A family of Boolean circuits $\{C_n\}_{n\geq 0}$ is called \emph{$\gamma(n)$-weakly uniform} if
there is a polynomial-time algorithm for deciding the direct-connection language of every $C_n$,
given \emph{advice} of size $\gamma(n)$. This is a relaxation of the usual notion of uniformity, which allows one
to interpolate between complete uniformity (when $\gamma(n)=0$) ... more >>>

The Valiant-Vazirani Isolation Lemma [TCS, vol. 47, pp. 85--93, 1986] provides an efficient procedure for isolating a satisfying assignment of a given satisfiable circuit: given a Boolean circuit $C$ on $n$ input variables, the procedure outputs a new circuit $C'$ on the same $n$ input variables with the property that ... more >>>

We give a simple combinatorial proof of the Chernoff-Hoeffding concentration bound~\cite{Chernoff, Hof63}, which says that the sum of independent $\{0,1\}$-valued random variables is highly concentrated around the expected value. Unlike the standard proofs,
our proof does not use the method of higher moments, but rather uses a simple and ... more >>>

The “direct product code” of a function f gives its values on all k-tuples (f(x1), . . . , f(xk)).
This basic construct underlies “hardness amplification” in cryptography, circuit complexity and
PCPs. Goldreich and Safra [GS00] pioneered its local testing and its PCP application. A recent
result by Dinur and ... more >>>

The classical Direct-Product Theorem for circuits says
that if a Boolean function $f:\{0,1\}^n\to\{0,1\}$ is somewhat hard
to compute on average by small circuits, then the corresponding
$k$-wise direct product function
$f^k(x_1,\dots,x_k)=(f(x_1),\dots,f(x_k))$ (where each
$x_i\in\{0,1\}^n$) is significantly harder to compute on average by
slightly smaller ... more >>>

For any given Boolean formula $\phi(x_1,\dots,x_n)$, one can
efficiently construct (using \emph{arithmetization}) a low-degree
polynomial $p(x_1,\dots,x_n)$ that agrees with $\phi$ over all
points in the Boolean cube $\{0,1\}^n$; the constructed polynomial
$p$ can be interpreted as a polynomial over an arbitrary field
$\mathbb{F}$. The problem ... more >>>

We consider the problem of amplifying uniform average-case hardness
of languages in $\NP$, where hardness is with respect to $\BPP$
algorithms. We introduce the notion of \emph{monotone}
error-correcting codes, and show that hardness amplification for
$\NP$ is essentially equivalent to constructing efficiently
\emph{locally} encodable and \emph{locally} list-decodable monotone
codes. The ... more >>>

We prove a version of the derandomized Direct Product Lemma for
deterministic space-bounded algorithms. Suppose a Boolean function
$g:\{0,1\}^n\to\{0,1\}$ cannot be computed on more than $1-\delta$
fraction of inputs by any deterministic time $T$ and space $S$
algorithm, where $\delta\leq 1/t$ for some $t$. Then, for $t$-step
walks $w=(v_1,\dots, v_t)$ ... more >>>

We show that derandomizing Polynomial Identity Testing is,
essentially, equivalent to proving circuit lower bounds for
NEXP. More precisely, we prove that if one can test in polynomial
time (or, even, nondeterministic subexponential time, infinitely
often) whether a given arithmetic circuit over integers computes an
identically zero polynomial, then either ... more >>>

This survey focuses on the recent (after 1998) developments in
the area of derandomization, with the emphasis on the derandomization of
time-bounded randomized complexity classes.

We consider a class, denoted APP, of real-valued functions
f:{0,1}^n\rightarrow [0,1] such that f can be approximated, to
within any epsilon>0, by a probabilistic Turing machine running in
time poly(n,1/epsilon). We argue that APP can be viewed as a
generalization of BPP, and show that APP contains a natural
complete ... more >>>

We study the complexity of the circuit minimization problem:
given the truth table of a Boolean function f and a parameter s, decide
whether f can be realized by a Boolean circuit of size at most s. We argue
why this problem is unlikely to be in P (or ... more >>>

Andreev et al.~\cite{ABCR97} give constructions of Boolean
functions (computable by polynomial-size circuits) that require large
read-once branching program (1-b.p.'s): a function in P that requires
1-b.p. of size at least $2^{n-\polylog(n)}$, a function in quasipolynomial
time that requires 1-b.p. of size at least $2^{n-O(\log n)}$, and a
function in LINSPACE ... more >>>