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← Core Methods
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Core Methods
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Matrix Factorization
383 directly classified papers
Papers per year
2004: 1
2006: 6
2007: 3
2008: 5
2009: 5
2010: 11
2011: 15
2012: 23
2013: 36
2014: 32
2015: 21
2016: 25
2017: 25
2018: 40
2019: 29
2020: 28
2021: 24
2022: 13
2023: 15
2024: 22
2025: 4
Papers
Federated Binary Matrix Factorization Using Proximal Optimization
AAAI 2025
Creating Coherence in Federated Non-Negative Matrix Factorization
AAAI 2025
Deep Rank-One Tensor Functional Factorization for Multi-Dimensional Data Recovery
AAAI 2025
Constrained Non-negative Matrix Factorization for Guided Topic Modeling of Minority Topics
EMNLP 2025
On Socially Fair Low-Rank Approximation and Column Subset Selection
NIPS 2024
Sparse NMF with Archetypal Regularization: Computational and Robustness Properties
JMLR 2024
Fine-Grained Bipartite Concept Factorization for Clustering
CVPR 2024
Accelerating Nuclear-norm Regularized Low-rank Matrix Optimization Through Burer-Monteiro Decomposition
JMLR 2024
LERE: Learning-Based Low-Rank Matrix Recovery with Rank Estimation
AAAI 2024
Fast Dynamic Sampling for Determinantal Point Processes
AISTATS 2024
Sample Efficient Learning of Factored Embeddings of Tensor Fields
AISTATS 2024
Compressing Large Language Models using Low Rank and Low Precision Decomposition
NIPS 2024
Efficient Leverage Score Sampling for Tensor Train Decomposition
NIPS 2024
Structured Matrix Basis for Multivariate Time Series Forecasting with Interpretable Dynamics
NIPS 2024
A tensor factorization model of multilayer network interdependence
JMLR 2024
Efficient Nonparametric Tensor Decomposition for Binary and Count Data
AAAI 2024
Fast and Accurate Estimation of Low-Rank Matrices from Noisy Measurements via Preconditioned Non-Convex Gradient Descent
AISTATS 2024
On the Computational and Statistical Complexity of Over-parameterized Matrix Sensing
JMLR 2024
Triple Component Matrix Factorization: Untangling Global, Local, and Noisy Components
JMLR 2024
Training a Tucker Model With Shared Factors: a Riemannian Optimization Approach
AISTATS 2024
A Bregman Proximal Stochastic Gradient Method with Extrapolation for Nonconvex Nonsmooth Problems
AAAI 2024
Delegation-Relegation for Boolean Matrix Factorization
AAAI 2024
Identifying Selections for Unsupervised Subtask Discovery
NIPS 2024
Unlabeled Principal Component Analysis and Matrix Completion
JMLR 2024
Generalized Tensor Decomposition for Understanding Multi-Output Regression under Combinatorial Shifts
NIPS 2024
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