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