Let P be a probability distribution over a finite alphabet Omega^L with all L marginals equal. Let X^(1), ..., X^(L), where X^(j) = (X_1^(j), ..., X_n^(j)) be random vectors such that for every coordinate i in [n] the tuples (X_i^(1), ..., X_i^(L)) are i.i.d. according to P. The question we address is: does there exist a function c_P independent of n such that for every f: Omega^n -> [0, 1] with E[f(X^(1))] = m > 0 we have E[f(X^(1)) * ... * f(X^(n))] > c_P(m) > 0? We settle the question for L=2 and when L>2 and P has bounded correlation smaller than 1.

We propose a method to automatically derive hardware structures that perform a fixed linear permutation on streaming data. Linear permutations are permutations that map linearly the bit representation of the elements addresses. This set contains many of the most important permutations in media processing, communication, and other applications and includes perfect shuffles, stride permutations, and the bit reversal. Streaming means that the data to be permuted arrive as a sequence of chunks over several cycles. We solve this problem by mathematically decomposing a given permutation into a sequence of three permutations that are either temporal or spatial. The former are implemented as banks of RAM, the latter as switching networks. We prove optimality of our solution in terms of the number of switches in these networks.

We study generalisations of a simple, combinatorial proof of a Chernoff bound similar to the one by Impagliazzo and Kabanets (RANDOM, 2010). In particular, we prove a randomized version of the hitting property of expander random walks and use it to obtain an optimal expander random walk concentration bound settling a question asked by Impagliazzo and Kabanets. Next, we obtain an upper tail bound for polynomials with input variables in [0, 1] which are not necessarily independent, but obey a certain condition inspired by Impagliazzo and Kabanets. The resulting bound is applied by Holenstein and Sinha (FOCS, 2012) in the proof of a lower bound for the number of calls in a black-box construction of a pseudorandom generator from a one-way function. We also show that the same technique yields the upper tail bound for the number of copies of a fixed graph in an Erdös–Rényi random graph, matching the one given by Janson, Oleszkiewicz, and Rucinski (Israel J. Math, 2002).

Let p be a prime and k, t be positive integers. Given a quadratic equation Q(x1,x2,...,xn)=t mod p^k in n-variables; we present a polynomial time Las-Vegas algorithm that samples a uniformly random solution of the quadratic equation.

We show that a black-box construction of a pseudorandom generator from a one-way function needs to make Ω(n/log(n)) calls to the underlying one-way function. The bound even holds if the one-way function is guaranteed to be regular. In this case it matches the best known construction due to Gold Reich, Krawczyk, and Luby (SIAM J. Comp. 22, 1993), which uses O(n/log(n)) calls.

We initiate a study of when the value of mathematical relaxations such as linear and semi-definite programs for constraint satisfaction problems (CSPs) is approximately preserved when restricting the instance to a sub-instance induced by a small random subsample of the variables. Let C be a family of CSPs such as 3SAT, Max-Cut, etc., and let П be a mathematical program that is a relaxation for C, in the sense that for every instance P ∊ C, П(P) is a number in [0, 1] upper bounding the maximum fraction of satisfiable constraints of P. Loosely speaking, we say that subsampling holds for C and П if for every sufficiently dense instance P ∊ C and every ε > 0, if we let P′ be the instance obtained by restricting P to a sufficiently large constant number of variables, then П(P′) ∊ (1 ± ε)П(P). We say that weak subsampling holds if the above guarantee is replaced with П(P′) = 1 − Θ(γ) whenever П(P) = 1 − γ, where Θ hides only absolute constants. We obtain both positive and negative results, showing that: 1. Subsampling holds for the BasicLP and BasicSDP programs. BasicSDP is a variant of the semi-definite program considered by Raghavendra (2008), who showed it gives an optimal approximation factor for every constraint-satisfaction problem under the unique games conjecture. BasicLP is the linear programming analog of BasicSDP. 2. For tighter versions of BasicSDP obtained by adding additional constraints from the Lasserre hierarchy, weak subsampling holds for CSPs of unique games type. 3. There are non-unique CSPs for which even weak subsampling fails for the above tighter semi-definite programs. Also there are unique CSPs for which (even weak) subsampling fails for the Sherali-Adams linear programming hierarchy. As a corollary of our weak subsampling for strong semi-definite programs, we obtain a polynomial-time algorithm to certify that random geometric graphs (of the type considered by Feige and Schechtman, 2002) of max-cut value 1 − γ have a cut value at most 1 − γ/10. More generally, our results give an approach to obtaining average-case algorithms for CSPs using semi-definite programming hierarchies.

