Low Rank Property

Low-rank property research focuses on exploiting the inherent low-rank structure within data matrices or tensors to improve efficiency and accuracy in various applications. Current research emphasizes developing algorithms that leverage this property, including those based on incremental low-rank learning, sharpness-aware minimization, and structured tensor models like Tucker decompositions. This focus is driven by the need for efficient processing of large datasets and improved generalization capabilities in machine learning, as well as enhanced performance in signal processing tasks like phase retrieval and source localization. The resulting advancements have significant implications for resource-constrained devices and applications requiring robust solutions in the presence of noisy or incomplete data.

Papers

December 15, 2023

ParsNets: A Parsimonious Orthogonal and Low-Rank Linear Networks for Zero-Shot Learning
Jingcai Guo, Qihua Zhou, Ruibing Li, Xiaocheng Lu, Ziming Liu, Junyang Chen, Xin Xie, Jie Zhang
Zero Shot Learning Post Hoc Orthogonalization Linear Network Low Rank Constraint Low Rank Property

July 14, 2023

Low Rank Properties for Estimating Microphones Start Time and Sources Emission Time
Faxian Cao, Yongqiang Cheng, Adil Mehmood Khan, Zhijing Yang, S. M. Ahsan Kazmiand Yingxiu Chang
Audio Recording Timing Analysis Low Rank Structure Source Localization Joint Audio Low Rank Property

June 20, 2023

InRank: Incremental Low-Rank Learning
Jiawei Zhao, Yifei Zhang, Beidi Chen, Florian Schäfer, Anima Anandkumar
LeArning Abstract Low Rank Matrix Greedy Learning Low Rank Property

May 25, 2023

Sharpness-Aware Minimization Leads to Low-Rank Features
Maksym Andriushchenko, Dara Bahri, Hossein Mobahi, Nicolas Flammarion
Low Rank Feature Wise Sharpness Aware Minimization Low Rank Property Layer Selective Rank Reduction

April 25, 2023

Alternating Local Enumeration (TnALE): Solving Tensor Network Structure Search with Fewer Evaluations
Chao Li, Junhua Zeng, Chunmei Li, Cesar Caiafa, Qibin Zhao
High Dimensional Tensor Efficient Enumeration Low Rank Property Tensor Network Structure Search

January 2, 2023

Causal Inference (C-inf) -- asymmetric scenario of typical phase transitions
Agostino Capponi, Mihailo Stojnic
Causal Inference Phase Transition Low Rank Matrix Recovery Random Duality Theory Low Rank Property

February 15, 2022

Low-Rank Phase Retrieval with Structured Tensor Models
Soo Min Kwon, Xin Li, Anand D. Sarwate
Low Rank Phase Retrieval Tucker Decomposition Tensor Model Low Rank Property

January 29, 2022

Exact Decomposition of Joint Low Rankness and Local Smoothness Plus Sparse Matrices
Jiangjun Peng, Yao Wang, Hongying Zhang, Jianjun Wang, Deyu Meng
Sparse Matrix Robust Principal Component Analysis Smoothness Assumption Matrix Decomposition Stagewise Decomposition Low Rank Property