The method of obtaining lower bounds on the complexity
of Boolean functions for nondeterministic branching programs
is proposed.
A nonlinear lower bound on the complexity of characteristic
functions of Reed--Muller codes for nondeterministic
branching programs is obtained.

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We study the proper learnability of axis parallel concept classes
in the PAC learning model and in the exact learning model with
membership and equivalence queries. These classes include union of boxes,
DNF, decision trees and multivariate polynomials.

For the {\it constant} dimensional axis parallel concepts $C$
we ... more >>>

In this paper we present some new results on the approximate parallel
construction of Huffman codes. Our algorithm achieves linear work
and logarithmic time, provided that the initial set of elements
is sorted. This is the first parallel algorithm for that problem
with the optimal time and ... more >>>