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71 Results
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Poster
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Thu 17:00 |
Randomized Automatic Differentiation Deniz Oktay · Nick McGreivy · Joshua Aduol · Alex Beatson · Ryan P Adams |
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Poster
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Mon 1:00 |
Overfitting for Fun and Profit: Instance-Adaptive Data Compression Ties van Rozendaal · Iris Huijben · Taco Cohen |
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Poster
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Mon 9:00 |
Adaptive Federated Optimization Sashank Reddi · Zachary Charles · Manzil Zaheer · Zachary Garrett · Keith Rush · Jakub Konečný · Sanjiv Kumar · H. Brendan McMahan |
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Oral
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Tue 12:00 |
Randomized Automatic Differentiation Deniz Oktay · Nick McGreivy · Joshua Aduol · Alex Beatson · Ryan P Adams |
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Poster
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Wed 9:00 |
Optimism in Reinforcement Learning with Generalized Linear Function Approximation Yining Wang · Ruosong Wang · Simon Du · Akshay Krishnamurthy |
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Poster
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Thu 1:00 |
A Diffusion Theory For Deep Learning Dynamics: Stochastic Gradient Descent Exponentially Favors Flat Minima Zeke Xie · Issei Sato · Masashi Sugiyama |
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Poster
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Wed 17:00 |
PolarNet: Learning to Optimize Polar Keypoints for Keypoint Based Object Detection wu xiongwei · Doyen Sahoo · Steven HOI |
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Poster
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Mon 17:00 |
Partitioned Learned Bloom Filters Kapil Vaidya · Eric Knorr · Michael Mitzenmacher · Tim Kraska |
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Poster
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Tue 17:00 |
Usable Information and Evolution of Optimal Representations During Training Michael Kleinman · Alessandro Achille · Daksh Idnani · Jonathan Kao |
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Poster
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Mon 17:00 |
Regularization Matters in Policy Optimization - An Empirical Study on Continuous Control Zhuang Liu · Xuanlin Li · Bingyi Kang · trevor darrell |
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Oral
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Tue 4:23 |
Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes Mike Gartrell · Insu Han · Elvis Dohmatob · Jennifer Gillenwater · Victor-Emmanuel Brunel |
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Poster
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Tue 17:00 |
The Importance of Pessimism in Fixed-Dataset Policy Optimization Jacob Buckman · Carles Gelada · Marc G Bellemare |