#### The complexity of finite-valued CSPs

Thapper, Johan ; Zivny, StanislavWe construct a 1-round delegation scheme (i.e., argument-system) for every language computable in time t=t(n), where the running time of the prover is poly(t) and the running time of the verifier is n*polylog(t). In particular, for every language in P we obtain a delegation scheme with almost linear time verification. Our construction relies on the existence of a computational sub-exponentially secure private information retrieval (PIR) scheme. The proof exploits a curious connection between the problem of computation delegation and the model of multi-prover interactive proofs that are sound against no-signaling (cheating) strategies, a model that was studied in the context of multi-prover interactive proofs with provers that share quantum entanglement, and is motivated by the physical principle that information cannot travel faster than light. For any language computable in time t=t(n), we construct a multi-prover interactive proof (MIP) that is sound against no-signaling strategies, where the running time of the provers is poly(t), the number of provers is polylog(t), and the running time of the verifier is n*polylog(t). In particular, this shows that the class of languages that have polynomial-time MIPs that are sound against no-signaling strategies, is exactly EXP. Previously, this class was only known to contain PSPACE. To convert our MIP into a 1-round delegation scheme, we use the method suggested by Aiello et-al (ICALP, 2000), which makes use of a PIR scheme. This method lacked a proof of security. We prove that this method is secure assuming the underlying MIP is secure against no-signaling provers.

We show an exponential gap between communication complexity and information complexity, by giving an explicit example of a partial boolean function with information complexity $\leq O(k)$, and distributional communication complexity $\geq 2^k$. This shows that a communication protocol cannot always be compressed to its internal information. By a result of Braverman, our gap is the largest possible. By a result of Braverman and Rao, our example shows a gap between communication complexity and amortized communication complexity, implying that a tight direct sum result for distributional communication complexity cannot hold, answering a long standing open problem. Another (conceptual) contribution of our work is the relative discrepancy method, a new rectangle-based method for proving communication complexity lower bounds for boolean functions, powerful enough to separate information complexity and communication complexity.

Randomness is a vital resource for modern day information processing, especially for cryptography. A wide range of applications critically rely on abundant, high quality random numbers generated securely. Here we show how to expand a random seed at an exponential rate without trusting the underlying quantum devices. Our approach is secure against the most general adversaries, and has the following new features: cryptographic level of security, tolerating a constant level of imprecision in the devices, requiring only a unit size quantum memory per device component for the honest implementation, and allowing a large natural class of constructions for the protocol. In conjunct with a recent work by Chung, Shi and Wu, it also leads to robust unbounded expansion using just 2 multi-part devices. When adapted for distributing cryptographic keys, our method achieves, for the first time, exponential expansion combined with cryptographic security and noise tolerance. The proof proceeds by showing that the Renyi divergence of the outputs of the protocol (for a specific bounding operator) decreases linearly as the protocol iterates. At the heart of the proof are a new uncertainty principle on quantum measurements, and a method for simulating trusted measurements with untrusted devices.

#### Constant rate PCPs for CircuitSat with sublinear query complexity

Ben-Sasson, Eli ; Kaplan, Yohay ; Kopparty, Swastik ; Meir, Or ; Stichtenoth, HenningWe prove super-polynomial lower bounds on the size of linear programming relaxations for approximation versions of constraint satisfaction problems. We show that for these problems, polynomial-sized linear programs are exactly as powerful as programs arising from a constant number of rounds of the Sherali-Adams hierarchy. In particular, any polynomial-sized linear program for Max Cut has an integrality gap of 1/2 and any such linear program for Max 3-Sat has an integrality gap of 7/8.

We consider coding schemes for computationally bounded channels, which can introduce an arbitrary set of errors as long as (a) the fraction of errors is bounded with high probability by a parameter p and (b) the process which adds the errors can be described by a sufficiently simple circuit. Codes for such channel models are attractive since, like codes for standard adversarial errors, they can handle channels whose true behavior is unknown or varying over time. For two classes of channels, we provide explicit, efficiently encodable/decodable codes of optimal rate where only inefficiently decodable codes were previously known. In each case, we provide one en- coder/decoder that works for every channel in the class. The encoders are randomized, and probabilities are taken over the (local, unknown to the decoder) coins of the encoder and those of the channel. Unique decoding for additive errors: We give the first construction of a polynomial-time encod- able/decodable code for additive (a.k.a. oblivious) channels that achieve the Shannon capacity 1 H(p). These are channels which add an arbitrary error vector e {0, 1}^N of weight at most pN to the transmitted word; the vector e can depend on the code but not on the particular transmitted word. Such channels capture binary symmetric errors and burst errors as special cases. List-decoding for polynomial-time channels: For every constant c > 0, we give a Monte Carlo construction of an code with optimal rate (arbitrarily close to 1 H(p)) that efficiently recovers a short list containing the correct message with high probability for channels describable by circuits of size at most N^c. We are not aware of any channel models considered in the information theory literature, other than purely adversarial channels, which require more than linear-size circuits to implement. We justify the relaxation to list-decoding with an impossibility result showing that, in a large range of parameters (p > 1/4), codes that are uniquely decodable for a modest class of channels (online, memoryless, nonuniform channels) cannot have positive rate.

