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Methodology
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non-convex optimization
546 papers
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Also known as
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
Basis Learning as an Algorithmic Primitive
COLT 2016
Fast Algorithms for Robust PCA via Gradient Descent
NIPS 2016
Global Optimality of Local Search for Low Rank Matrix Recovery
NIPS 2016
The non-convex Burer-Monteiro approach works on smooth semidefinite programs
NIPS 2016
Provable Efficient Online Matrix Completion via Non-convex Stochastic Gradient Descent
NIPS 2016
Solving Random Systems of Quadratic Equations via Truncated Generalized Gradient Flow
NIPS 2016
Learning Supervised PageRank with Gradient-Based and Gradient-Free Optimization Methods
NIPS 2016
Deep Learning without Poor Local Minima
NIPS 2016
A Non-convex One-Pass Framework for Generalized Factorization Machine and Rank-One Matrix Sensing
NIPS 2016
Matrix Completion has No Spurious Local Minimum
NIPS 2016
A Pseudo-Bayesian Algorithm for Robust PCA
NIPS 2016
Stochastic Structured Prediction under Bandit Feedback
NIPS 2016
On Graduated Optimization for Stochastic Non-Convex Problems
ICML 2016
Train faster, generalize better: Stability of stochastic gradient descent
ICML 2016
Improved SVRG for Non-Strongly-Convex or Sum-of-Non-Convex Objectives
ICML 2016
SDCA without Duality, Regularization, and Individual Convexity
ICML 2016
Variance Reduction for Faster Non-Convex Optimization
ICML 2016
Low-rank Solutions of Linear Matrix Equations via Procrustes Flow
ICML 2016
Convergence of Stochastic Gradient Descent for PCA
ICML 2016
Training Neural Networks Without Gradients: A Scalable ADMM Approach
ICML 2016
On the Quality of the Initial Basin in Overspecified Neural Networks
ICML 2016
Alternating Minimization for Regression Problems with Vector-valued Outputs
NIPS 2015
Solving Random Quadratic Systems of Equations Is Nearly as Easy as Solving Linear Systems
NIPS 2015
Equilibrated adaptive learning rates for non-convex optimization
NIPS 2015
Simple, Efficient, and Neural Algorithms for Sparse Coding
COLT 2015
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