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Electronic Colloquium on Computational Complexity

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All reports by Author William Gasarch:

TR10-139 | 17th September 2010
Eric Allender, Luke Friedman, William Gasarch

Limits on the Computational Power of Random Strings

Revisions: 1

Let C(x) and K(x) denote plain and prefix Kolmogorov complexity, respectively, and let R_C and R_K denote the sets of strings that are ``random'' according to these measures; both R_K and R_C are undecidable. Earlier work has shown that every set in NEXP is in NP relative to both R_K ... more >>>

TR10-138 | 17th September 2010
Eric Allender, Luke Friedman, William Gasarch

Exposition of the Muchnik-Positselsky Construction of a Prefix Free Entropy Function that is not Complete under Truth-Table Reductions

In this paper we give an exposition of a theorem by Muchnik and Positselsky, showing that there is a universal prefix Turing machine U, with the property that there is no truth-table reduction from the halting problem to the set {(x,i) : there is a description d of length at ... more >>>

TR08-053 | 27th March 2008
Stephen A. Fenner, William Gasarch, Brian Postow

The complexity of learning SUBSEQ(A)

Higman showed that if A is *any* language then SUBSEQ(A)
is regular, where SUBSEQ(A) is the language of all
subsequences of strings in A. (The result we attribute
to Higman is actually an easy consequence of his work.)
Let s_1, s_2, s_3, ... more >>>

TR04-120 | 22nd November 2004
Andris Ambainis, William Gasarch, Aravind Srinivasan, Andrey Utis

Lower bounds on the Deterministic and Quantum Communication Complexity of HAM_n^a

Alice and Bob want to know if two strings of length $n$ are
almost equal. That is, do they differ on at most $a$ bits?
Let $0\le a\le n-1$.
We show that any deterministic protocol, as well as any
error-free quantum protocol ($C^*$ version), for this problem
requires at ... more >>>

TR03-087 | 10th December 2003
Richard Beigel, Lance Fortnow, William Gasarch

A Nearly Tight Bound for Private Information Retrieval Protocols

Comments: 1

We show that any 1-round 2-server Private Information
Retrieval Protocol where the answers are 1-bit long must ask questions
that are at least $n-2$ bits long, which is nearly equal to the known
$n-1$ upper bound. This improves upon the approximately $0.25n$ lower
bound of Kerenidis and de Wolf while ... more >>>

TR01-019 | 2nd March 2001
Andris Ambainis, Harry Buhrman, William Gasarch, Bala Kalyansundaram, Leen Torenvliet

The Communication Complexity of Enumeration, Elimination, and Selection

Normally, communication Complexity deals with how many bits
Alice and Bob need to exchange to compute f(x,y)
(Alice has x, Bob has y). We look at what happens if
Alice has x_1,x_2,...,x_n and Bob has y_1,...,y_n
and they want to compute f(x_1,y_1)... f(x_n,y_n).
THis seems hard. We look at various ... more >>>

TR00-024 | 16th May 2000
Amihood Amir, Richard Beigel, William Gasarch

Some Connections between Bounded Query Classes and Non-Uniform Complexity

Let A(x) be the characteristic function of A. Consider the function
F_k^A(x_1,...,x_k) = A(x_1)...A(x_k). We show that if F_k^A can be
computed with fewer than k queries to some set X, then A can be
computed by polynomial size circuits. A generalization of this result
has applications to bounded query ... more >>>

TR96-051 | 1st October 1996
Richard Beigel, William Gasarch, Ming Li, Louxin Zhang

Addition in $\log_2{n}$ + O(1)$ Steps on Average: A Simple Analysis

We demonstrate the use of Kolmogorov complexity in average case
analysis of algorithms through a classical example: adding two $n$-bit
numbers in $\ceiling{\log_2{n}}+2$ steps on average. We simplify the
analysis of Burks, Goldstine, and von Neumann in 1946 and
(in more complete forms) of Briley and of Schay.

more >>>

TR95-036 | 5th July 1995
Richard Beigel, William Gasarch, Efim Kinber

Frequency Computation and Bounded Queries

For a set A and a number n let F_n^A(x_1,...,x_n) =
A(x_1)\cdots A(x_n). We study how hard it is to approximate this
function in terms of the number of queries required. For a general
set A we have exact bounds that depend on functions from coding
theory. These are applied ... more >>>

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