Optimization

On the Local Minima of the Empirical Risk NeurIPS 2018 On the Relative Expressiveness of Bayesian and Neural Networks PGM 2018 Optimization Algorithm Inspired Deep Neural Network Structure Design ACML 2018 Pipe-SGD: A Decentralized Pipelined SGD Framework for Distributed Deep Net Training NeurIPS 2018 Provably Correct Automatic Sub-Differentiation for Qualified Programs NeurIPS 2018 Quantum Divide-and-Conquer Anchoring for Separable Non-negative Matrix Factorization IJCAI 2018 Robust Facial Landmark Detection via a Fully-Convolutional Local-Global Context Network CVPR 2018 RSG: Beating Subgradient Method without Smoothness and Strong Convexity JMLR 2018 Scalable Dense Non-Rigid Structure-From-Motion: A Grassmannian Perspective CVPR 2018 SecureNets: Secure Inference of Deep Neural Networks on an Untrusted Cloud ACML 2018 SGD and Hogwild! Convergence Without the Bounded Gradients Assumption ICML 2018 Single-Channel Dereverberation Using Direct MMSE Optimization and Bidirectional LSTM Networks Interspeech 2018 Spotlight: Optimizing Device Placement for Training Deep Neural Networks ICML 2018 Statistical Optimality of Stochastic Gradient Descent on Hard Learning Problems through Multiple Passes NeurIPS 2018 Step Size Matters in Deep Learning NeurIPS 2018 Stochastic Cubic Regularization for Fast Nonconvex Optimization NeurIPS 2018 The Convergence of Sparsified Gradient Methods NeurIPS 2018 The Effect of Network Width on the Performance of Large-batch Training NeurIPS 2018 The Implicit Bias of Gradient Descent on Separable Data ICLR 2018 The Implicit Bias of Gradient Descent on Separable Data JMLR 2018 The Price of Privacy for Low-rank Factorization NeurIPS 2018 Toward Designing Convergent Deep Operator Splitting Methods for Task-specific Nonconvex Optimization IJCAI 2018 Towards Dynamic Computation Graphs via Sparse Latent Structure EMNLP 2018 Towards Fast Computation of Certified Robustness for ReLU Networks ICML 2018 Training Deep Models Faster with Robust, Approximate Importance Sampling NeurIPS 2018