Papers
Efficient Dictionary Learning with Gradient Descent
Dar Gilboa, Sam Buchanan, John Wright
Efficient Full-Matrix Adaptive Regularization
Naman Agarwal, Brian Bullins, Xinyi Chen et al.
Efficient learning of smooth probability functions from Bernoulli tests with guarantees
Paul Rolland, Ali Kavis, Alexander Immer et al.
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
Mingxing Tan, Quoc Le
Efficient Nonconvex Regularized Tensor Completion with Structure-aware Proximal Iterations
Quanming Yao, James Tin-Yau Kwok, Bo Han
Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables
Kate Rakelly, Aurick Zhou, Chelsea Finn et al.
Efficient optimization of loops and limits with randomized telescoping sums
Alex Beatson, Ryan P Adams
Efficient Training of BERT by Progressively Stacking
Linyuan Gong, Di He, Zhuohan Li et al.
EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis
Chaoqi Wang, Roger Grosse, Sanja Fidler et al.
ELF OpenGo: an analysis and open reimplementation of AlphaZero
Yuandong Tian, Jerry Ma, Qucheng Gong et al.
Emerging Convolutions for Generative Normalizing Flows
Emiel Hoogeboom, Rianne Van Den Berg, Max Welling
EMI: Exploration with Mutual Information
Hyoungseok Kim, Jaekyeom Kim, Yeonwoo Jeong et al.
Empirical Analysis of Beam Search Performance Degradation in Neural Sequence Models
Eldan Cohen, Christopher Beck
End-to-End Probabilistic Inference for Nonstationary Audio Analysis
William Wilkinson, Michael Andersen, Joshua D. Reiss et al.
Entropic GANs meet VAEs: A Statistical Approach to Compute Sample Likelihoods in GANs
Yogesh Balaji, Hamed Hassani, Rama Chellappa et al.
Equivariant Transformer Networks
Kai Sheng Tai, Peter Bailis, Gregory Valiant
Error Feedback Fixes SignSGD and other Gradient Compression Schemes
Sai Praneeth Karimireddy, Quentin Rebjock, Sebastian Stich et al.
Escaping Saddle Points with Adaptive Gradient Methods
Matthew Staib, Sashank Reddi, Satyen Kale et al.
Estimate Sequences for Variance-Reduced Stochastic Composite Optimization
Andrei Kulunchakov, Julien Mairal
Estimating Information Flow in Deep Neural Networks
Ziv Goldfeld, Ewout Van Den Berg, Kristjan Greenewald et al.
Explaining Deep Neural Networks with a Polynomial Time Algorithm for Shapley Value Approximation
Marco Ancona, Cengiz Oztireli, Markus Gross
Exploiting structure of uncertainty for efficient matroid semi-bandits
Pierre Perrault, Vianney Perchet, Michal Valko
Exploiting Worker Correlation for Label Aggregation in Crowdsourcing
Yuan Li, Benjamin Rubinstein, Trevor Cohn
Exploration Conscious Reinforcement Learning Revisited
Lior Shani, Yonathan Efroni, Shie Mannor