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Tue 14:00 Animal pose estimation from video data with a hierarchical von Mises-Fisher-Gaussian model
Libby Zhang · Tim Dunn · Jesse Marshall · Bence Olveczky · Scott Linderman
Tue 18:30 Learning Temporal Point Processes with Intermittent Observations
Vinayak Gupta · Srikanta Bedathur · Sourangshu Bhattacharya · Abir De
Tue 14:00 Revisiting Model-Agnostic Private Learning: Faster Rates and Active Learning
Chong Liu · Yuqing Zhu · Kamalika Chaudhuri · Yu-Xiang Wang
Thu 7:30 A Contraction Approach to Model-based Reinforcement Learning
Ting-Han Fan · Peter Ramadge
Wed 6:00 On the Importance of Hyperparameter Optimization for Model-based Reinforcement Learning
Baohe Zhang · Raghu Rajan · Luis Pineda · Nathan Lambert · AndrĂ© Biedenkapp · Kurtland Chua · Frank Hutter · Roberto Calandra
Tue 14:00 Learning-to-Rank with Partitioned Preference: Fast Estimation for the Plackett-Luce Model
Jiaqi Ma · Xinyang Yi · Weijing Tang · Zhe Zhao · Lichan Hong · Ed Chi · Qiaozhu Mei
Tue 18:30 Homeomorphic-Invariance of EM: Non-Asymptotic Convergence in KL Divergence for Exponential Families via Mirror Descent
Frederik Kunstner · Raunak Kumar · Mark Schmidt
Wed 12:45 Rate-Regularization and Generalization in Variational Autoencoders
Alican Bozkurt · Babak Esmaeili · Jean-Baptiste Tristan · Dana Brooks · Jennifer Dy · Jan-Willem van de Meent
Tue 18:30 Parametric Programming Approach for More Powerful and General Lasso Selective Inference
Vo Nguyen Le Duy · Ichiro Takeuchi
Wed 12:45 Fast and Smooth Interpolation on Wasserstein Space
Sinho Chewi · Julien Clancy · Thibaut Le Gouic · Philippe Rigollet · George Stepaniants · Austin Stromme
Wed 12:45 Provable Hierarchical Imitation Learning via EM
Zhiyu Zhang · Ioannis Paschalidis
Wed 6:00 Approximately Solving Mean Field Games via Entropy-Regularized Deep Reinforcement Learning
Kai Cui · Heinz Koeppl