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Poster
Tue 7:00 Distance Metric Learning with Joint Representation Diversification
Xu Chu · Yang Lin · Yasha Wang · Xiting Wang · Hailong Yu · Xin Gao · Qi Tong
Poster
Tue 7:00 Deep Divergence Learning
Kubra Cilingir · Rachel Manzelli · Brian Kulis
Poster
Tue 7:00 Scalable Nearest Neighbor Search for Optimal Transport
Arturs Backurs · Yihe Dong · Piotr Indyk · Ilya Razenshteyn · Tal Wagner
Poster
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
Poster
Tue 9:00 Two Simple Ways to Learn Individual Fairness Metrics from Data
Debarghya Mukherjee · Mikhail Yurochkin · Moulinath Banerjee · Yuekai Sun
Poster
Tue 11:00 Optimization and Analysis of the pAp@k Metric for Recommender Systems
Gaurush Hiranandani · Warut Vijitbenjaronk · Sanmi Koyejo · Prateek Jain
Poster
Tue 11:00 A Swiss Army Knife for Minimax Optimal Transport
Sofien Dhouib · Ievgen Redko · Tanguy Kerdoncuff · RĂ©mi Emonet · Marc Sebban
Poster
Tue 11:00 Online metric algorithms with untrusted predictions
Antonios Antoniadis · Christian Coester · Marek Elias · Adam Polak · Bertrand Simon
Poster
Tue 13:00 Graph Random Neural Features for Distance-Preserving Graph Representations
Daniele Zambon · Cesare Alippi · Lorenzo Livi
Poster
Tue 14:00 Learning Similarity Metrics for Numerical Simulations
Georg Kohl · Kiwon Um · Nils Thuerey
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 Optimal Bounds between f-Divergences and Integral Probability Metrics
Rohit Agrawal · Thibaut Horel