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Electronic Colloquium on Computational Complexity

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All reports by Author Nikolay Vereshchagin:

TR23-011 | 13th February 2023
Mikhail Dektiarev, Nikolay Vereshchagin

Half-duplex communication complexity with adversary? can be less than the classical communication complexity

Half-duplex communication complexity with adversary was defined in [Hoover, K., Impagliazzo, R., Mihajlin, I., Smal, A. V. Half-Duplex Communication Complexity, ISAAC 2018.] Half-duplex communication protocols generalize classical protocols defined by Andrew Yao in [Yao, A. C.-C. Some Complexity Questions Related to Distributive Computing (Preliminary Report), STOC 1979]. It has been ... more >>>

TR22-060 | 27th April 2022
Nikolay Vereshchagin

How much randomness is needed to convert MA protocols to AM protocols?

The Merlin-Arthur class of languages MA is included into Arthur-Merlin class AM, and into PP. For a standard transformation of a given MA protocol with Arthur's message (= random string) of length $a$ and Merlin's message of length $m$ to a PP machine, the latter needs $O(ma)$ random bits. The ... more >>>

TR17-043 | 3rd March 2017
Alexey Milovanov, Nikolay Vereshchagin

Stochasticity in Algorithmic Statistics for Polynomial Time

A fundamental notion in Algorithmic Statistics is that of a stochastic object, i.e., an object having a simple plausible explanation. Informally, a probability distribution is a plausible explanation for $x$ if it looks likely that $x$ was drawn at random with respect to that distribution. In this paper, we ... more >>>

TR13-178 | 14th December 2013
Nikolay Vereshchagin

Randomized communication complexity of appropximating Kolmogorov complexity

Revisions: 2

The paper [Harry Buhrman, Michal Koucky, Nikolay Vereshchagin. Randomized Individual Communication Complexity. IEEE Conference on Computational Complexity 2008: 321-331] considered communication complexity of the following problem. Alice has a binary string $x$ and Bob a binary string $y$, both of length $n$, and they want to compute or approximate
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TR13-007 | 8th January 2013
Bruno Bauwens, Anton Makhlin, Nikolay Vereshchagin, Marius Zimand

Short lists with short programs in short time

Revisions: 1

Given a machine $U$, a $c$-short program for $x$ is a string $p$ such that $U(p)=x$ and the length of $p$ is bounded by $c$ + (the length of a shortest program for $x$). We show that for any universal machine, it is possible to compute in polynomial time on ... more >>>

TR11-167 | 6th December 2011
Nikolay Vereshchagin

Improving on Gutfreund, Shaltiel, and Ta-Shma's paper "If NP Languages are Hard on the Worst-Case, Then it is Easy to Find Their Hard Instances''

Revisions: 1

Assume that $NP\ne RP$. Gutfreund, Shaltiel, and Ta-Shma in [Computational Complexity 16(4):412-441 (2007)] have proved that for every randomized polynomial time decision algorithm $D$ for SAT there is a polynomial time samplable distribution such that $D$ errs with probability at least $1/6-\epsilon$ on a random formula chosen with respect to ... more >>>

TR10-163 | 3rd November 2010
Harry Buhrman, Leen Torenvliet, Falk Unger, Nikolay Vereshchagin

Sparse Selfreducible Sets and Nonuniform Lower Bounds

It is well-known that the class of sets that can be computed by polynomial size circuits is equal to the class of sets that are polynomial time reducible to a sparse set. It is widely believed, but unfortunately up to now unproven, that there are sets in $EXP^{NP}$, or even ... more >>>

TR10-091 | 14th May 2010
Nikolay Vereshchagin

An Encoding Invariant Version of Polynomial Time Computable Distributions

When we represent a decision problem,like CIRCUIT-SAT, as a language over the binary alphabet,
we usually do not specify how to encode instances by binary strings.
This relies on the empirical observation that the truth of a statement of the form ``CIRCUIT-SAT belongs to a complexity class $C$''
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TR10-090 | 14th May 2010
Nikolay Vereshchagin

{Algorithmic Minimal Sufficient Statistics: a New Definition

We express some criticism about the definition of an algorithmic sufficient statistic and, in particular, of an algorithmic minimal sufficient statistic. We propose another definition, which has better properties.

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TR06-024 | 18th February 2006
Harry Burhman, Lance Fortnow, Michal Koucky, John Rogers, Nikolay Vereshchagin

Inverting onto functions might not be hard

The class TFNP, defined by Megiddo and Papadimitriou, consists of
multivalued functions with values that are polynomially verifiable
and guaranteed to exist. Do we have evidence that such functions are
hard, for example, if TFNP is computable in polynomial-time does
this imply the polynomial-time hierarchy collapses?

