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Distributed Matrix Completion and Robust Factorization

5 July 2011

Papers citing "Distributed Matrix Completion and Robust Factorization"

36 / 36 papers shown

Title
GPU accelerated matrix factorization of large scale data using block based approach Prasad Bhavana V. Padmanabhan 35 0 0 02 Jan 2023
Modeling Dynamic User Preference via Dictionary Learning for Sequential Recommendation Chao Chen Dongsheng Li Junchi Yan Xiaokang Yang 38 16 0 02 Apr 2022
Learning Self-Modulating Attention in Continuous Time Space with Applications to Sequential Recommendation Chao Chen Haoyu Geng Nianzu Yang Junchi Yan Daiyue Xue Jianping Yu Xiaokang Yang HAI AI4TS 62 11 0 30 Mar 2022
Data splitting improves statistical performance in overparametrized regimes Nicole Mücke Enrico Reiss Jonas Rungenhagen Markus Klein 53 8 0 21 Oct 2021
Oversampling Divide-and-conquer for Response-skewed Kernel Ridge Regression Jingyi Zhang Xiaoxiao Sun 46 0 0 13 Jul 2021
Doubly Distributed Supervised Learning and Inference with High-Dimensional Correlated Outcomes Emily C. Hector P. Song FedML 90 15 0 16 Jul 2020
Federated Learning: Challenges, Methods, and Future Directions Tian Li Anit Kumar Sahu Ameet Talwalkar Virginia Smith FedML 149 4,568 0 21 Aug 2019
Block based Singular Value Decomposition approach to matrix factorization for recommender systems Prasad Bhavana Vikas Kumar V. Padmanabhan 113 10 0 17 Jul 2019
On the Difficulty of Evaluating Baselines: A Study on Recommender Systems Steffen Rendle Li Zhang Y. Koren 77 127 0 04 May 2019
WONDER: Weighted one-shot distributed ridge regression in high dimensions Yan Sun Yueqi Sheng OffRL 79 51 0 22 Mar 2019
BMF: Block matrix approach to factorization of large scale data Prasad Bhavana Vineet Nair 42 1 0 02 Jan 2019
Collaborative Filtering with Stability Dongsheng Li Chao Chen Q. Lv Junchi Yan Li Shang Stephen M. Chu 24 0 0 06 Nov 2018
Multi-Level Network Embedding with Boosted Low-Rank Matrix Approximation Jundong Li Liang Wu Huan Liu 45 35 0 26 Aug 2018
Scalable and Robust Community Detection with Randomized Sketching M. Rahmani Andre Beckus Adel Karimian George Atia 69 10 0 25 May 2018
Approximating Hamiltonian dynamics with the Nyström method Alessandro Rudi Leonard Wossnig C. Ciliberto Andrea Rocchetto Massimiliano Pontil Simone Severini 59 10 0 06 Apr 2018
A Distributed Frank-Wolfe Framework for Learning Low-Rank Matrices with the Trace Norm Wenjie Zheng A. Bellet Patrick Gallinari 69 19 0 20 Dec 2017
Robust PCA by Manifold Optimization Teng Zhang Yi Yang 93 45 0 01 Aug 2017
Block CUR: Decomposing Matrices using Groups of Columns Urvashi Oswal Swayambhoo Jain Kevin S. Xu Brian Eriksson 34 2 0 17 Mar 2017
Robust and Scalable Column/Row Sampling from Corrupted Big Data M. Rahmani George Atia 119 9 0 18 Nov 2016
Parallelizing Spectral Algorithms for Kernel Learning Gilles Blanchard Nicole Mücke 42 15 0 24 Oct 2016
A Neural Autoregressive Approach to Collaborative Filtering Yin Zheng Bangsheng Tang Wenkui Ding Hanning Zhou BDL 65 223 0 31 May 2016
Decomposition into Low-rank plus Additive Matrices for Background/Foreground Separation: A Review for a Comparative Evaluation with a Large-Scale Dataset T. Bouwmans A. Sobral S. Javed Soon Ki Jung E. Zahzah 99 332 0 04 Nov 2015
Randomized Robust Subspace Recovery for High Dimensional Data Matrices M. Rahmani George Atia 86 57 0 21 May 2015
oASIS: Adaptive Column Sampling for Kernel Matrix Approximation Raajen Patel Thomas A. Goldstein Eva L. Dyer Azalia Mirhoseini Richard G. Baraniuk 55 9 0 19 May 2015
On the Feasibility of Distributed Kernel Regression for Big Data Chen Xu Yongquan Zhang Runze Li 33 30 0 05 May 2015
Relative Error Bound Analysis for Nuclear Norm Regularized Matrix Completion Lijun Zhang Tianbao Yang Rong Jin Zhi Zhou 68 5 0 26 Apr 2015
High Dimensional Low Rank plus Sparse Matrix Decomposition M. Rahmani George Atia 154 78 0 01 Feb 2015
TuPAQ: An Efficient Planner for Large-scale Predictive Analytic Queries Evan R. Sparks Ameet Talwalkar Michael Franklin Michael I. Jordan Tim Kraska 97 25 0 31 Jan 2015
CUR Algorithm for Partially Observed Matrices Miao Xu Rong Jin Zhi Zhou 109 34 0 04 Nov 2014
Identifying Outliers in Large Matrices via Randomized Adaptive Compressive Sampling Xingguo Li Jarvis Haupt 110 59 0 01 Jul 2014
Low-Rank Modeling and Its Applications in Image Analysis Xiaowei Zhou Can Yang Hongyu Zhao Weichuan Yu 149 182 0 15 Jan 2014
On statistics, computation and scalability Michael I. Jordan 294 110 0 30 Sep 2013
Distributed Low-rank Subspace Segmentation Ameet Talwalkar Lester W. Mackey Yadong Mu Shih-Fu Chang Michael I. Jordan 96 35 0 20 Apr 2013
Revisiting the Nystrom Method for Improved Large-Scale Machine Learning Alex Gittens Michael W. Mahoney 120 416 0 07 Mar 2013
A Scalable CUR Matrix Decomposition Algorithm: Lower Time Complexity and Tighter Bound Shusen Wang Zhihua Zhang Jian Li 207 22 0 04 Oct 2012
Improved Bound for the Nystrom's Method and its Application to Kernel Classification Rong Jin Tianbao Yang M. Mahdavi Yu-Feng Li Zhi Zhou 125 61 0 09 Nov 2011