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Matrix Completion

Matrix Completion is a method for recovering lost information. It originates from machine learning and usually deals with highly sparse matrices. Missing or unknown data is estimated using the low-rank matrix of the known data.

Source: A Fast Matrix-Completion-Based Approach for Recommendation Systems

Papers

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Showing 151–200 of 796 papers

TitleStatusHype
A Non-convex One-Pass Framework for Generalized Factorization Machine and Rank-One Matrix Sensing—0
A General Framework for Fast Stagewise Algorithms—0
Annotation Projection-based Representation Learning for Cross-lingual Dependency Parsing—0
Causal Inference with Corrupted Data: Measurement Error, Missing Values, Discretization, and Differential Privacy—0
Causal Imputation for Counterfactual SCMs: Bridging Graphs and Latent Factor Models—0
A framework to generate sparsity-inducing regularizers for enhanced low-rank matrix completion—0
Active Feature Acquisition with Supervised Matrix Completion—0
Categorical Matrix Completion—0
Calibrated Elastic Regularization in Matrix Completion—0
Spectal Harmonics: Bridging Spectral Embedding and Matrix Completion in Self-Supervised Learning—0
An Extended Frank-Wolfe Method with "In-Face" Directions, and its Application to Low-Rank Matrix Completion—0
A Fast Matrix-Completion-Based Approach for Recommendation Systems—0
Bounded Manifold Completion—0
Low-rank matrix completion theory via Plucker coordinates—0
Boolean Matrix Factorization and Noisy Completion via Message Passing—0
Blocked Collaborative Bandits: Online Collaborative Filtering with Per-Item Budget Constraints—0
Adversarial Robust Low Rank Matrix Estimation: Compressed Sensing and Matrix Completion—0
A Comparison of Clustering and Missing Data Methods for Health Sciences—0
Abrupt Learning in Transformers: A Case Study on Matrix Completion—0
BlockEcho: Retaining Long-Range Dependencies for Imputing Block-Wise Missing Data—0
Blind Regression: Nonparametric Regression for Latent Variable Models via Collaborative Filtering—0
A New Theory for Matrix Completion—0
Binary matrix completion with nonconvex regularizers—0
Binary Matrix Completion Using Unobserved Entries—0
A New Retraction for Accelerating the Riemannian Three-Factor Low-Rank Matrix Completion Algorithm—0
Multi-source Learning via Completion of Block-wise Overlapping Noisy Matrices—0
PAC-Bayesian Matrix Completion with a Spectral Scaled Student Prior—0
Bayesian matrix completion: prior specification—0
A new accelerated gradient method inspired by continuous-time perspective—0
Bayesian Low-rank Matrix Completion with Dual-graph Embedding: Prior Analysis and Tuning-free Inference—0
Bayesian Learning for Low-Rank matrix reconstruction—0
Relative Error Bound Analysis for Nuclear Norm Regularized Matrix Completion—0
Bayesian Graph Convolutional Neural Networks Using Non-Parametric Graph Learning—0
Deterministic and Probabilistic Conditions for Finite Completability of Low-rank Multi-View Data—0
Amplify Graph Learning for Recommendation via Sparsity Completion—0
Advancing Thermodynamic Group-Contribution Methods by Machine Learning: UNIFAC 2.0—0
Bayesian Collaborative Bandits with Thompson Sampling for Improved Outreach in Maternal Health Program—0
Basis Pursuit Denoise with Nonsmooth Constraints—0
A More Stable Accelerated Gradient Method Inspired by Continuous-Time Perspective—0
Depth-Aided Color Image Inpainting in Quaternion Domain—0
Dense Air Quality Maps Using Regressive Facility Location Based Drive By Sensing—0
Demystifying Language Model Forgetting with Low-rank Example Associations—0
Balancing Accuracy and Diversity in Recommendations using Matrix Completion Framework—0
A Max-Norm Constrained Minimization Approach to 1-Bit Matrix Completion—0
Depth Enhancement via Low-rank Matrix Completion—0
Advancing Matrix Completion by Modeling Extra Structures beyond Low-Rankness—0
Depth Restoration: A fast low-rank matrix completion via dual-graph regularization—0
A Characterization of Deterministic Sampling Patterns for Low-Rank Matrix Completion—0
A Block Lanczos with Warm Start Technique for Accelerating Nuclear Norm Minimization Algorithms—0
Deep Non-Rigid Structure from Motion with Missing Data—0
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