We give a relativized ... more >>>

TR05-095 | 26th August 2005
Noga Alon, Ilan Newman, Alexander Shen, Gábor Tardos, Nikolay Vereshchagin

Partitioning multi-dimensional sets in a small number of ``uniform'' parts

Our main result implies the following easily formulated statement. The set of edges E of every finite bipartite graph can be split into poly(log |E|) subsets so the all the resulting bipartite graphcs are almost regular. The latter means that the ratio between the maximal and minimal non-zero degree of ... more >>>

TR04-081 | 9th September 2004
Harry Buhrman, Lance Fortnow, Ilan Newman, Nikolay Vereshchagin

Increasing Kolmogorov Complexity

How much do we have to change a string to increase its Kolmogorov complexity. We show that we can
increase the complexity of any non-random string of length n by flipping O(sqrt(n)) bits and some strings
Omega(sqrt(n)) bit flips. For a given m, we also give bounds for ... more >>>

TR04-080 | 7th September 2004
Lance Fortnow, Troy Lee, Nikolay Vereshchagin

Kolmogorov Complexity with Error

We introduce the study of Kolmogorov complexity with error. For a
metric d, we define C_a(x) to be the length of a shortest
program p which prints a string y such that d(x,y) \le a. We
also study a conditional version of this measure C_{a,b}(x|y)
where the task is, given ... more >>>

TR04-054 | 5th June 2004
Andrej Muchnik, Alexander Shen, Nikolay Vereshchagin, Mikhail V. Vyugin

Non-reducible descriptions for conditional Kolmogorov complexity

Let a program p on input a output b. We are looking for a
shorter program p' having the same property (p'(a)=b). In
addition, we want p' to be simple conditional to p (this
means that the conditional Kolmogorov complexity K(p'|p) is
negligible). In the present paper, we prove that ... more >>>

TR04-030 | 9th March 2004
Nikolay Vereshchagin

Kolmogorov complexity of enumerating finite sets

Solovay has proven that
the minimal length of a program enumerating a set A
is upper bounded by 3 times the absolute value of the
logarithm of the
probability that a random program will enumerate A.
It is unknown whether one can replace the constant
3 by a smaller constant.
more >>>

TR01-089 | 29th October 2001
Andrej Muchnik, Nikolay Vereshchagin

Logical operations and Kolmogorov complexity. II

We invistigate what is the minimal length of
a program mapping A to B and at the same time
mapping C to D (where A,B,C,D are binary strings). We prove that
it cannot be expressed
in terms of Kolmogorv complexity of A,B,C,D, their pairs (A,B), (A,C),
..., their ... more >>>

TR01-088 | 29th October 2001
Alexander Shen, Nikolay Vereshchagin

Logical operations and Kolmogorov complexity

We define Kolmogorov complexity of a set of strings as the minimal
Kolmogorov complexity of its element. Consider three logical
operations on sets going back to Kolmogorov
and Kleene:
(A OR B) is the direct sum of A,B,
(A AND B) is the cartesian product of A,B,
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TR01-087 | 29th October 2001
Bruno Durand, Alexander Shen, Nikolay Vereshchagin

Descriptive complexity of computable sequences

We study different notions of descriptive complexity of
computable sequences. Our main result states that if for almost all
n the Kolmogorov complexity of the n-prefix of an infinite
binary sequence x conditional to n
is less than m then there is a program of length
m^2+O(1) that for ... more >>>

TR01-086 | 29th October 2001
Nikolay Vereshchagin

Kolmogorov Complexity Conditional to Large Integers

Assume that for almost all n Kolmogorov complexity
of a string x conditional to n is less than m.
We prove that in this case
there is a program of size m+O(1) that given any sufficiently large
n outputs x.

more >>>

TR01-083 | 29th October 2001
Nikolay Vereshchagin

An enumerable undecidable set with low prefix complexity: a simplified proof

Revisions: 1

We present a simplified proof of Solovay-Calude-Coles theorem
stating that there is an enumerable undecidable set with the
following property: prefix
complexity of its initial segment of length n is bounded by prefix
complexity of n (up to an additive constant).

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TR00-035 | 6th June 2000
Nikolay Vereshchagin, Mikhail V. Vyugin

Independent minimum length programs to translate between given strings

A string $p$ is called a program to compute $y$ given $x$
if $U(p,x)=y$, where $U$ denotes universal programming language.
Kolmogorov complexity $K(y|x)$ of $y$ relative to $x$
is defined as minimum length of
a program to compute $y$ given $x$.
Let $K(x)$ denote $K(x|\text{empty string})$
(Kolmogorov complexity of $x$) ... more >>>

TR00-026 | 11th April 2000
Andrei Romashchenko, Alexander Shen, Nikolay Vereshchagin

Combinatorial Interpretation of Kolmogorov Complexity

The very first Kolmogorov's paper on algorithmic
information theory was entitled `Three approaches to the
definition of the quantity of information'. These three
approaches were called combinatorial, probabilistic and
algorithmic. Trying to establish formal connections
between combinatorial and algorithmic approaches, we
prove that any ... more >>>

TR99-014 | 30th May 1999
Alexander Razborov, Nikolay Vereshchagin

One Property of Cross-Intersecting Families

Assume that A, B are finite families of n-element sets.
We prove that there is an element that simultaneously
belongs to at least |A|/2n sets
in A and to at least |B|/2n sets in B. We use this result to prove
that for any inconsistent DNF's F,G with OR ... more >>>

TR97-054 | 17th November 1997
Ran Raz, Gábor Tardos, Oleg Verbitsky, Nikolay Vereshchagin

Arthur-Merlin Games in Boolean Decision Trees

It is well known that probabilistic boolean decision trees
cannot be much more powerful than deterministic ones (N.~Nisan, SIAM
Journal on Computing, 20(6):999--1007, 1991). Motivated by a question
if randomization can significantly speed up a nondeterministic
computation via a boolean decision tree, we address structural
properties of Arthur-Merlin games ... more >>>

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