Papers
Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning
Sebastian Curi, Felix Berkenkamp, Andreas Krause
Efficient Nonmyopic Bayesian Optimization via One-Shot Multi-Step Trees
Shali Jiang, Daniel Jiang, Maximilian Balandat et al.
Efficient Online Learning of Optimal Rankings: Dimensionality Reduction via Gradient Descent
Dimitris Fotakis, Thanasis Lianeas, Georgios Piliouras et al.
Efficient Planning in Large MDPs with Weak Linear Function Approximation
Roshan Shariff, Csaba Szepesvari
Efficient Projection-free Algorithms for Saddle Point Problems
Cheng Chen, Luo Luo, Weinan Zhang et al.
Efficient semidefinite-programming-based inference for binary and multi-class MRFs
Chirag Pabbaraju, Po-Wei Wang, J. Zico Kolter
Efficient Variational Inference for Sparse Deep Learning with Theoretical Guarantee
Jincheng Bai, Qifan Song, Guang Cheng
Elastic-InfoGAN: Unsupervised Disentangled Representation Learning in Class-Imbalanced Data
Utkarsh Ojha, Krishna Kumar Singh, Cho-Jui Hsieh et al.
Election Coding for Distributed Learning: Protecting SignSGD against Byzantine Attacks
Jy-yong Sohn, Dong-Jun Han, Beongjun Choi et al.
Emergent Complexity and Zero-shot Transfer via Unsupervised Environment Design
Michael Dennis, Natasha Jaques, Eugene Vinitsky et al.
Empirical Likelihood for Contextual Bandits
Nikos Karampatziakis, John Langford, Paul Mineiro
Enabling certification of verification-agnostic networks via memory-efficient semidefinite programming
Sumanth Dathathri, Krishnamurthy Dvijotham, Alexey Kurakin et al.
End-to-End Learning and Intervention in Games
Jiayang Li, Jing Yu, Yu Nie et al.
Energy-based Out-of-distribution Detection
Weitang Liu, Xiaoyun Wang, John Owens et al.
Ensemble Distillation for Robust Model Fusion in Federated Learning
Tao Lin, Lingjing Kong, Sebastian U Stich et al.
Ensembling geophysical models with Bayesian Neural Networks
Ushnish Sengupta, Matt Amos, Scott Hosking et al.
Ensuring Fairness Beyond the Training Data
Debmalya Mandal, Samuel Deng, Suman Jana et al.
Entropic Causal Inference: Identifiability and Finite Sample Results
Spencer Compton, Murat Kocaoglu, Kristjan Greenewald et al.
Entropic Optimal Transport between Unbalanced Gaussian Measures has a Closed Form
Hicham Janati, Boris Muzellec, Gabriel Peyré et al.
Entrywise convergence of iterative methods for eigenproblems
Vasileios Charisopoulos, Austin R Benson, Anil Damle
Equivariant Networks for Hierarchical Structures
Renhao Wang, Marjan Albooyeh, Siamak Ravanbakhsh
Erdos Goes Neural: an Unsupervised Learning Framework for Combinatorial Optimization on Graphs
Nikolaos Karalias, Andreas Loukas
Error Bounds of Imitating Policies and Environments
Tian Xu, Ziniu Li, Yang Yu
Escaping Saddle-Point Faster under Interpolation-like Conditions
Abhishek Roy, Krishnakumar Balasubramanian, Saeed Ghadimi et al.