Optimization

An Effective Optimization Method for Neural Machine Translation: The Case of English-Persian Bilingually Low-Resource Scenario AACL 2020 An Efficient Explorative Sampling Considering the Generative Boundaries of Deep Generative Neural Networks AAAI 2020 An efficient nonconvex reformulation of stagewise convex optimization problems NeurIPS 2020 An Empirical Investigation of Beam-Aware Training in Supertagging EMNLP 2020 An Empirical Study of Stochastic Gradient Descent with Structured Covariance Noise AISTATS 2020 An implicit function learning approach for parametric modal regression NeurIPS 2020 An Investigation Into the Stochasticity of Batch Whitening CVPR 2020 Ansor: Generating High-Performance Tensor Programs for Deep Learning OSDI 2020 A Tensor Compiler for Unified Machine Learning Prediction Serving OSDI 2020 AutoCompress: An Automatic DNN Structured Pruning Framework for Ultra-High Compression Rates AAAI 2020 AutoML-Zero: Evolving Machine Learning Algorithms From Scratch ICML 2020 Auto-Tuning Structured Light by Optical Stochastic Gradient Descent CVPR 2020 BaKer-Nets: Bayesian Random Kernel Mapping Networks IJCAI 2020 Benchmarking Deep Inverse Models over time, and the Neural-Adjoint method NeurIPS 2020 Bi-level Probabilistic Feature Learning for Deformable Image Registration IJCAI 2020 Block-Wisely Supervised Neural Architecture Search With Knowledge Distillation CVPR 2020 Bounding the expected run-time of nonconvex optimization with early stopping UAI 2020 Branch and Bound for Piecewise Linear Neural Network Verification JMLR 2020 Bundle Adjustment on a Graph Processor CVPR 2020 Can gradient clipping mitigate label noise? ICLR 2020 Communication-Efficient Distributed Stochastic AUC Maximization with Deep Neural Networks ICML 2020 Complexity of Finding Stationary Points of Nonconvex Nonsmooth Functions ICML 2020 Conic Descent and its Application to Memory-efficient Optimization over Positive Semidefinite Matrices NeurIPS 2020 Continual Learning With Extended Kronecker-Factored Approximate Curvature CVPR 2020 Convergence Rates for the Stochastic Gradient Descent Method for Non-Convex Objective Functions JMLR 2020