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Poster
Thu 6:00 FR-Train: A Mutual Information-Based Approach to Fair and Robust Training
Yuji Roh · Kangwook Lee · Steven Whang · Changho Suh
Poster
Wed 9:00 Mix-n-Match : Ensemble and Compositional Methods for Uncertainty Calibration in Deep Learning
Jize Zhang · Bhavya Kailkhura · T. Yong-Jin Han
Poster
Tue 8:00 Detecting Out-of-Distribution Examples with Gram Matrices
Chandramouli Shama Sastry · Sageev Oore
Poster
Wed 9:00 SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates
Lingkai Kong · Jimeng Sun · Chao Zhang
Poster
Tue 8:00 Feature Noise Induces Loss Discrepancy Across Groups
Fereshte Khani · Percy Liang
Poster
Wed 16:00 On Lp-norm Robustness of Ensemble Decision Stumps and Trees
Yihan Wang · Huan Zhang · Hongge Chen · Duane Boning · Cho-Jui Hsieh
Poster
Wed 11:00 DeBayes: a Bayesian Method for Debiasing Network Embeddings
Maarten Buyl · Tijl De Bie
Poster
Thu 6:00 FACT: A Diagnostic for Group Fairness Trade-offs
Joon Kim · Jiahao Chen · Ameet Talwalkar
Workshop
Fri 6:30 Theoretical Foundations of Reinforcement Learning
Emma Brunskill · Thodoris Lykouris · Max Simchowitz · Wen Sun · Mengdi Wang
Poster
Tue 13:00 Confidence-Calibrated Adversarial Training: Generalizing to Unseen Attacks
David Stutz · Matthias Hein · Bernt Schiele
Poster
Wed 10:00 How to Solve Fair k-Center in Massive Data Models
Ashish Chiplunkar · Sagar Kale · Sivaramakrishnan Natarajan Ramamoorthy
Poster
Wed 5:00 Fair k-Centers via Maximum Matching
Matthew Jones · Huy Nguyen · Thy Nguyen