Pages that link to "Item:Q2392935"

The following pages link to Parallel stochastic gradient algorithms for large-scale matrix completion (Q2392935):

Displaying 39 items.

• Numerical comparisons between Bayesian and frequentist low-rank matrix completion: estimation accuracy and uncertainty quantification (Q123602) (← links)
• Analysis of multiview legislative networks with structured matrix factorization: does Twitter influence translate to the real world? (Q262369) (← links)
• Inexact coordinate descent: complexity and preconditioning (Q306308) (← links)
• Conditional gradient algorithms for norm-regularized smooth convex optimization (Q494314) (← links)
• 1-bit matrix completion: PAC-Bayesian analysis of a variational approximation (Q1640399) (← links)
• Linear feature transform and enhancement of classification on deep neural network (Q1785494) (← links)
• Optimization landscape of Tucker decomposition (Q2144548) (← links)
• Robust principal component analysis using facial reduction (Q2218887) (← links)
• Worst-case complexity of cyclic coordinate descent: \(O(n^2)\) gap with randomized version (Q2220668) (← links)
• Why random reshuffling beats stochastic gradient descent (Q2227529) (← links)
• Matrix recipes for hard thresholding methods (Q2251217) (← links)
• Recovery of simultaneous low rank and two-way sparse coefficient matrices, a nonconvex approach (Q2286374) (← links)
• A Riemannian gossip approach to subspace learning on Grassmann manifold (Q2320541) (← links)
• Enabling numerically exact local solver for waveform inversion -- a low-rank approach (Q2321974) (← links)
• A Bayesian approach for noisy matrix completion: optimal rate under general sampling distribution (Q2340879) (← links)
• Low-rank matrix completion via preconditioned optimization on the Grassmann manifold (Q2347362) (← links)
• Decentralized and privacy-preserving low-rank matrix completion (Q2516374) (← links)
• \textsc{OCam}: out-of-core coordinate descent algorithm for matrix completion (Q2660731) (← links)
• T-product factorization based method for matrix and tensor completion problems (Q2696924) (← links)
• LIBMF: a library for parallel matrix factorization in shared-memory systems (Q2810909) (← links)
• Block Stochastic Gradient Iteration for Convex and Nonconvex Optimization (Q2945126) (← links)
• Multilevel Stochastic Gradient Methods for Nested Composition Optimization (Q4629336) (← links)
• (Q4637013) (← links)
• Rank $2r$ Iterative Least Squares: Efficient Recovery of Ill-Conditioned Low Rank Matrices from Few Entries (Q4999366) (← links)
• Mixed-Projection Conic Optimization: A New Paradigm for Modeling Rank Constraints (Q5060505) (← links)
• On the Efficiency of Random Permutation for ADMM and Coordinate Descent (Q5108265) (← links)
• On the rates of convergence of parallelized averaged stochastic gradient algorithms (Q5110810) (← links)
• A Continuous-Time Analysis of Distributed Stochastic Gradient (Q5131162) (← links)
• (Q5149024) (← links)
• Convergence Rate of Incremental Gradient and Incremental Newton Methods (Q5237308) (← links)
• Orthogonal Rank-One Matrix Pursuit for Low Rank Matrix Completion (Q5251927) (← links)
• The Alternating Descent Conditional Gradient Method for Sparse Inverse Problems (Q5737722) (← links)
• Approximate matrix completion based on cavity method (Q5872687) (← links)
• Spectral gap in random bipartite biregular graphs and applications (Q5886318) (← links)
• A mini-batch proximal stochastic recursive gradient algorithm with diagonal Barzilai-Borwein stepsize (Q6097380) (← links)
• Block mirror stochastic gradient method for stochastic optimization (Q6158991) (← links)
• Random-reshuffled SARAH does not need full gradient computations (Q6204201) (← links)
• SPIRAL: a superlinearly convergent incremental proximal algorithm for nonconvex finite sum minimization (Q6498409) (← links)
• Matrix completion from a computational statistics perspective (Q6600376) (← links)