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Poster
Tue 7:00 Collaborative Machine Learning with Incentive-Aware Model Rewards
Rachael Hwee Ling Sim · Yehong Zhang · Mun Choon Chan · Bryan Kian Hsiang Low
Poster
Tue 7:00 Individual Fairness for k-Clustering
Sepideh Mahabadi · Ali Vakilian
Poster
Tue 7:00 Fair Generative Modeling via Weak Supervision
Kristy Choi · Aditya Grover · Trisha Singh · Rui Shu · Stefano Ermon
Poster
Tue 7:00 Fair Learning with Private Demographic Data
Hussein Mozannar · Mesrob Ohannessian · Nati Srebro
Poster
Tue 7:00 Optimizing Long-term Social Welfare in Recommender Systems: A Constrained Matching Approach
Martin Mladenov · Elliot Creager · Omer Ben-Porat · Kevin Swersky · Richard Zemel · Craig Boutilier
Poster
Tue 8:00 Detecting Out-of-Distribution Examples with Gram Matrices
Chandramouli Shama Sastry · Sageev Oore
Poster
Tue 8:00 Learning Fair Policies in Multi-Objective (Deep) Reinforcement Learning with Average and Discounted Rewards
Umer Siddique · Paul Weng · Matthieu Zimmer
Poster
Tue 8:00 Feature Noise Induces Loss Discrepancy Across Groups
Fereshte Khani · Percy Liang
Poster
Tue 9:00 Fiduciary Bandits
Gal Bahar · Omer Ben-Porat · Kevin Leyton-Brown · Moshe Tennenholtz
Poster
Tue 9:00 Two Simple Ways to Learn Individual Fairness Metrics from Data
Debarghya Mukherjee · Mikhail Yurochkin · Moulinath Banerjee · Yuekai Sun
Poster
Wed 5:00 Measuring Non-Expert Comprehension of Machine Learning Fairness Metrics
Debjani Saha · Candice Schumann · Duncan McElfresh · John P Dickerson · Michelle Mazurek · Michael Tschantz
Poster
Wed 5:00 Learning Structured Latent Factors from Dependent Data:A Generative Model Framework from Information-Theoretic Perspective
Ruixiang ZHANG · Masanori Koyama · Katsuhiko Ishiguro