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We present an approximation scheme for minimizing certain Quadratic Integer Programming problems with positive semidefinite objective functions and global linear constraints. This framework includes well known graph problems such as Minimum…

Data Structures and Algorithms · Computer Science 2013-12-12 Venkatesan Guruswami , Ali Kemal Sinop

We show a new way to round vector solutions of semidefinite programming (SDP) hierarchies into integral solutions, based on a connection between these hierarchies and the spectrum of the input graph. We demonstrate the utility of our method…

Data Structures and Algorithms · Computer Science 2011-04-26 Boaz Barak , Prasad Raghavendra , David Steurer

Partitioning the vertices of a graph into two roughly equal parts while minimizing the number of edges crossing the cut is a fundamental problem (called Balanced Separator) that arises in many settings. For this problem, and variants such…

Computational Complexity · Computer Science 2015-03-20 Venkatesan Guruswami , Ali Kemal Sinop , Yuan Zhou

We generalize the reduction mechanism for linear programming problems and semidefinite programming problems from [arXiv:1410.8816] in two ways 1) relaxing the requirement of affineness and 2) extending to fractional optimization problems.…

Computational Complexity · Computer Science 2018-10-23 Gábor Braun , Sebastian Pokutta , Aurko Roy

This work is concerned with approximating constraint satisfaction problems (CSPs) with an additional global cardinality constraints. For example, \maxcut is a boolean CSP where the input is a graph $G = (V,E)$ and the goal is to find a cut…

Data Structures and Algorithms · Computer Science 2011-10-06 Prasad Raghavendra , Ning Tan

We design approximation algorithms for Unique Games when the constraint graph admits good low diameter graph decomposition. For the ${\sf Max2Lin}_k$ problem in $K_r$-minor free graphs, when there is an assignment satisfying $1-\varepsilon$…

Data Structures and Algorithms · Computer Science 2017-12-01 Vedat Levi Alev , Lap Chi Lau

We consider the NP-hard problem of minimizing a convex quadratic function over the integer lattice ${\bf Z}^n$. We present a simple semidefinite programming (SDP) relaxation for obtaining a nontrivial lower bound on the optimal value of the…

Optimization and Control · Mathematics 2017-03-16 Jaehyun Park , Stephen Boyd

This thesis explores algorithmic applications and limitations of convex relaxation hierarchies for approximating some discrete and continuous optimization problems. - We show a dichotomy of approximability of constraint satisfaction…

Computational Complexity · Computer Science 2025-09-01 Mrinalkanti Ghosh

The UNIQUE GAMES problem is a central problem in algorithms and complexity theory. Given an instance of UNIQUE GAMES, the STRONG UNIQUE GAMES problem asks to find the largest subset of vertices, such that the UNIQUE GAMES instance induced…

Data Structures and Algorithms · Computer Science 2020-05-19 Suprovat Ghoshal , Anand Louis

The vertex expansion of the graph is a fundamental graph parameter. Given a graph $G=(V,E)$ and a parameter $\delta \in (0,1/2]$, its $\delta$-Small-Set Vertex Expansion (SSVE) is defined as \[ \min_{S : |S| = \delta |V|}…

Data Structures and Algorithms · Computer Science 2023-11-29 Suprovat Ghoshal , Anand Louis

The Min-sum single machine scheduling problem (denoted 1||sum f_j) generalizes a large number of sequencing problems. The first constant approximation guarantees have been obtained only recently and are based on natural time-indexed LP…

Data Structures and Algorithms · Computer Science 2015-11-30 Adam Kurpisz , Samuli Leppänen , Monaldo Mastrolilli

Convex relaxations based on different hierarchies of linear/semi-definite programs have been used recently to devise approximation algorithms for various optimization problems. The approximation guarantee of these algorithms improves with…

Data Structures and Algorithms · Computer Science 2015-03-20 Venkatesan Guruswami , Ali Kemal Sinop

Constraint satisfaction problems (CSPs) are ubiquitous in theoretical computer science. We study the problem of StrongCSPs, i.e. instances where a large induced sub-instance has a satisfying assignment. More formally, given a CSP instance…

Data Structures and Algorithms · Computer Science 2022-05-24 Suprovat Ghoshal , Anand Louis

Semidefinite programs (SDPs) are a framework for exact or approximate optimization that have widespread application in quantum information theory. We introduce a new method for using reductions to construct integrality gaps for SDPs. These…

Quantum Physics · Physics 2019-03-18 Aram W. Harrow , Anand Natarajan , Xiaodi Wu

Topology optimization of frame structures under free-vibration eigenvalue constraints constitutes a challenging nonconvex polynomial optimization problem with disconnected feasible sets. In this article, we first formulate it as a…

Optimization and Control · Mathematics 2025-09-08 Marek Tyburec , Michal Kočvara , Marouan Handa , Jan Zeman

Kolla and Tulsiani [KT07,Kolla11} and Arora, Barak and Steurer [ABS10] introduced the technique of subspace enumeration, which gives approximation algorithms for graph problems such as unique games and small set expansion; the running time…

Data Structures and Algorithms · Computer Science 2012-12-11 Shayan Oveis Gharan , Luca Trevisan

The matching problem between two adjacency matrices can be formulated as the NP-hard quadratic assignment problem (QAP). Previous work on semidefinite programming (SDP) relaxations to the QAP have produced solutions that are often tight in…

Optimization and Control · Mathematics 2017-03-29 Jose F. S. Bravo Ferreira , Yuehaw Khoo , Amit Singer

We give a new algorithm for Unique Games which is based on purely {\em spectral} techniques, in contrast to previous work in the area, which relies heavily on semidefinite programming (SDP). Given a highly satisfiable instance of Unique…

Computational Complexity · Computer Science 2011-02-14 Alexandra Kolla

We give an algorithm for solving unique games (UG) instances whenever low-degree sum-of-squares proofs certify good bounds on the small-set-expansion of the underlying constraint graph via a hypercontractive inequality. Our algorithm is in…

Computational Complexity · Computer Science 2021-06-29 Mitali Bafna , Boaz Barak , Pravesh Kothari , Tselil Schramm , David Steurer

We initiate the study of approximating the largest induced expander in a given graph $G$. Given a $\Delta$-regular graph $G$ with $n$ vertices, the goal is to find the set with the largest induced expansion of size at least $\delta \cdot…

Data Structures and Algorithms · Computer Science 2015-11-10 Shayan Oveis Gharan , Alireza Rezaei
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