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non-convex optimization

546 papers

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IRLS

Co-occurring keywords

stochastic gradient descent (1088) stochastic optimization (1060) gradient descent (1143) convergence rate (606) convergence analysis (394) variance reduction (520) nonconvex optimization (316) saddle point (95) matrix factorization (529) online learning (1770)

Papers

Adaptive Negative Curvature Descent with Applications in Non-convex Optimization NIPS 2018
Non-Convex Matrix Completion Against a Semi-Random Adversary COLT 2018
Cutting plane methods can be extended into nonconvex optimization COLT 2018
Fast and Sample Efficient Inductive Matrix Completion via Multi-Phase Procrustes Flow ICML 2018
The Convergence of Sparsified Gradient Methods NIPS 2018
How To Make the Gradients Small Stochastically: Even Faster Convex and Nonconvex SGD NIPS 2018
Approximate message passing for amplitude based optimization ICML 2018
Convergence guarantees for a class of non-convex and non-smooth optimization problems ICML 2018
Escaping Saddles with Stochastic Gradients ICML 2018
Gradient Primal-Dual Algorithm Converges to Second-Order Stationary Solution for Nonconvex Distributed Optimization Over Networks ICML 2018
Katyusha X: Simple Momentum Method for Stochastic Sum-of-Nonconvex Optimization ICML 2018
signSGD: Compressed Optimisation for Non-Convex Problems ICML 2018
A Fast Algorithm for Separated Sparsity via Perturbed Lagrangians AISTATS 2018
Generalization Bounds of SGLD for Non-convex Learning: Two Theoretical Viewpoints COLT 2018
An Analysis of the t-SNE Algorithm for Data Visualization COLT 2018
Accelerated Gradient Descent Escapes Saddle Points Faster than Gradient Descent COLT 2018
Global Guarantees for Enforcing Deep Generative Priors by Empirical Risk COLT 2018
Local Optimality and Generalization Guarantees for the Langevin Algorithm via Empirical Metastability COLT 2018
Towards a Mathematical Understanding of the Difficulty in Learning With Feedforward Neural Networks CVPR 2018
Data-Dependent Stability of Stochastic Gradient Descent ICML 2018
Towards Provable Learning of Polynomial Neural Networks Using Low-Rank Matrix Estimation AISTATS 2018
Gradient Descent Learns Linear Dynamical Systems JMLR 2018
SADAGRAD: Strongly Adaptive Stochastic Gradient Methods ICML 2018
Dual Principal Component Pursuit: Improved Analysis and Efficient Algorithms NIPS 2018
Structured Local Minima in Sparse Blind Deconvolution NIPS 2018