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Poster
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Tue 7:00 |
Distance Metric Learning with Joint Representation Diversification Xu Chu · Yang Lin · Yasha Wang · Xiting Wang · Hailong Yu · Xin Gao · Qi Tong |
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Poster
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Tue 7:00 |
Deep Divergence Learning Kubra Cilingir · Rachel Manzelli · Brian Kulis |
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Poster
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Tue 7:00 |
Scalable Nearest Neighbor Search for Optimal Transport Arturs Backurs · Yihe Dong · Piotr Indyk · Ilya Razenshteyn · Tal Wagner |
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Poster
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Tue 8:00 |
An end-to-end approach for the verification problem: learning the right distance Joao Monteiro · Isabela Albuquerque · Jahangir Alam · R Devon Hjelm · Tiago Falk |
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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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Tue 11:00 |
Optimization and Analysis of the pAp@k Metric for Recommender Systems Gaurush Hiranandani · Warut Vijitbenjaronk · Sanmi Koyejo · Prateek Jain |
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Poster
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Tue 11:00 |
A Swiss Army Knife for Minimax Optimal Transport Sofien Dhouib · Ievgen Redko · Tanguy Kerdoncuff · Rémi Emonet · Marc Sebban |
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Poster
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Tue 11:00 |
Online metric algorithms with untrusted predictions Antonios Antoniadis · Christian Coester · Marek Elias · Adam Polak · Bertrand Simon |
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Poster
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Tue 13:00 |
Graph Random Neural Features for Distance-Preserving Graph Representations Daniele Zambon · Cesare Alippi · Lorenzo Livi |
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Poster
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Tue 14:00 |
Learning Similarity Metrics for Numerical Simulations Georg Kohl · Kiwon Um · Nils Thuerey |
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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 |
Optimal Bounds between f-Divergences and Integral Probability Metrics Rohit Agrawal · Thibaut Horel |