It was shown some years ago that the computation time for many important
Boolean functions of n arguments on concurrent-read exclusive-write
parallel random-access machines
(CREW PRAMs) of unlimited size is at least f(n) = 0.72 log n.
On the other hand, it is known ... more >>>

The paper analyzes in terms of polynomial time many-one reductions
the computational complexity of several natural equivalence
relations on Boolean functions which derive from replacing
variables by expressions. Most of these computational problems
turn out to be between co-NP and Sigma^p_2.

Branching programs (b.p.'s) or decision diagrams are a general
graph-based model of sequential computation. B.p.'s of polynomial
size are a nonuniform counterpart of LOG. Lower bounds for
different kinds of restricted b.p.'s are intensively investigated.
An important restriction are so called 1-b.p.'s, where each
computation reads each input bit at ... more >>>

We introduce a model of a {\em randomized branching program}
in a natural way similar to the definition of a randomized circuit.
We exhibit an explicit boolean function
$f_{n}:\{0,1\}^{n}\to\{0,1\}$ for which we prove that:

1) $f_{n}$ can be computed by a polynomial size randomized
ordered read-once ... more >>>

We prove an exponential lower bound ($2^{\Omega(n/\log n)}$) on the
size of any randomized ordered read-once branching program
computing integer multiplication. Our proof depends on proving
a new lower bound on Yao's randomized one-way communication
complexity of certain boolean functions. It generalizes to some
other ... more >>>

We survey some upper and lower bounds established recently on
the sizes of randomized branching programs computing explicit
boolean functions. In particular, we display boolean
functions on which randomized read-once ordered branching
programs are exponentially more powerful than deterministic
or nondeterministic read-$k$-times branching programs for ... more >>>

We prove that the error-free (Las Vegas) randomized OBDDs
are computationally equivalent to the deterministic OBDDs.
In contrast, it is known the same is not true for the
Las Vegas read-once branching programs.

Ordered binary decision diagrams (OBDDs) are well established tools to
represent Boolean functions. There are a lot of results concerning
different types of generalizations of OBDDs. The same time, the power
of the most general form of OBDD, namely probabilistic (without bounded
error) OBDDs, is not studied enough. In ... more >>>

We establish a lower bound of $\Omega{(\sqrt{n})}$ on the bounded-error quantum query complexity of read-once Boolean functions, providing evidence for the conjecture that $\Omega(\sqrt{D(f)})$ is a lower bound for all Boolean functions.Our technique extends a result of Ambainis, based on the idea that successful computation of a function requires ``decoherence'' ... more >>>

We study deterministic one-way communication complexity
of functions with Hankel communication matrices.
Some structural properties of such matrices are established
and applied to the one-way two-party communication complexity
of symmetric Boolean functions.
It is shown that the number of required communication bits
does not depend on ... more >>>

We continue the study of the degree of polynomials representing threshold functions modulo 6 initiated by Barrington, Beigel and Rudich. We use the framework established by the authors relating representations by symmetric polynomials to simultaneous protocols. We show that proving bounds on the degree of Threshold functions is equivalent to ... more >>>

It is known that a k-term DNF can have at most 2^k ? 1 prime implicants and this bound is sharp. We determine all k-term DNF having the maximal number of prime implicants. It is shown that a DNF is maximal if and only if it corresponds to a non-repeating ... more >>>

Implicit algorithms work on their input's characteristic functions and should solve problems heuristically by as few and as efficient functional operations as possible. Together with an appropriate data structure to represent the characteristic functions they yield heuristics which are successfully applied in numerous areas. It is known that implicit algorithms ... more >>>

We give an algorithm that with high probability properly learns random monotone t(n)-term
DNF under the uniform distribution on the Boolean cube {0, 1}^n. For any polynomially bounded function t(n) <= poly(n) the algorithm runs in time poly(n, 1/eps) and with high probability outputs an eps accurate monotone DNF ... more >>>

Given a boolean function, let epsilon_M(f) denote the smallest distance between f and a monotone function on {0,1}^n. Let delta_M(f) denote the fraction of hypercube edges where f violates monotonicity. We give an alternative proof of the tight bound: delta_M(f) >= 2/n eps_M(f) for any boolean function f. This was ... more >>>

Every Boolean function on $n$ variables can be expressed as a unique multivariate polynomial modulo $p$ for every prime $p$. In this work, we study how the degree of a function in one characteristic affects its complexity in other characteristics. We establish the following general principle: functions with low degree ... more >>>

Call a function $f: \mathbb{F}_2^n \to \{0,1\}$ odd-cycle-free if there are no $x_1, \dots, x_k \in \mathbb{F}_2^n$ with $k$ an odd integer such that $f(x_1) = \cdots = f(x_k) = 1$ and $x_1 + \cdots + x_k = 0$. We show that one can distinguish odd-cycle-free functions from those $\epsilon$-far ... more >>>

In this note we give a new separation between sensitivity and block sensitivity of Boolean functions: $bs(f)=\frac{2}{3}s(f)^2-\frac{1}{3}s(f)$.