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REPORTS > AUTHORS > ILAN KOMARGODSKI:
All reports by Author Ilan Komargodski:

TR19-113 | 5th September 2019
Tomer Grossman, Ilan Komargodski, Moni Naor

Instance Complexity and Unlabeled Certificates in the Decision Tree Model

Instance complexity is a measure of goodness of an algorithm in which the performance of one algorithm is compared to others per input. This is in sharp contrast to worst-case and average-case complexity measures, where the performance is compared either on the worst input or on an average one, ... more >>>


TR18-140 | 11th August 2018
Ilan Komargodski, Ran Raz, Yael Tauman Kalai

A Lower Bound for Adaptively-Secure Collective Coin-Flipping Protocols

Revisions: 1

In 1985, Ben-Or and Linial (Advances in Computing Research '89) introduced the collective coin-flipping problem, where $n$ parties communicate via a single broadcast channel and wish to generate a common random bit in the presence of adaptive Byzantine corruptions. In this model, the adversary can decide to corrupt a party ... more >>>


TR17-060 | 9th April 2017
Boaz Barak, Zvika Brakerski, Ilan Komargodski, Pravesh Kothari

Limits on Low-Degree Pseudorandom Generators (Or: Sum-of-Squares Meets Program Obfuscation)

Revisions: 1

We prove that for every function $G\colon\{0,1\}^n \rightarrow \mathbb{R}^m$, if every output of $G$ is a polynomial (over $\mathbb{R}$) of degree at most $d$ of at most $s$ monomials and $m > \widetilde{O}(sn^{\lceil d/2 \rceil})$, then there is a polynomial time algorithm that can distinguish a vector of the form ... more >>>


TR17-015 | 4th February 2017
Ilan Komargodski, Moni Naor, Eylon Yogev

White-Box vs. Black-Box Complexity of Search Problems: Ramsey and Graph Property Testing

Revisions: 1

Ramsey theory assures us that in any graph there is a clique or independent set of a certain size, roughly logarithmic in the graph size. But how difficult is it to find the clique or independent set? If the graph is given explicitly, then it is possible to do so ... more >>>


TR16-131 | 21st August 2016
Andrej Bogdanov, Siyao Guo, Ilan Komargodski

Threshold Secret Sharing Requires a Linear Size Alphabet

We prove that for every $n$ and $1 < t < n$ any $t$-out-of-$n$ threshold secret sharing scheme for one-bit secrets requires share size $\log(t + 1)$. Our bound is tight when $t = n - 1$ and $n$ is a prime power. In 1990 Kilian and Nisan proved ... more >>>


TR16-023 | 23rd February 2016
Ilan Komargodski, Moni Naor, Eylon Yogev

How to Share a Secret, Infinitely

Revisions: 4

Secret sharing schemes allow a dealer to distribute a secret piece of information among several parties so that any qualified subset of parties can reconstruct the secret, while every unqualified subset of parties learns nothing about the secret. The collection of qualified subsets is called an access structure. The best ... more >>>


TR15-092 | 31st May 2015
Yael Tauman Kalai, Ilan Komargodski

Compressing Communication in Distributed Protocols

Revisions: 2

We show how to compress communication in distributed protocols in which parties do not have private inputs. More specifically, we present a generic method for converting any protocol in which parties do not have private inputs, into another protocol where each message is "short" while preserving the same number of ... more >>>


TR15-064 | 19th April 2015
Ilan Komargodski, Pravesh Kothari, Madhu Sudan

Communication with Contextual Uncertainty

Revisions: 1

We introduce a simple model illustrating the role of context in communication and the challenge posed by uncertainty of knowledge of context. We consider a variant of distributional communication complexity where Alice gets some information $x$ and Bob gets $y$, where $(x,y)$ is drawn from a known distribution, and Bob ... more >>>


TR15-026 | 21st February 2015
Siyao Guo, Ilan Komargodski

Negation-Limited Formulas

Revisions: 1

Understanding the power of negation gates is crucial to bridge the exponential gap between monotone and non-monotone computation. We focus on the model of formulas over the De Morgan basis and consider it in a negation-limited setting.

We prove that every formula that contains $t$ negation gates can be shrunk ... more >>>


TR14-025 | 25th February 2014
Oded Goldreich, Tom Gur, Ilan Komargodski

Strong Locally Testable Codes with Relaxed Local Decoders

Locally testable codes (LTCs) are error-correcting codes
that admit very efficient codeword tests. An LTC is said to
be strong if it has a proximity-oblivious tester;
that is, a tester that makes only a constant number of queries
and reject non-codewords with probability that depends solely
on their distance from ... more >>>


TR13-058 | 5th April 2013
Ilan Komargodski, Ran Raz, Avishay Tal

Improved Average-Case Lower Bounds for DeMorgan Formula Size

Revisions: 2

We give a function $h:\{0,1\}^n\to\{0,1\}$ such that every deMorgan formula of size $n^{3-o(1)}/r^2$ agrees with $h$ on at most a fraction of $\frac{1}{2}+2^{-\Omega(r)}$ of the inputs. This improves the previous average-case lower bound of Komargodski and Raz (STOC, 2013).

Our technical contributions include a theorem that shows that the ``expected ... more >>>


TR12-182 | 24th December 2012
Itay Berman, Iftach Haitner, Ilan Komargodski, Moni Naor

Hardness Preserving Reductions via Cuckoo Hashing

Revisions: 2

A common method for increasing the usability and uplifting the security of pseudorandom function families (PRFs) is to ``hash" the inputs into a smaller domain before applying the PRF. This approach, known as ``Levin's trick", is used to achieve ``PRF domain extension" (using a short, e.g., fixed, input length PRF ... more >>>


TR12-174 | 12th December 2012
Anat Ganor, Ilan Komargodski, Ran Raz

The Spectrum of Small DeMorgan Formulas

Revisions: 1

We show a connection between the deMorgan formula size of a Boolean function and the noise stability of the function. Using this connection, we show that the Fourier spectrum of any balanced Boolean function computed by a deMorgan formula of size $s$ is concentrated on coefficients of degree up to ... more >>>


TR12-062 | 17th May 2012
Ilan Komargodski, Ran Raz

Average-Case Lower Bounds for Formula Size

Revisions: 2

We give an explicit function $h:\{0,1\}^n\to\{0,1\}$ such that any deMorgan formula of size $O(n^{2.499})$ agrees with $h$ on at most $\frac{1}{2} + \epsilon$ fraction of the inputs, where $\epsilon$ is exponentially small (i.e. $\epsilon = 2^{-n^{\Omega(1)}}$). Previous lower bounds for formula size were obtained for exact computation.

The same ... more >>>




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