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Spotlight
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Tue 18:30
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Towards Deployment-Efficient Reinforcement Learning: Lower Bound and Optimality
Jiawei Huang · Jinglin Chen · Li Zhao · Tao Qin · Nan Jiang · Tie-Yan Liu
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Spotlight
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Thu 18:30
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Analyzing and Improving the Optimization Landscape of Noise-Contrastive Estimation
Bingbin Liu · Elan Rosenfeld · Pradeep K Ravikumar · Andrej Risteski
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Poster
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Tue 10:30
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A Reduction-Based Framework for Conservative Bandits and Reinforcement Learning
Yunchang Yang · Tianhao Wu · Han Zhong · Evrard Garcelon · Matteo Pirotta · Alessandro Lazaric · Liwei Wang · Simon Du
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Poster
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Thu 18:30
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Analyzing and Improving the Optimization Landscape of Noise-Contrastive Estimation
Bingbin Liu · Elan Rosenfeld · Pradeep K Ravikumar · Andrej Risteski
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Poster
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Wed 10:30
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Sequence Approximation using Feedforward Spiking Neural Network for Spatiotemporal Learning: Theory and Optimization Methods
Xueyuan She · Saurabh Dash · Saibal Mukhopadhyay
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Poster
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Tue 18:30
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Towards Deployment-Efficient Reinforcement Learning: Lower Bound and Optimality
Jiawei Huang · Jinglin Chen · Li Zhao · Tao Qin · Nan Jiang · Tie-Yan Liu
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Workshop
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Fri 5:45
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GroundedML: Anchoring Machine Learning in Classical Algorithmic Theory
Perouz Taslakian · Pierre-André Noël · David Vazquez · Jian Tang · Xavier Bresson
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Poster
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Wed 10:30
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Pessimistic Model-based Offline Reinforcement Learning under Partial Coverage
Masatoshi Uehara · Wen Sun
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Poster
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Thu 10:30
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Optimization and Adaptive Generalization of Three layer Neural Networks
Khashayar Gatmiry · Stefanie Jegelka · Jonathan Kelner
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Poster
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Tue 18:30
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When Can We Learn General-Sum Markov Games with a Large Number of Players Sample-Efficiently?
Ziang Song · Song Mei · Yu Bai
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Poster
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Tue 10:30
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A global convergence theory for deep ReLU implicit networks via over-parameterization
Tianxiang Gao · Hailiang Liu · Jia Liu · Hridesh Rajan · Hongyang Gao
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Poster
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Mon 10:30
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Near-optimal Offline Reinforcement Learning with Linear Representation: Leveraging Variance Information with Pessimism
Ming Yin · Yaqi Duan · Mengdi Wang · Yu-Xiang Wang
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