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Musco, Cameron ;
Musco, Christopher ;
Woodruff, David P.
Simple Heuristics Yield Provable Algorithms for Masked Low-Rank Approximation
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LIPIcs-ITCS-2021-6.pdf (0.6 MB)
Abstract
In the masked low-rank approximation problem, one is given data matrix A ∈ ℝ^{n × n} and binary mask matrix W ∈ {0,1}^{n × n}. The goal is to find a rank-k matrix L for which:
cost(L) := ∑_{i=1}^n ∑_{j=1}^n W_{i,j} ⋅ (A_{i,j} - L_{i,j})² ≤ OPT + ε ‖A‖_F²,
where OPT = min_{rank-k L̂} cost(L̂) and ε is a given error parameter. Depending on the choice of W, the above problem captures factor analysis, low-rank plus diagonal decomposition, robust PCA, low-rank matrix completion, low-rank plus block matrix approximation, low-rank recovery from monotone missing data, and a number of other important problems. Many of these problems are NP-hard, and while algorithms with provable guarantees are known in some cases, they either 1) run in time n^Ω(k²/ε) or 2) make strong assumptions, for example, that A is incoherent or that the entries in W are chosen independently and uniformly at random.
In this work, we show that a common polynomial time heuristic, which simply sets A to 0 where W is 0, and then finds a standard low-rank approximation, yields bicriteria approximation guarantees for this problem. In particular, for rank k' > k depending on the public coin partition number of W, the heuristic outputs rank-k' L with cost(L) ≤ OPT + ε ‖A‖_F². This partition number is in turn bounded by the randomized communication complexity of W, when interpreted as a two-player communication matrix. For many important cases, including all those listed above, this yields bicriteria approximation guarantees with rank k' = k ⋅ poly(log n/ε).
Beyond this result, we show that different notions of communication complexity yield bicriteria algorithms for natural variants of masked low-rank approximation. For example, multi-player number-in-hand communication complexity connects to masked tensor decomposition and non-deterministic communication complexity to masked Boolean low-rank factorization.BibTeX - Entry
@InProceedings{musco_et_al:LIPIcs.ITCS.2021.6,
author = {Cameron Musco and Christopher Musco and David P. Woodruff},
title = {{Simple Heuristics Yield Provable Algorithms for Masked Low-Rank Approximation}},
booktitle = {12th Innovations in Theoretical Computer Science Conference (ITCS 2021)},
pages = {6:1--6:20},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-177-1},
ISSN = {1868-8969},
year = {2021},
volume = {185},
editor = {James R. Lee},
publisher = {Schloss Dagstuhl--Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/opus/volltexte/2021/13545},
URN = {urn:nbn:de:0030-drops-135452},
doi = {10.4230/LIPIcs.ITCS.2021.6},
annote = {Keywords: low-rank approximation, communication complexity, weighted low-rank approximation, bicriteria approximation algorithms}
}
Keywords:
low-rank approximation, communication complexity, weighted low-rank approximation, bicriteria approximation algorithms
Collection:
12th Innovations in Theoretical Computer Science Conference (ITCS 2021)
Issue Date:
2021
Date of publication:
04.02.2021
Supplementary Material:
Full paper available at https://arxiv.org/abs/1904.09841.