Papers
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.
Estimation of Markov Chain via Rank-Constrained Likelihood
Xudong Li, Mengdi Wang, Anru Zhang
Explicit Inductive Bias for Transfer Learning with Convolutional Networks
Xuhong LI, Yves Grandvalet, Franck Davoine
Exploiting the Potential of Standard Convolutional Autoencoders for Image Restoration by Evolutionary Search
Masanori Suganuma, Mete Ozay, Takayuki Okatani
Exploring Hidden Dimensions in Accelerating Convolutional Neural Networks
Zhihao Jia, Sina Lin, Charles R. Qi et al.
Extracting Automata from Recurrent Neural Networks Using Queries and Counterexamples
Gail Weiss, Yoav Goldberg, Eran Yahav
Extreme Learning to Rank via Low Rank Assumption
Minhao Cheng, Ian Davidson, Cho-Jui Hsieh
Fair and Diverse DPP-Based Data Summarization
Elisa Celis, Vijay Keswani, Damian Straszak et al.
Fairness Without Demographics in Repeated Loss Minimization
Tatsunori Hashimoto, Megha Srivastava, Hongseok Namkoong et al.
Fast and Sample Efficient Inductive Matrix Completion via Multi-Phase Procrustes Flow
Xiao Zhang, Simon Du, Quanquan Gu
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam
Mohammad Khan, Didrik Nielsen, Voot Tangkaratt et al.
Fast Approximate Spectral Clustering for Dynamic Networks
Lionel Martin, Andreas Loukas, Pierre Vandergheynst
Fast Bellman Updates for Robust MDPs
Chin Pang Ho, Marek Petrik, Wolfram Wiesemann
Fast Decoding in Sequence Models Using Discrete Latent Variables
Lukasz Kaiser, Samy Bengio, Aurko Roy et al.
Faster Derivative-Free Stochastic Algorithm for Shared Memory Machines
Bin Gu, Zhouyuan Huo, Cheng Deng et al.
Fast Gradient-Based Methods with Exponential Rate: A Hybrid Control Framework
Arman Sharifi Kolarijani, Peyman Mohajerin Esfahani, Tamas Keviczky