Rank-Sparsity Incoherence for Matrix Decomposition

11 June 2009

Sujay Sanghavi

Papers citing "Rank-Sparsity Incoherence for Matrix Decomposition"

50 / 276 papers shown

Title
AltGDmin: Alternating GD and Minimization for Partly-Decoupled (Federated) Optimization Namrata Vaswani 44 0 0 20 Apr 2025
Preconditioned Gradient Descent for Over-Parameterized Nonconvex Matrix Factorization G. Zhang S. Fattahi Richard Y. Zhang 47 36 0 13 Apr 2025
Alternating minimization for square root principal component pursuit Shengxiang Deng Xudong Li Yangjing Zhang 42 0 0 31 Dec 2024
$$\ell_0$ factor analysis$ $\ell_0$ factor analysis Linyang Wang Wanquan Liu Bin Zhu 27 2 0 13 Nov 2024
Tailed Low-Rank Matrix Factorization for Similarity Matrix Completion Changyi Ma Runsheng Yu Xiao Chen Youzhi Zhang 26 0 0 29 Sep 2024
OATS: Outlier-Aware Pruning Through Sparse and Low Rank Decomposition Stephen Zhang Vardan Papyan VLM 51 1 0 20 Sep 2024
Attention Incorporated Network for Sharing Low-rank, Image and K-space Information during MR Image Reconstruction to Achieve Single Breath-hold Cardiac Cine Imaging Siying Xu Kerstin Hammernik Andreas Lingg Jens Kuebler Patrick Krumm Daniel Rueckert S. Gatidis T. Kuestner 31 1 0 03 Jul 2024
SLTrain: a sparse plus low-rank approach for parameter and memory efficient pretraining Andi Han Jiaxiang Li Wei Huang Mingyi Hong Akiko Takeda Pratik Jawanpuria Bamdev Mishra 46 10 0 04 Jun 2024
Extremal graphical modeling with latent variables via convex optimization Sebastian Engelke Armeen Taeb 31 2 0 14 Mar 2024
Get More with LESS: Synthesizing Recurrence with KV Cache Compression for Efficient LLM Inference Harry Dong Xinyu Yang Zhenyu Zhang Zhangyang Wang Yuejie Chi Beidi Chen 35 49 0 14 Feb 2024
A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables Xinshuai Dong Erdun Gao Ignavier Ng Xiangchen Song Yujia Zheng Songyao Jin Roberto Legaspi Peter Spirtes Kun Zhang BDL CML 30 10 0 18 Dec 2023
Learning Dynamics in Linear VAE: Posterior Collapse Threshold, Superfluous Latent Space Pitfalls, and Speedup with KL Annealing Yuma Ichikawa Koji Hukushima 26 5 0 24 Oct 2023
Provably Accelerating Ill-Conditioned Low-rank Estimation via Scaled Gradient Descent, Even with Overparameterization Cong Ma Xingyu Xu Tian Tong Yuejie Chi 18 9 0 09 Oct 2023
Byzantine-Resilient Federated PCA and Low Rank Column-wise Sensing Ankit Pratap Singh Namrata Vaswani 32 0 0 25 Sep 2023
Generalized Independent Noise Condition for Estimating Causal Structure with Latent Variables Feng Xie Erdun Gao Zhen Chen Ruichu Cai Clark Glymour Zhi Geng Kun Zhang CML 31 5 0 13 Aug 2023
Causality-oriented robustness: exploiting general noise interventions Xinwei Shen Peter Buhlmann Armeen Taeb OOD 67 8 0 18 Jul 2023
Identification of Nonlinear Latent Hierarchical Models Lingjing Kong Erdun Gao Feng Xie Eric Xing Yuejie Chi Kun Zhang CML 32 19 0 13 Jun 2023
Active-Learning-Driven Surrogate Modeling for Efficient Simulation of Parametric Nonlinear Systems Harshit Kapadia Lihong Feng P. Benner 15 9 0 09 Jun 2023
SKI to go Faster: Accelerating Toeplitz Neural Networks via Asymmetric Kernels Alexander Moreno Jonathan Mei Luke Walters 23 0 0 15 May 2023
Robust Tensor CUR Decompositions: Rapid Low-Tucker-Rank Tensor Recovery with Sparse Corruption HanQin Cai Zehan Chao Longxiu Huang Deanna Needell 37 11 0 06 May 2023
Domain Generalization via Nuclear Norm Regularization Zhenmei Shi Yifei Ming Ying Fan Frederic Sala Yingyu Liang 30 12 0 13 Mar 2023
Robust Autoencoders for Collective Corruption Removal Taihui Li Hengkang Wang Peng Le XianE Tang Ju Sun OOD 18 1 0 06 Mar 2023
Can Learning Be Explained By Local Optimality In Robust Low-rank Matrix Recovery? Jianhao Ma S. Fattahi 36 0 0 21 Feb 2023
