Algorithms and Certificates for Boolean CSP Refutation: "Smoothed is no harder than Random"
Venkatesan Guruswami, Pravesh K. Kothari, Peter Manohar

TL;DR
This paper introduces an algorithm for strongly refuting smoothed Boolean CSP instances, matching the efficiency of algorithms for random CSPs, and establishes a new connection to hypergraph covers that resolves Feige's conjecture.
Contribution
It presents a novel algorithm for smoothed CSP refutation with optimal trade-offs and links it to hypergraph even covers, resolving a longstanding conjecture.
Findings
Algorithm matches state-of-the-art for random CSPs
Resolves Feige's 2008 hypergraph conjecture
Polynomial-size refutation witnesses below spectral threshold
Abstract
We present an algorithm for strongly refuting smoothed instances of all Boolean CSPs. The smoothed model is a hybrid between worst and average-case input models, where the input is an arbitrary instance of the CSP with only the negation patterns of the literals re-randomized with some small probability. For an -variable smoothed instance of a -arity CSP, our algorithm runs in time, and succeeds with high probability in bounding the optimum fraction of satisfiable constraints away from , provided that the number of constraints is at least . This matches, up to polylogarithmic factors in , the trade-off between running time and the number of constraints of the state-of-the-art algorithms for refuting fully random instances of CSPs [RRS17]. We also make a surprising new connection between our algorithm and even…
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Taxonomy
TopicsMachine Learning and Algorithms · Bayesian Modeling and Causal Inference · Complexity and Algorithms in Graphs
