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REPORTS > AUTHORS > SUBHASH KHOT:
All reports by Author Subhash Khot:

TR11-119 | 4th September 2011
Subhash Khot, Preyas Popat, Nisheeth Vishnoi

$2^{\log^{1-\epsilon} n}$ Hardness for Closest Vector Problem with Preprocessing

We prove that for an arbitrarily small constant $\eps>0,$ assuming NP$\not \subseteq$DTIME$(2^{{\log^{O(1/\epsilon)} n}})$, the preprocessing versions of the closest vector problem and the nearest codeword problem are hard to approximate within a factor better than $2^{\log ^{1-\epsilon}n}.$ This improves upon the previous hardness factor of $(\log n)^\delta$ for some $\delta ... more >>>


TR10-112 | 15th July 2010
Subhash Khot, Dana Moshkovitz

NP-Hardness of Approximately Solving Linear Equations Over Reals

In this paper, we consider the problem of approximately solving a system of homogeneous linear equations over reals, where each
equation contains at most three variables.

Since the all-zero assignment always satisfies all the equations exactly, we restrict the assignments to be ``non-trivial". Here is
an informal statement of our ... more >>>


TR10-053 | 28th March 2010
Dana Moshkovitz, Subhash Khot

Hardness of Approximately Solving Linear Equations Over Reals

Comments: 1

In this paper, we consider the problem of approximately solving a
system of homogeneous linear equations over reals, where each
equation contains at most three variables.

Since the all-zero assignment always satisfies all the equations
exactly, we restrict the assignments to be ``non-trivial". Here is
an informal statement of our ... more >>>


TR07-073 | 3rd August 2007
Parikshit Gopalan, Subhash Khot, Rishi Saket

Hardness of Reconstructing Multivariate Polynomials over Finite Fields

We study the polynomial reconstruction problem for low-degree
multivariate polynomials over finite fields. In the GF[2] version of this problem, we are given a set of points on the hypercube and target values $f(x)$ for each of these points, with the promise that there is a polynomial over GF[2] of ... more >>>


TR06-059 | 3rd May 2006
Vitaly Feldman, Parikshit Gopalan, Subhash Khot, Ashok Kumar Ponnuswami

New Results for Learning Noisy Parities and Halfspaces

We address well-studied problems concerning the learnability of parities and halfspaces in the presence of classification noise.

Learning of parities under the uniform distribution with random classification noise,also called the noisy parity problem is a famous open problem in computational learning. We reduce a number of basic problems regarding learning ... more >>>


TR05-101 | 20th September 2005
Guy Kindler, Ryan O'Donnell, Subhash Khot, Elchanan Mossel

Optimal Inapproximability Results for MAX-CUT and Other 2-Variable CSPs?

In this paper we show a reduction from the Unique Games problem to the problem of approximating MAX-CUT to within a factor of $\GW + \eps$, for all $\eps > 0$; here $\GW \approx .878567$ denotes the approximation ratio achieved by the Goemans-Williamson algorithm~\cite{GW95}. This implies that if the Unique ... more >>>


TR05-064 | 26th June 2005
Howard Karloff, Subhash Khot, Aranyak Mehta, Yuval Rabani

On earthmover distance, metric labeling, and 0-extension

We study the classification problem {\sc Metric Labeling} and its special case {\sc 0-Extension} in the context of earthmover metrics. Researchers recently proposed using earthmover metrics to get a polynomial time-solvable relaxation of {\sc Metric Labeling}; until now, however, no one knew if the integrality ratio was constant or not, ... more >>>


TR02-027 | 30th April 2002
Irit Dinur, Venkatesan Guruswami, Subhash Khot

Vertex Cover on k-Uniform Hypergraphs is Hard to Approximate within Factor (k-3-\epsilon)

Given a $k$-uniform hypergraph, the E$k$-Vertex-Cover problem is
to find a minimum subset of vertices that ``hits'' every edge. We
show that for every integer $k \geq 5$, E$k$-Vertex-Cover is
NP-hard to approximate within a factor of $(k-3-\epsilon)$, for
an arbitrarily small constant $\epsilon > 0$.

This almost matches the ... more >>>




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