS Colloquium: Bhramar Mukherjee (Yale), “Analysis of “Big” Real-World Health Care Data: Promises and Perils”
Speaker: Bhramar Mukherjee, Ph.D.Senior Associate Dean of Public Health Data Science and Data EquityAnna M.R Lauder Professor of BiostatisticsProfessor of Epidemiology (Chronic Diseases) and […]
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