Papers
Does Distributionally Robust Supervised Learning Give Robust Classifiers?
Weihua Hu, Gang Niu, Issei Sato et al.
Do Outliers Ruin Collaboration?
Mingda Qiao
DRACO: Byzantine-resilient Distributed Training via Redundant Gradients
Lingjiao Chen, Hongyi Wang, Zachary Charles et al.
Dropout Training, Data-dependent Regularization, and Generalization Bounds
Wenlong Mou, Yuchen Zhou, Jun Gao et al.
DVAE++: Discrete Variational Autoencoders with Overlapping Transformations
Arash Vahdat, William Macready, Zhengbing Bian et al.
Dynamical Isometry and a Mean Field Theory of CNNs: How to Train 10,000-Layer Vanilla Convolutional Neural Networks
Lechao Xiao, Yasaman Bahri, Jascha Sohl-Dickstein et al.
Dynamical Isometry and a Mean Field Theory of RNNs: Gating Enables Signal Propagation in Recurrent Neural Networks
Minmin Chen, Jeffrey Pennington, Samuel Schoenholz
Dynamic Evaluation of Neural Sequence Models
Ben Krause, Emmanuel Kahembwe, Iain Murray et al.
Dynamic Regret of Strongly Adaptive Methods
Lijun Zhang, Tianbao Yang, jin et al.
Efficient and Consistent Adversarial Bipartite Matching
Rizal Fathony, Sima Behpour, Xinhua Zhang et al.
Efficient Bias-Span-Constrained Exploration-Exploitation in Reinforcement Learning
Ronan Fruit, Matteo Pirotta, Alessandro Lazaric et al.
Efficient end-to-end learning for quantizable representations
Yeonwoo Jeong, Hyun Oh Song
Efficient First-Order Algorithms for Adaptive Signal Denoising
Dmitrii Ostrovskii, Zaid Harchaoui
Efficient Gradient-Free Variational Inference using Policy Search
Oleg Arenz, Gerhard Neumann, Mingjun Zhong
Efficient Model-Based Deep Reinforcement Learning with Variational State Tabulation
Dane Corneil, Wulfram Gerstner, Johanni Brea
Efficient Neural Architecture Search via Parameters Sharing
Hieu Pham, Melody Guan, Barret Zoph et al.
Efficient Neural Audio Synthesis
Nal Kalchbrenner, Erich Elsen, Karen Simonyan et al.
End-to-end Active Object Tracking via Reinforcement Learning
Wenhan Luo, Peng Sun, Fangwei Zhong et al.
End-to-End Learning for the Deep Multivariate Probit Model
Di Chen, Yexiang Xue, Carla Gomes
Entropy-SGD optimizes the prior of a PAC-Bayes bound: Generalization properties of Entropy-SGD and data-dependent priors
Gintare Karolina Dziugaite, Daniel Roy
Error Compensated Quantized SGD and its Applications to Large-scale Distributed Optimization
Jiaxiang Wu, Weidong Huang, Junzhou Huang et al.
Error Estimation for Randomized Least-Squares Algorithms via the Bootstrap
Miles Lopes, Shusen Wang, Michael Mahoney
Escaping Saddles with Stochastic Gradients
Hadi Daneshmand, Jonas Kohler, Aurelien Lucchi et al.
Essentially No Barriers in Neural Network Energy Landscape
Felix Draxler, Kambis Veschgini, Manfred Salmhofer et al.