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Linear Algebra

480 papers

Papers per year

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36
44
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Papers

Robust Spectral Detection of Global Structures in the Data by Learning a Regularization NIPS 2016
Low-Rank Regression with Tensor Responses NIPS 2016
A posteriori error bounds for joint matrix decomposition problems NIPS 2016
Clustering Signed Networks with the Geometric Mean of Laplacians NIPS 2016
Structured Matrix Recovery via the Generalized Dantzig Selector NIPS 2016
Fast recovery from a union of subspaces NIPS 2016
Coordinate-wise Power Method NIPS 2016
Learning HMMs with Nonparametric Emissions via Spectral Decompositions of Continuous Matrices NIPS 2016
Global Optimality of Local Search for Low Rank Matrix Recovery NIPS 2016
Fast Algorithms for Robust PCA via Gradient Descent NIPS 2016
Normalized Spectral Map Synchronization NIPS 2016
LazySVD: Even Faster SVD Decomposition Yet Without Agonizing Pain NIPS 2016
Correlated-PCA: Principal Components' Analysis when Data and Noise are Correlated NIPS 2016
Tensor vs. Matrix Methods: Robust Tensor Decomposition under Block Sparse Perturbations AISTATS 2016
Low-Rank Approximation of Weighted Tree Automata AISTATS 2016
Non-Gaussian Component Analysis with Log-Density Gradient Estimation AISTATS 2016
Multiresolution Matrix Compression AISTATS 2016
An Improved Gap-Dependency Analysis of the Noisy Power Method COLT 2016
Linear Shape Deformation Models With Local Support Using Graph-Based Structured Matrix Factorisation CVPR 2016
Fast Stochastic Algorithms for SVD and PCA: Convergence Properties and Convexity ICML 2016
Convergence of Stochastic Gradient Descent for PCA ICML 2016
Learning from Multiway Data: Simple and Efficient Tensor Regression ICML 2016
Low-rank Solutions of Linear Matrix Equations via Procrustes Flow ICML 2016
Quadratic Optimization with Orthogonality Constraints: Explicit Lojasiewicz Exponent and Linear Convergence of Line-Search Methods ICML 2016
A Subspace Learning Approach for High Dimensional Matrix Decomposition with Efficient Column/Row Sampling ICML 2016