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Spotlight
Tue 7:30 Learning Intra-Batch Connections for Deep Metric Learning
Jenny Seidenschwarz · Ismail Elezi · Laura Leal-Taixé
Spotlight
Tue 7:35 Simultaneous Similarity-based Self-Distillation for Deep Metric Learning
Karsten Roth · Timo Milbich · Bjorn Ommer · Joseph Paul Cohen · Marzyeh Ghassemi
Poster
Tue 9:00 MC-LSTM: Mass-Conserving LSTM
Pieter-Jan Hoedt · Frederik Kratzert · Daniel Klotz · Christina Halmich · Markus Holzleitner · Grey Nearing · Sepp Hochreiter · Günter Klambauer
Poster
Tue 9:00 Simultaneous Similarity-based Self-Distillation for Deep Metric Learning
Karsten Roth · Timo Milbich · Bjorn Ommer · Joseph Paul Cohen · Marzyeh Ghassemi
Poster
Tue 9:00 Learning Intra-Batch Connections for Deep Metric Learning
Jenny Seidenschwarz · Ismail Elezi · Laura Leal-Taixé
Spotlight
Tue 18:30 GMAC: A Distributional Perspective on Actor-Critic Framework
Daniel Nam · Younghoon Kim · Chan Youn Park
Poster
Tue 21:00 GMAC: A Distributional Perspective on Actor-Critic Framework
Daniel Nam · Younghoon Kim · Chan Youn Park
Spotlight
Wed 7:35 The Power of Log-Sum-Exp: Sequential Density Ratio Matrix Estimation for Speed-Accuracy Optimization
Taiki Miyagawa · Akinori Ebihara
Poster
Wed 9:00 The Power of Log-Sum-Exp: Sequential Density Ratio Matrix Estimation for Speed-Accuracy Optimization
Taiki Miyagawa · Akinori Ebihara
Spotlight
Wed 17:30 Optimizing Black-box Metrics with Iterative Example Weighting
Gaurush Hiranandani · Jatin Mathur · Harikrishna Narasimhan · Mahdi Milani Fard · Sanmi Koyejo
Spotlight
Wed 19:25 MC-LSTM: Mass-Conserving LSTM
Pieter-Jan Hoedt · Frederik Kratzert · Daniel Klotz · Christina Halmich · Markus Holzleitner · Grey Nearing · Sepp Hochreiter · Günter Klambauer
Poster
Wed 21:00 Optimizing Black-box Metrics with Iterative Example Weighting
Gaurush Hiranandani · Jatin Mathur · Harikrishna Narasimhan · Mahdi Milani Fard · Sanmi Koyejo