A basic question in any computational model is how to reliably compute a given function when the inputs or intermediate computations are subject to noise at a constant rate. Ideally, one would like to use at most a constant factor more resources compared to the noise-free case. This question has ... more >>>

We study the set disjointness problem in the number-on-the-forehead model.

(i) We prove that $k$-party set disjointness has randomized and nondeterministic
communication complexity $\Omega(n/4^k)^{1/4}$ and Merlin-Arthur complexity $\Omega(n/4^k)^{1/8}.$
These bounds are close to tight. Previous lower bounds (2007-2008) for $k\geq3$ parties
were weaker than $n^{1/(k+1)}/2^{k^2}$ in all ... more >>>

In the gap Hamming distance problem, two parties must
determine whether their respective strings $x,y\in\{0,1\}^n$
are at Hamming distance less than $n/2-\sqrt n$ or greater
than $n/2+\sqrt n.$ In a recent tour de force, Chakrabarti and
Regev (STOC '11) proved the long-conjectured $\Omega(n)$ bound
on the randomized communication complexity ... more >>>

A strong direct product theorem (SDPT) states that solving $n$ instances of a problem requires $\Omega(n)$ times the resources for a single instance, even to achieve success probability $2^{-\Omega(n)}.$ We prove that quantum communication complexity obeys an SDPT whenever the communication lower bound for a single instance is proved by ... more >>>

We prove that NP$\ne$coNP and coNP$\nsubseteq$MA in the number-on-forehead model of multiparty communication complexity for up to $k=(1-\epsilon)\log n$ players, where $\epsilon>0$ is any constant. Specifically, we construct a function $F:(\zoon)^k\to\zoo$ with co-nondeterministic
complexity $O(\log n)$ and Merlin-Arthur
complexity $n^{\Omega(1)}$.
The problem was open for $k\geq3$.

The threshold degree of a function
$f\colon\{0,1\}^n\to\{-1,+1\}$ is the least degree of a
real polynomial $p$ with $f(x)\equiv\mathrm{sgn}\; p(x).$ We
prove that the intersection of two halfspaces on
$\{0,1\}^n$ has threshold degree $\Omega(n),$ which
matches the trivial upper bound and completely answers
a question due to Klivans (2002). The best ... more >>>

The threshold degree of a Boolean function
$f\colon\{0,1\}\to\{-1,+1\}$ is the least degree of a real
polynomial $p$ such $f(x)\equiv\mathrm{sgn}\; p(x).$ We
construct two halfspaces on $\{0,1\}^n$ whose intersection has
threshold degree $\Theta(\sqrt n),$ an exponential improvement on
previous lower bounds. This solves an open problem due to Klivans
(2002) and ... more >>>

Representations of Boolean functions by real polynomials
play an important role in complexity theory. Typically,
one is interested in the least degree of a polynomial
p(x_1,...,x_n) that approximates or sign-represents
a given Boolean function f(x_1,...,x_n). This article
surveys a new and growing body of work in communication
complexity that centers ... more >>>

The sign-rank of a matrix A=[A_{ij}] with +/-1 entries
is the least rank of a real matrix B=[B_{ij}] with A_{ij}B_{ij}>0
for all i,j. We obtain the first exponential lower bound on the
sign-rank of a function in AC^0. Namely, let
f(x,y)=\bigwedge_{i=1}^m\bigvee_{j=1}^{m^2} (x_{ij}\wedge y_{ij}).
We show that the matrix [f(x,y)]_{x,y} has ... more >>>

Let A_1,...,A_n be events in a probability space. The
approximate inclusion-exclusion problem, due to Linial and
Nisan (1990), is to estimate Pr[A_1 OR ... OR A_n] given
Pr[AND_{i\in S}A_i] for all |S|<=k. Kahn et al. (1996) solve
this problem optimally for each k. We study the following more
general question: ... more >>>

The sign-rank of a real matrix M is the least rank
of a matrix R in which every entry has the same sign as the
corresponding entry of M. We determine the sign-rank of every
matrix of the form M=[ D(|x AND y|) ]_{x,y}, where
D:{0,1,...,n}->{-1,+1} is given and x ... more >>>

In a breakthrough result, Razborov (2003) gave optimal
lower bounds on the communication complexity of every function f
of the form f(x,y)=D(|x AND y|) for some D:{0,1,...,n}->{0,1}, in
the bounded-error quantum model with and without prior entanglement.
This was proved by the _multidimensional_ discrepancy method. We
give an entirely different ... more >>>

We solve an open problem of Kushilevitz and Nisan
(1997) in communication complexity. Let $R_{eps}(f)$
and $D^{mu}_{eps}(f)$ denote the randomized and
$mu$-distributional communication complexities of
f, respectively ($eps$ a small constant). Yao's
well-known Minimax Principle states that
R_{eps}(f) = max_{mu} { D^{mu}_{eps}(f) }.
Kushilevitz and Nisan (1997) ask whether ... more >>>

We give the first representation-independent hardness results for
PAC learning intersections of halfspaces, a central concept class
in computational learning theory. Our hardness results are derived
from two public-key cryptosystems due to Regev, which are based on the
worst-case hardness of well-studied lattice problems. Specifically, we
prove that a polynomial-time ... more >>>