All reports by Author Guy Kindler:

__
TR17-094
| 25th May 2017
__

Irit Dinur, Subhash Khot, Guy Kindler, Dor Minzer, Muli Safra#### On Non-Optimally Expanding Sets in Grassmann Graphs

__
TR16-198
| 14th December 2016
__

Irit Dinur, Subhash Khot, Guy Kindler, Dor Minzer, Muli Safra#### Towards a Proof of the 2-to-1 Games Conjecture?

__
TR16-007
| 23rd January 2016
__

Guy Kindler#### Property Testing, PCP, andJuntas

Revisions: 1

__
TR15-085
| 23rd May 2015
__

Irit Dinur, Prahladh Harsha, Guy Kindler#### Polynomially Low Error PCPs with polyloglogn Queries via Modular Composition

__
TR14-002
| 8th January 2014
__

Roee David, Irit Dinur, Elazar Goldenberg, Guy Kindler, Igor Shinkar#### Direct Sum Testing

Revisions: 1

__
TR10-037
| 8th March 2010
__

Boaz Barak, Guy Kindler, Ronen Shaltiel, Benny Sudakov, Avi Wigderson#### Simulating Independence: New Constructions of Condensers, Ramsey Graphs, Dispersers, and Extractors

__
TR07-043
| 7th May 2007
__

Uriel Feige, Guy Kindler, Ryan O'Donnell#### Understanding Parallel Repetition Requires Understanding Foams

__
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?

__
TR05-061
| 15th June 2005
__

Ronen Gradwohl, Guy Kindler, Omer Reingold, Amnon Ta-Shma#### On the Error Parameter of Dispersers

__
TR05-058
| 24th May 2005
__

Sanjeev Arora, Eli Berger, Elad Hazan, Guy Kindler, Muli Safra#### On Non-Approximability for Quadratic Programs

__
TR98-066
| 3rd November 1998
__

Irit Dinur, Eldar Fischer, Guy Kindler, Ran Raz, Shmuel Safra#### PCP Characterizations of NP: Towards a Polynomially-Small Error-Probability

__
TR98-048
| 6th July 1998
__

Irit Dinur, Guy Kindler, Shmuel Safra#### Approximating CVP to Within Almost Polynomial Factor is NP-Hard

Irit Dinur, Subhash Khot, Guy Kindler, Dor Minzer, Muli Safra

The paper investigates expansion properties of the Grassmann graph,

motivated by recent results of [KMS, DKKMS] concerning hardness

of the Vertex-Cover and of the $2$-to-$1$ Games problems. Proving the

hypotheses put forward by these papers seems to first require a better

understanding of these expansion properties.

We consider the edge ... more >>>

Irit Dinur, Subhash Khot, Guy Kindler, Dor Minzer, Muli Safra

We propose a combinatorial hypothesis regarding a subspace vs. subspace agreement test, and prove that if correct it leads to a proof of the 2-to-1 Games Conjecture, albeit with imperfect completeness.

Guy Kindler

The first part of this thesis strengthens the low-error PCP

characterization of NP, coming closer to the upper limit of the

conjecture of~\cite{BGLR}.

In the second part we show that a boolean function over

$n$ variables can be tested for the property of depending ...
more >>>

Irit Dinur, Prahladh Harsha, Guy Kindler

We show that every language in NP has a PCP verifier that tosses $O(\log n)$ random coins, has perfect completeness, and a soundness error of at most $1/poly(n)$, while making at most $O(poly\log\log n)$ queries into a proof over an alphabet of size at most $n^{1/poly\log\log n}$. Previous constructions that ... more >>>

Roee David, Irit Dinur, Elazar Goldenberg, Guy Kindler, Igor Shinkar

For a string $a \in \{0,1\}^n$ its $k$-fold direct sum encoding is a function $f_a$ that takes as input sets $S \subseteq [n]$ of

size $k$ and outputs $f_a(S) = \sum_{i \in S} a_i$.

In this paper we are interested in the Direct Sum Testing Problem,

where we are given ...
more >>>

Boaz Barak, Guy Kindler, Ronen Shaltiel, Benny Sudakov, Avi Wigderson

We present new explicit constructions of *deterministic* randomness extractors, dispersers and related objects. We say that a

distribution $X$ on binary strings of length $n$ is a

$\delta$-source if $X$ assigns probability at most $2^{-\delta n}$

to any string of length $n$. For every $\delta>0$ we construct the

following poly($n$)-time ...
more >>>

Uriel Feige, Guy Kindler, Ryan O'Donnell

Motivated by the study of Parallel Repetition and also by the Unique

Games Conjecture, we investigate the value of the ``Odd Cycle Games''

under parallel repetition. Using tools from discrete harmonic

analysis, we show that after $d$ rounds on the cycle of length $m$,

the value of the game is ...
more >>>

Guy Kindler, Ryan O'Donnell, Subhash Khot, Elchanan Mossel

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 >>>

Ronen Gradwohl, Guy Kindler, Omer Reingold, Amnon Ta-Shma

Optimal dispersers have better dependence on the error than

optimal extractors. In this paper we give explicit disperser

constructions that beat the best possible extractors in some

parameters. Our constructions are not strong, but we show that

having such explicit strong constructions implies a solution

to the Ramsey graph construction ...
more >>>

Sanjeev Arora, Eli Berger, Elad Hazan, Guy Kindler, Muli Safra

This paper studies the computational complexity of the following type of

quadratic programs: given an arbitrary matrix whose diagonal elements are zero, find $x \in \{-1,+1\}^n$ that maximizes $x^TA x$. This problem recently attracted attention due to its application in various clustering settings (Charikar and Wirth, 2004) as well as ...
more >>>

Irit Dinur, Eldar Fischer, Guy Kindler, Ran Raz, Shmuel Safra

This paper strengthens the low-error PCP characterization of NP, coming

closer to the ultimate BGLR conjecture. Namely, we prove that witnesses for

membership in any NP language can be verified with a constant

number of accesses, and with an error probability exponentially

small in the ...
more >>>

Irit Dinur, Guy Kindler, Shmuel Safra

This paper shows finding the closest vector in a lattice

to be NP-hard to approximate to within any factor up to

$2^{(\log{n})^{1-\epsilon}}$ where

$\epsilon = (\log\log{n})^{-\alpha}$

and $\alpha$ is any positive constant $<{1\over 2}$.