Search Results for author:
Found 3 papers, 1 papers with code
MLJ: A Julia package for composable machine learning
MLJ (Machine Learing in Julia) is an open source software package providing a common interface for interacting with machine learning models written in Julia and other languages.
Algebraic-Combinatorial Methods for Low-Rank Matrix Completion with Application to Athletic Performance Prediction
This paper presents novel algorithms which exploit the intrinsic algebraic and combinatorial structure of the matrix completion task for estimating missing en- tries in the general low rank setting.
Error-Minimizing Estimates and Universal Entry-Wise Error Bounds for Low-Rank Matrix Completion
We propose a general framework for reconstructing and denoising single entries of incomplete and noisy entries.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
