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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 |
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 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 |
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 |
Fair k-Centers via Maximum Matching Matthew Jones, Huy Nguyen, Thy Nguyen |
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Poster
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Wed 5:00 |
Causal Modeling for Fairness In Dynamical Systems Elliot Creager, David Madras, Toniann Pitassi, Richard Zemel |
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Poster
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Wed 5:00 |
Data preprocessing to mitigate bias: A maximum entropy based approach L. Elisa Celis, Vijay Keswani, Nisheeth K. Vishnoi |
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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 |
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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 8:00 |
Optimizing Black-box Metrics with Adaptive Surrogates Qijia Jiang, Olaoluwa Adigun, Harikrishna Narasimhan, Mahdi Milani Fard, Maya Gupta |
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Poster
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Wed 8:00 |
Individual Calibration with Randomized Forecasting Shengjia Zhao, Tengyu Ma, Stefano Ermon |
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Poster
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Wed 8:00 |
Predictive Multiplicity in Classification Charles Marx, Flavio Calmon, Berk Ustun |
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Poster
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Wed 9:00 |
Balancing Competing Objectives with Noisy Data: Score-Based Classifiers for Welfare-Aware Machine Learning Esther Rolf, Max Simchowitz, Sarah Dean, Lydia T. Liu, Daniel Bjorkegren, Moritz Hardt, Joshua Blumenstock |
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Poster
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Wed 10:00 |
How to Solve Fair k-Center in Massive Data Models Ashish Chiplunkar, Sagar Kale, Sivaramakrishnan Natarajan Ramamoorthy |
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Poster
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Wed 11:00 |
DeBayes: a Bayesian Method for Debiasing Network Embeddings Maarten Buyl, Tijl De Bie |
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Poster
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Wed 12:00 |
Too Relaxed to Be Fair Michael Lohaus, Michaël Perrot, Ulrike von Luxburg |
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Poster
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Wed 13:00 |
Interpretations are Useful: Penalizing Explanations to Align Neural Networks with Prior Knowledge Laura Rieger, Chandan Singh, William Murdoch, Bin Yu |
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Poster
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Thu 6:00 |
A Pairwise Fair and Community-preserving Approach to k-Center Clustering Brian Brubach, Darshan Chakrabarti, John P Dickerson, Samir Khuller, Aravind Srinivasan, Leonidas Tsepenekas |
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Poster
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Thu 6:00 |
FR-Train: A Mutual Information-Based Approach to Fair and Robust Training Yuji Roh, Kangwook Lee, Steven Whang, Changho Suh |
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Poster
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Thu 6:00 |
FACT: A Diagnostic for Group Fairness Trade-offs Joon Kim, Jiahao Chen, Ameet Talwalkar |
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Poster
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Thu 7:00 |
Is There a Trade-Off Between Fairness and Accuracy? A Perspective Using Mismatched Hypothesis Testing Sanghamitra Dutta, Dennis Wei, Hazar Yueksel, Pin-Yu Chen, Sijia Liu, Kush Varshney |
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Poster
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Thu 8:00 |
Minimax Pareto Fairness: A Multi Objective Perspective Natalia Martinez Gil, Martin Bertran, Guillermo Sapiro |
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Poster
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Thu 8:00 |
Generalized and Scalable Optimal Sparse Decision Trees Jimmy Lin, Chudi Zhong, Diane Hu, Cynthia Rudin, Margo Seltzer |
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Poster
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Thu 9:00 |
Bounding the fairness and accuracy of classifiers from population statistics Sivan Sabato, Elad Yom-Tov |