We consider the cryptographic problem of constructing an invertible random permutation from a public random function (i.e., which can be accessed by the adversary). This goal is formalized by the notion of indifferentiability of Maurer et al. (TCC 2004). This is the natural extension to the public setting of the well-studied problem of building random permutations from random functions, which was first solved by Luby and Rackoff (Siam J. Comput., '88) using the so-called Feistel construction. The most important implication of such a construction is the equivalence of the random oracle model (Bellare and Rogaway, CCS '93) and the ideal cipher model, which is typically used in the analysis of several constructions in symmetric cryptography.

Smooth entropies characterize basic information-theoretic properties of random variables, such as the number of bits required to store them or the amount of uniform randomness that can be extracted from them (possibly with respect to side information). In this paper, explicit and almost tight bounds on the smooth entropies of n-fold product distributions, Pn, are derived. These bounds are expressed in terms of the Shannon entropy of a single distribution, P . The results can be seen as an extension of the asymptotic equipartition property (AEP).

The design of optimal auctions focuses on ways to negotiate with the bidders for eliciting relevant information that they hold. Sometimes, however, decisions should be made very quickly, and the auctioneer cannot allow a costly iterative procedure of negotiation or waiting for bidders to determine their exact valuation. One solution that has been used in practice is to post prices for the bidders, without collecting any information from the bidders, and ask for their immediate take-it-or-leave-it response.

Consider a game where a refereed chooses (x,y) according to a publiclyknown distribution PXY, sends x to Alice, and y to Bob. Withoutcommunicating with each other, Alice responds with a value "a" and Bobresponds with a value "b". Alice and Bob jointly win if a publiclyknown predicate Q(x,y,a,b) holds. Let such a game be given and assume that the maximum probabilitythat Alice and Bob can win is v<1. Raz (SIAM J. Comput. 27, 1998)shows that if the game is repeated n times in parallel, then the probability that Alice and Bob win all games simultaneously is at most v'(n/log(s)), where s is the maximal number of possible responses from Alice and Bob in the initial game, and v' is a constant depending only on v. In this work, we simplify Raz's proof in various ways and thus shorten it significantly. Further we study the case where Alice and Bob are not restricted to local computations and can use any strategy which does not imply communication among them.

Assume that Alice and Bob, given an authentic channel, have a protocol where they end up with a bit SA and SB, respectively, such that with probability 1+ε/2 these bits are equal. Further assume that conditioned on the event SA =n SB no polynomial time bounded algorithm can predict the bit better than with probability 1-δ/2. Is it possible to obtain key agreement from such a primitive? We show that for constant δ and ε the answer is yes if and only if δ > 1-ε/1+ε, both for uniform and non-uniform adversaries.The main computational technique used in this paper is a strengthening of Impagliazzo's hard-core lemma to the uniform case and to a set size parameter which is tight (i.e., twice the original size). This may be of independent interest.

It is well-known that n players, connected only by pairwise secure channels, can achieve Byzantine agreement only if the number t of cheaters satisfies t < n/3, even with respect to computational security. However, for many applications it is sufficient to achieve detectable broadcast. With this primitive, broadcast is only guaranteed when all players are non-faulty ("honest"), but all non-faulty players always reach agreement on whether broadcast was achieved or not. We show that detectable broadcast can be achieved regardless of the number of faulty players (i.e., for all t < n). We give a protocol which is unconditionally secure, as well as two more efficient protocols which are secure with respect to computational assumptions, and the existence of quantum channels, respectively.These protocols allow for secure multi-party computation tolerating any t < n, assuming only pairwise authenticated channels. Moreover, they allow for the setup of public-key infrastructures that are consistent among all participants --- using neither a trusted party nor broadcast channels.Finally, we show that it is not even necessary for players to begin the protocol at the same time step. We give a "detectable Firing Squad" protocol which can be initiated by a single user at any time and such that either all honest players end up with synchronized clocks, or all honest players abort.