A 2-server Private Information Retrieval (PIR) scheme allows a user to retrieve the $i$th bit of an $n$-bit database replicated among two non-communicating servers, while not revealing any information about $i$ to either server. In this work we construct a 2-server PIR scheme with total communication cost $n^{O\left(\sqrt{\frac{\log\log n}{\log n}}\right)}$. This improves over current 2-server protocols which all require $\Omega(n^{1/3})$ communication. Our construction circumvents the $n^{1/3}$ barrier of \cite{RazborovY06} which holds for the restricted model of bilinear group-based schemes (covering all previous 2-server schemes). The improvement comes from reducing the number of servers in existing protocols, based on Matching Vector Codes, from 3 or 4 servers to 2. This is achieved by viewing these protocols in an algebraic way (using polynomial interpolation) and extending them using partial derivatives.

The Local Lemma is a fundamental tool of probabilistic combinatorics and theoretical computer science, yet there are hardly any natural problems known where it provides an asymptotically tight answer. The main theme of our paper is to identify several of these problems, among them a couple of widely studied extremal functions related to certain restricted versions of the k-SAT problem, where the Local Lemma does give essentially optimal answers. As our main contribution, we construct unsatisfiable k-CNF formulas where every clause has k distinct literals and every variable appears in at most (2/e + o(1))*2^k/k clauses. The Lopsided Local Lemma, applied with an assignment of random values according to counterintuitive probabilities, shows that this is asymptotically best possible. The determination of this extremal function is particularly important as it represents the value where the corresponding k-SAT problem exhibits a complexity hardness jump: from having every instance being a YES-instance it becomes NP-hard just by allowing each variable to occur in one more clause. The construction of our unsatisfiable CNF-formulas is based on the binary tree approach of [Gebauer, 2012] and thus the constructed formulas are in the class MU(1) of minimal unsatisfiable formulas having one more clauses than variables. The main novelty of our approach here comes in setting up an appropriate continuous approximation of the problem. This leads us to a differential equation, the solution of which we are able to estimate. The asymptotically optimal binary trees are then obtained through a discretization of this solution. The importance of the binary trees constructed is also underlined by their appearance in many other scenarios. In particular, they give asymptotically precise answers for seemingly unrelated problems like the European Tenure Game introduced by Doerr, and a search problem allowing a limited number of consecutive lies. As yet another consequence we slightly improve the best known bounds on the maximum degree and maximum edge-degree of a k-uniform Makers win hypergraph in the Neighborhood Conjecture of Beck.

Let M = (E,I) be a matroid and let S={S_1, ... , S_t} be a family of subsets
of E of size p. A subfamily ~~ subset of S is q-representative for S if for
every set Y subset of E of size at most q, if there is a set X in S disjoint
from Y with X \cup Y in I, then there is a set ~~~~ disjoint from Y
with ~~

In a parameterized problem, every instance $I$ comes with a positive integer $k$. The problem is said to admit a {\em polynomial kernel} if, in polynomial time, one can reduce the size of the instance $I$ to a polynomial in $k$, while preserving the answer. In this work we give two meta-theorems on kernelzation. The first theorem says that all problems expressible in Counting Monadic Second Order Logic and satisfying a compactness property admit a polynomial kernel on graphs of bounded genus. Our second result is that all problems that have finite integer index and satisfy a weaker compactness condition admit a linear kernel on graphs of bounded genus. These theorems unify and extend { all} previously known kernelization results for planar graph problems. Combining our theorems with the Erd\H{o}s-P\'{o}sa property we obtain various new results on linear kernels for a number of packing and covering problems.

#### Optimal Mechanisms for Combinatorial Auctions and Combinatorial Public Projects via Convex Rounding

Dughmi, Shaddin ; Roughgarden, Tim ; Yan, QiqiIn the Edge-Disjoint Paths with Congestion problem (EDPwC), we are given an undirected $n$-vertex graph $G$, a collection $M=\{(s_1,t_1),\ldots,(s_k,t_k)\}$ of demand pairs and an integer $c$. The goal is to connect the maximum possible number of the demand pairs by paths, so that the maximum edge congestion - the number of paths sharing any edge - is bounded by $c$. When the maximum allowed congestion is $c=1$, this is the classical Edge-Disjoint Paths problem (EDP). The best current approximation algorithm for EDP achieves an $O(\sqrt n)$-approximation, by rounding the standard multi-commodity flow relaxation of the problem. This matches the $\Omega(\sqrt n)$ lower bound on the integrality gap of this relaxation. We show an $O(poly\log k)$-approximation algorithm for EDPwC with congestion $c=2$, by rounding the same multi-commodity flow relaxation. This gives the best possible congestion for a sub-polynomial approximation of EDPwC via this relaxation. Our results are also close to optimal in terms of the number of pairs routed, since EDPwC is known to be hard to approximate to within a factor of $\tilde{\Omega}\left((\log n)^{1/(c+1)}\right )$ for any constant congestion $c$. Prior to our work, the best approximation factor for EDPwC with congestion $2$ was $\tilde O(n^{3/7})$, and the best algorithm achieving a polylogarithmic approximation required congestion $14$.