Multi-Rate VAE: Train Once, Get the Full Rate-Distortion Curve Juhan Bae Michael Ruogu Zhang Michael Ruan Eric Wang S. Hasegawa Jimmy Ba Roger C. Grosse DRL 29 17 0 07 Dec 2022
Latent Hierarchical Causal Structure Discovery with Rank Constraints Erdun Gao C. Low Feng Xie Clark Glymour Kun Zhang CML 70 40 0 01 Oct 2022
Bounded Simplex-Structured Matrix Factorization: Algorithms, Identifiability and Applications Olivier Vu Thanh Nicolas Gillis Fabian Lecron 14 3 0 26 Sep 2022
Optimal Sparse Estimation of High Dimensional Heavy-tailed Time Series Sagnik Halder George Michailidis AI4TS 13 0 0 19 Sep 2022
Large covariance matrix estimation via penalized log-det heuristics E. Bernardi M. Farné 28 0 0 11 Sep 2022
Signed Network Embedding with Application to Simultaneous Detection of Communities and Anomalies H. Zhang Junhui Wang 14 1 0 08 Jul 2022
Fast and Provable Tensor Robust Principal Component Analysis via Scaled Gradient Descent Harry Dong Tian Tong Cong Ma Yuejie Chi 43 12 0 18 Jun 2022
Robust Projection based Anomaly Extraction (RPE) in Univariate Time-Series M. Rahmani Anoop Deoras Laurent Callot AI4TS 31 0 0 31 May 2022
Stochastic and Private Nonconvex Outlier-Robust PCA Tyler Maunu Chenyun Yu Gilad Lerman 19 3 0 17 Mar 2022
Flat minima generalize for low-rank matrix recovery Lijun Ding Dmitriy Drusvyatskiy Maryam Fazel Zaid Harchaoui 46 16 0 07 Mar 2022
Robust Estimation for Random Graphs Jayadev Acharya Ayush Jain Gautam Kamath A. Suresh Huanyu Zhang 30 8 0 09 Nov 2021
Rethinking Point Cloud Filtering: A Non-Local Position Based Approach Jinxi Wang Jincen Jiang Xuequan Lu Meili Wang 3DPC 35 14 0 14 Oct 2021
Learned Robust PCA: A Scalable Deep Unfolding Approach for High-Dimensional Outlier Detection HanQin Cai Jialin Liu W. Yin 38 39 0 11 Oct 2021
Provable Low Rank Plus Sparse Matrix Separation Via Nonconvex Regularizers April Sagan J. Mitchell 24 0 0 26 Sep 2021
Sparse Plus Low Rank Matrix Decomposition: A Discrete Optimization Approach Dimitris Bertsimas Ryan Cory-Wright Nicholas A. G. Johnson 22 13 0 26 Sep 2021
Active manifolds, stratifications, and convergence to local minima in nonsmooth optimization Damek Davis Dmitriy Drusvyatskiy L. Jiang 33 10 0 26 Aug 2021
Distributed stochastic inertial-accelerated methods with delayed derivatives for nonconvex problems Yangyang Xu Yibo Xu Yonggui Yan Jiewei Chen 17 4 0 24 Jul 2021
Model compression as constrained optimization, with application to neural nets. Part V: combining compressions Miguel Á. Carreira-Perpiñán Yerlan Idelbayev 30 6 0 09 Jul 2021
Closed-Form, Provable, and Robust PCA via Leverage Statistics and Innovation Search M. Rahmani Ping Li 24 4 0 23 Jun 2021
Square Root Principal Component Pursuit: Tuning-Free Noisy Robust Matrix Recovery Junhui Zhang Jingkai Yan John N. Wright 33 6 0 17 Jun 2021
Towards Understanding Generalization via Decomposing Excess Risk Dynamics Jiaye Teng Jianhao Ma Yang Yuan 29 4 0 11 Jun 2021
Low-Rank Subspaces in GANs Jiapeng Zhu Ruili Feng Yujun Shen Deli Zhao Zhengjun Zha Jingren Zhou Qifeng Chen GAN 24 71 0 08 Jun 2021
Learning Gaussian Graphical Models with Latent Confounders Ke Wang Alexander M. Franks Sang-Yun Oh CML 32 2 0 14 May 2021
An algebraic estimator for large spectral density matrices M. Barigozzi M. Farné 29 7 0 05 Apr 2021
Generalized Low-rank plus Sparse Tensor Estimation by Fast Riemannian Optimization Jian-Feng Cai Jingyang Li Dong Xia 49 30 0 16 Mar 2021
Robust Principal Component Analysis: A Median of Means Approach Debolina Paul Saptarshi Chakraborty Swagatam Das 24 8 0 05 Feb 2021
Sign-RIP: A Robust Restricted Isometry Property for Low-rank Matrix Recovery Jianhao Ma S. Fattahi 18 12 0 05 Feb 2021