non-convex optimization

Complex Dynamics in Simple Neural Networks: Understanding Gradient Flow in Phase Retrieval NeurIPS 2020 Complexity of Finding Stationary Points of Nonconvex Nonsmooth Functions ICML 2020 Continuous-time Lower Bounds for Gradient-based Algorithms ICML 2020 Convergence of a Stochastic Gradient Method with Momentum for Non-Smooth Non-Convex Optimization ICML 2020 Convergence Rates for the Stochastic Gradient Descent Method for Non-Convex Objective Functions JMLR 2020 Convergence Rates of a Momentum Algorithm with Bounded Adaptive Step Size for Nonconvex Optimization ACML 2020 Decentralized Deep Learning with Arbitrary Communication Compression ICLR 2020 Distributed Stochastic Gradient Descent with Event-Triggered Communication AAAI 2020 D-SPIDER-SFO: A Decentralized Optimization Algorithm with Faster Convergence Rate for Nonconvex Problems AAAI 2020 Efficient Clustering for Stretched Mixtures: Landscape and Optimality NeurIPS 2020 Escaping Saddle Points Faster with Stochastic Momentum ICLR 2020 Exact Guarantees on the Absence of Spurious Local Minima for Non-negative Rank-1 Robust Principal Component Analysis JMLR 2020 Explicit Gradient Learning for Black-Box Optimization ICML 2020 Fast Exact Matrix Completion: A Unified Optimization Framework for Matrix Completion JMLR 2020 Finding Second-Order Stationary Points Efficiently in Smooth Nonconvex Linearly Constrained Optimization Problems NeurIPS 2020 Generalization bound of globally optimal non-convex neural network training: Transportation map estimation by infinite dimensional Langevin dynamics NeurIPS 2020 Generalization Bound of Gradient Descent for Non-Convex Metric Learning NeurIPS 2020 Geometric Analysis of Nonconvex Optimization Landscapes for Overcomplete Learning ICLR 2020 Global Optimality for Point Set Registration Using Semidefinite Programming CVPR 2020 Guided Learning of Nonconvex Models through Successive Functional Gradient Optimization ICML 2020 High-dimensional Robust Mean Estimation via Gradient Descent ICML 2020 History-Gradient Aided Batch Size Adaptation for Variance Reduced Algorithms ICML 2020 How many samples is a good initial point worth in Low-rank Matrix Recovery? NeurIPS 2020 Hybrid Variance-Reduced SGD Algorithms For Minimax Problems with Nonconvex-Linear Function NeurIPS 2020 Improved Analysis of Clipping Algorithms for Non-convex Optimization NeurIPS 2020