Lock-free concurrent algorithms guarantee that \emph{some} concurrent operation will always make progress in a finite number of steps. Yet programmers prefer to treat concurrent code as if it were \emph{wait-free}, guaranteeing that \emph{all} operations always make progress. Unfortunately, designing wait-free algorithms is generally a very complex task, and the resulting algorithms are not always efficient. While obtaining efficient wait-free algorithms has been a long-time goal for the theory community, most non-blocking commercial code is only lock-free. This paper suggests a simple solution to this problem. We show that, for a large class of lock-free algorithms, under scheduling conditions which approximate those found in commercial hardware architectures, lock-free algorithms behave as if they are wait-free. In other words, programmers can keep on designing simple lock-free algorithms instead of complex wait-free ones, and in practice, they will get wait-free progress. Our main contribution is a new way of analyzing a general class of lock-free algorithms under a \emph{stochastic scheduler}. Our analysis relates the individual performance of processes with the global performance of the system using \emph{Markov chain lifting} between a complex per-process chain and a simpler system progress chain. We show that lock-free algorithms are not only wait-free with probability $1$, but that in fact a general subset of lock-free algorithms can be closely bounded in terms of the average number of steps required until an operation completes. To the best of our knowledge, this is the first attempt to analyze progress conditions, typically stated in relation to a worst case adversary, in a stochastic model capturing their expected asymptotic behavior.

*Any*Constant Bias Implies One-Way Functions

*Berman, Itay ; Haitner, Iftach ; Tentes, Aris*

*
*We show that the existence of a coin-flipping protocol safe against *any* non-trivial constant bias (e.g., .499) implies the existence of one-way functions. This improves upon a recent result of Haitner and Omri [FOCS '11], who proved this implication for protocols with bias (2 - 1)/2 - o(1) H .207. Unlike the result of Haitner and Omri, our result also holds for *weak* coin-flipping protocols.

*
Deterministic (Delta + 1)-coloring in sublinear (in Delta) time in static, dynamic and faulty networks Barenboim, Leonid
Query Complexity of Approximate Nash Equilibria Babichenko, Yakov
*In the distributed message passing model a communication network is represented by an n-vertex graph G = (V,E) of maximum degree \Delta. Computation proceeds in discrete synchronous rounds consisting of sending and receiving messages and performing local computations. The running time of an algorithm is the number of rounds it requires. In the {static setting} the network remains unchanged throughout the entire execution. In the {dynamic setting} the topology of the network changes, and a new solution has to be computed after each change. In the {faulty setting} the network is static, but some vertices or edges may lose the computed solution as a result of faults. The goal of an algorithm in this setting is fixing the solution. The problems of (\Delta + 1)-vertex-coloring and (2\Delta - 1)-edge-coloring are among the most important and intensively studied problems in distributed computing. Despite a very intensive research in the last 30 years, no deterministic algorithms for these problems with sublinear (in \Delta) time have been known so far. Moreover, for more restricted scenarios and some related problems there are lower bounds of \Omega(\Delta). The question of the possibility to devise algorithms that overcome this challenging barrier is one of the most fundamental questions in distributed symmetry breaking. In this paper we settle this question for (\Delta + 1)-vertex-coloring and (2\Delta - 1)-edge-coloring by devising deterministic algorithms that require O(\Delta^{3/4} \log \Delta + \log^* n) time in the static, dynamic and faulty settings. (The term \log^* n is unavoidable in view of the lower bound of Linial.) Moreover, for (1 + o(1))Delta-vertex-coloring and (2 + o(1))Delta-edge-coloring we devise algorithms with ~O(\sqrt{\Delta} + \log^* n) deterministic time. This is roughly a quadratic improvement comparing to the state-of-the-art that requires O(\Delta + \log^* n) time. Our results are actually more general than that since they apply also to a variant of the list-coloring problem that generalizes ordinary coloring. Our results are obtained using a novel technique for coloring partially-colored graphs (also known as {fixing}). We partition the uncolored parts into a small number of subgraphs with certain helpful properties. Then we color these subgraphs gradually using a technique that employs {constructions of polynomials} in a novel way. Our construction is inspired by the algorithm of Linial for ordinary O(\Delta^2)-coloring. However, it is a more sophisticated construction that differs from that of Linial in several important respects. These new insights in using systems of polynomials allow us to significantly speed up the O(\Delta)-coloring algorithms. Moreover, they allow us to devise algorithms with the same running time also in the more complicated settings of dynamic and faulty networks.

We study the query complexity of approximate notions of Nash equilibrium in games with a large number of players n. Our main result states that for n-player binary-action games and for constant µ, the query complexity of an µ-well-supported Nash equilibrium is exponential in n. As a consequences of this result, we get an exponential lower bound on the rate of convergence of adaptive dynamics to approximate Nash equilibria.