conftrace_

low-rank approximation

323 papers

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Also known as

LORA

Co-occurring keywords

model compression (3302) matrix factorization (529) matrix completion (356) tensor decomposition (375) singular value decomposition (222) matrix approximation (89) dimensionality reduction (720) tensor completion (64) kernel methods (1097) convex optimization (1321)

Papers

Differentially Private Robust Low-Rank Approximation NIPS 2018
Low-Rank Tucker Decomposition of Large Tensors Using TensorSketch NIPS 2018
Efficient Convex Completion of Coupled Tensors using Coupled Nuclear Norms NIPS 2018
A Dual Framework for Low-rank Tensor Completion NIPS 2018
The Price of Fair PCA: One Extra dimension NIPS 2018
Deep Non-Blind Deconvolution via Generalized Low-Rank Approximation NIPS 2018
Ridge Regression and Provable Deterministic Ridge Leverage Score Sampling NIPS 2018
Subspace Embedding and Linear Regression with Orlicz Norm ICML 2018
Fast Recursive Low-rank Tensor Learning for Regression IJCAI 2017
Mixture-Rank Matrix Approximation for Collaborative Filtering NIPS 2017
Fitting Low-Rank Tensors in Constant Time NIPS 2017
Adaptive Randomized Dimension Reduction on Massive Data JMLR 2017
Algorithms for $\ell_p$ Low-Rank Approximation ICML 2017
Nyström Method with Kernel K-means++ Samples as Landmarks ICML 2017
Online Robust Low-Rank Tensor Learning IJCAI 2017
Tensor Completion with Side Information: A Riemannian Manifold Approach IJCAI 2017
Compact Matrix Factorization With Dependent Subspaces CVPR 2017
Storage Fit Learning with Unlabeled Data IJCAI 2017
Category-aware Next Point-of-Interest Recommendation via Listwise Bayesian Personalized Ranking IJCAI 2017
Tensor Biclustering NIPS 2017
Hierarchically Compositional Kernels for Scalable Nonparametric Learning JMLR 2017
Scalable Demand-Aware Recommendation NIPS 2017
Certifiably Optimal Low Rank Factor Analysis JMLR 2017
Memory Efficient Kernel Approximation JMLR 2017
Riemannian Optimization for Skip-Gram Negative Sampling ACL 2017