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Electronic Colloquium on Computational Complexity

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Reports tagged with Sum of Squares:
TR13-184 | 23rd December 2013
Boaz Barak, Jonathan Kelner, David Steurer

Rounding Sum-of-Squares Relaxations

We present a general approach to rounding semidefinite programming relaxations obtained by the Sum-of-Squares method (Lasserre hierarchy). Our approach is based on using the connection between these relaxations and the Sum-of-Squares proof system to transform a *combining algorithm* -- an algorithm that maps a distribution over solutions into a (possibly ... more >>>

TR14-142 | 1st November 2014
Subhash Khot, Dana Moshkovitz

Candidate Lasserre Integrality Gap For Unique Games

We propose a candidate Lasserre integrality gap construction for the Unique Games problem.
Our construction is based on a suggestion in [KM STOC'11] wherein the authors study the complexity of approximately solving a system of linear equations over reals and suggest it as an avenue towards a (positive) resolution ... more >>>

TR16-058 | 12th April 2016
Boaz Barak, Samuel Hopkins, Jonathan Kelner, Pravesh Kothari, Ankur Moitra, Aaron Potechin

A Nearly Tight Sum-of-Squares Lower Bound for the Planted Clique Problem

We prove that with high probability over the choice of a random graph $G$ from the Erd\H{o}s-R\'enyi distribution $G(n,1/2)$, the $n^{O(d)}$-time degree $d$ Sum-of-Squares semidefinite programming relaxation for the clique problem will give a value of at least $n^{1/2-c(d/\log n)^{1/2}}$ for some constant $c>0$.
This yields a nearly tight ... more >>>

TR16-141 | 11th September 2016
Ryan O'Donnell

SOS is not obviously automatizable, even approximately

Revisions: 1

Suppose we want to minimize a polynomial $p(x) = p(x_1, \dots, x_n)$, subject to some polynomial constraints $q_1(x), \dots, q_m(x) \geq 0$, using the Sum-of-Squares (SOS) SDP hierarachy. Assume we are in the "explicitly bounded" ("Archimedean") case where the constraints include $x_i^2 \leq 1$ for all $1 \leq i \leq ... more >>>

TR17-011 | 22nd January 2017
Boaz Barak, Pravesh Kothari, David Steurer

Quantum entanglement, sum of squares, and the log rank conjecture

For every constant $\epsilon>0$, we give an $\exp(\tilde{O}(\sqrt{n}))$-time algorithm for the $1$ vs $1-\epsilon$ Best Separable State (BSS) problem of distinguishing, given an $n^2\times n^2$ matrix $M$ corresponding to a quantum measurement, between the case that there is a separable (i.e., non-entangled) state $\rho$ that $M$ accepts with probability $1$, ... more >>>

TR19-106 | 12th August 2019
Noah Fleming, Pravesh Kothari, Toniann Pitassi

Semialgebraic Proofs and Efficient Algorithm Design

Revisions: 4

Over the last twenty years, an exciting interplay has emerged between proof systems and algorithms. Some natural families of algorithms can be viewed as a generic translation from a proof that a solution exists into an algorithm for finding the solution itself. This connection has perhaps been the most consequential ... more >>>

TR20-012 | 14th February 2020
Dmitry Sokolov

(Semi)Algebraic Proofs over $\{\pm 1\}$ Variables

One of the major open problems in proof complexity is to prove lower bounds on $AC_0[p]$-Frege proof
systems. As a step toward this goal Impagliazzo, Mouli and Pitassi in a recent paper suggested to prove
lower bounds on the size for Polynomial Calculus over the $\{\pm 1\}$ basis. In this ... more >>>

TR20-136 | 11th September 2020
Irit Dinur, Yuval Filmus, Prahladh Harsha, Madhur Tulsiani

Explicit and structured sum of squares lower bounds from high dimensional expanders

We construct an explicit family of 3XOR instances which is hard for Omega(sqrt(log n)) levels of the Sum-of-Squares hierarchy. In contrast to earlier constructions, which involve a random component, our systems can be constructed explicitly in deterministic polynomial time.
Our construction is based on the high-dimensional expanders devised by Lubotzky, ... more >>>

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