We propose an information-theoretic approach to proving
lower bounds on the size of branching programs (b.p.). The argument
is based on Kraft-McMillan type inequalities for the average amount of
uncertainty about (or entropy of) a given input during various
stages of the computation.

We ... more >>>

The worst-case complexity of an implementation of Quicksort depends
on the random number generator that is used to select the pivot
elements. In this paper we estimate the expected number of
comparisons of Quicksort as a function in the entropy of the random
source. We give upper and lower bounds ... more >>>

We investigate the complexity of the following computational problem:

Polynomial Entropy Approximation (PEA):
Given a low-degree polynomial mapping
$p : F^n\rightarrow F^m$, where $F$ is a finite field, approximate the output entropy
$H(p(U_n))$, where $U_n$ is the uniform distribution on $F^n$ and $H$ may be any of several entropy measures.

... more >>>

We provide a characterization of pseudoentropy in terms of hardness of sampling: Let $(X,B)$ be jointly distributed random variables such that $B$ takes values in a polynomial-sized set. We show that $B$ is computationally indistinguishable from a random variable of higher Shannon entropy given $X$ if and only if there ... more >>>