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Aravinda Kanchana Ruwanpathirana

2 accepted papers

2021

Additive Error Guarantees for Weighted Low Rank Approximation

ICML 2021oral

Low-rank approximation is a classic tool in data analysis, where the goal is to approximate a matrix $A$ with a low-rank matrix $L$ so as to minimize the error $\norm{A - L}_F^2$. However in many applications, approximating some entries is more important than others, which leads to the weighted low…

Cited by 6SourcePDFScholar
2021

Principal Component Regression with Semirandom Observations via Matrix Completion

AISTATS 2021poster

Principal Component Regression (PCR) is a popular method for prediction from data, and is one way to address the so-called multi-collinearity problem in regression. It was shown recently that algorithms for PCR such as hard singular value thresholding (HSVT) are also quite robust, in that they can h…

Cited by 3SourcePDFScholar