Matrix Completion Survey: Theory, Algorithms, and Empirical Evaluation

TL;DR

This paper provides a comprehensive survey of matrix completion techniques, discussing theoretical foundations, algorithms, and empirical evaluations, including adaptive sampling strategies and their experimental behaviors.

Contribution

It offers a unified overview of matrix completion methods, highlighting both passive and adaptive approaches with experimental insights.

Findings

Adaptive sampling schemes can be effectively analyzed through synthetic experiments

The survey consolidates fundamental algorithms and their implementations

Empirical results demonstrate the behavior of adaptive strategies

Abstract

We present a concise survey of matrix completion methods and associated implementations of several fundamental algorithms. Our study covers both passive and adaptive strategies. We further illustrate the behavior of a simple adaptive sampling scheme through controlled synthetic experiments.