Minimum Manhattan Network Problem in Normed Planes with Polygonal Balls: A Factor 2.5 Approximation Algorithm

Let ${\mathcal{B}}$ be a centrally symmetric convex polygon of ?² and ‖p?q‖ be the distance between two points p,q∈?² in the normed plane whose unit ball is ${\mathcal{B}}$ . For a set T of n points (terminals) in ?², a ${\mathcal{B}}$ -network on T is a network N(T)=(V,E) with the property that its edges are parallel to the directions of ${\mathcal{B}}$ and for every pair of terminals t _i and t _j , the network N(T) contains a shortest ${\mathcal{B}}$ -path between them, i.e., a path of length ‖t _i ?t _j ‖. A minimum ${\mathcal{B}}$ -network on T is a ${\mathcal{B}}$ -network of minimum possible length. The problem of finding minimum ${\mathcal{B}}$ -networks has been introduced by Gudmundsson, Levcopoulos, and Narasimhan (APPROX’99) in the case when the unit ball ${\mathcal{B}}$ is a square (and hence the distance ‖p?q‖ is the l ₁ or the l _∞-distance between p and q) and it has been shown recently by Chin, Guo, and Sun (Symposium on Computational Geometry, pp. 393–402, 2009) to be strongly NP-complete. Several approximation algorithms (with factors 8, 4, 3, and 2) for the minimum Manhattan problem are known. In this paper, we propose a factor 2.5 approximation algorithm for the minimum ${\mathcal{B}}$ -network problem. The algorithm employs a simplified version of the strip-staircase decomposition proposed in our paper (Chepoi et al. in Theor. Comput. Sci. 390:56–69, 2008, and APPROX-RANDOM, pp. 40–51, 2005) and subsequently used in other factor 2 approximation algorithms for the minimum Manhattan problem.     

Delayed theory combination vs. Nelson-Oppen for satisfiability modulo theories: a comparative analysis

Most state-of-the-art approaches for Satisfiability Modulo Theories $(SMT(\mathcal{T}))$ rely on the integration between a SAT solver and a decision procedure for sets of literals in the background theory $\mathcal{T} (\mathcal{T}{\text {-}}solver)$ . Often $\mathcal{T}$ is the combination $\mathcal{T}_1 \cup \mathcal{T}_2$ of two (or more) simpler theories $(SMT(\mathcal{T}_1 \cup \mathcal{T}_2))$ , s.t. the specific ${\mathcal{T}_i}{\text {-}}solvers$ must be combined. Up to a few years ago, the standard approach to $SMT(\mathcal{T}_1 \cup \mathcal{T}_2)$ was to integrate the SAT solver with one combined $\mathcal{T}_1 \cup \mathcal{T}_2{\text {-}}solver$ , obtained from two distinct ${\mathcal{T}_i}{\text {-}}solvers$ by means of evolutions of Nelson and Oppen’s (NO) combination procedure, in which the ${\mathcal{T}_i}{\text {-}}solvers$ deduce and exchange interface equalities. Nowadays many state-of-the-art SMT solvers use evolutions of a more recent $SMT(\mathcal{T}_1 \cup \mathcal{T}_2)$ procedure called Delayed Theory Combination (DTC), in which each ${\mathcal{T}_i}{\text {-}}solver$ interacts directly and only with the SAT solver, in such a way that part or all of the (possibly very expensive) reasoning effort on interface equalities is delegated to the SAT solver itself. In this paper we present a comparative analysis of DTC vs. NO for $SMT(\mathcal{T}_1 \cup \mathcal{T}_2)$ . On the one hand, we explain the advantages of DTC in exploiting the power of modern SAT solvers to reduce the search. On the other hand, we show that the extra amount of Boolean search required to the SAT solver can be controlled. In fact, we prove two novel theoretical results, for both convex and non-convex theories and for different deduction capabilities of the ${\mathcal{T}_i}{\text {-}}solvers$ , which relate the amount of extra Boolean search required to the SAT solver by DTC with the number of deductions and case-splits required to the ${\mathcal{T}_i}{\text {-}}solvers$ by NO in order to perform the same tasks: (i) under the same hypotheses of deduction capabilities of the ${\mathcal{T}_i}{\text {-}}solvers$ required by NO, DTC causes no extra Boolean search; (ii) using ${\mathcal{T}_i}{\text {-}}solvers$ with limited or no deduction capabilities, the extra Boolean search required can be reduced down to a negligible amount by controlling the quality of the $\mathcal{T}$ -conflict sets returned by the ${\mathcal{T}_i}{\text {-}}solvers$ .     

Branching Time Logics \mathcal {BTL}^{\mathrm {U,S}}_{\mathrm {N},\mathrm {N}^{-1}}(\mathcal {Z})_{\alpha } with Operations Until and Since Based on Bundles of Integer Numbers, Logical Consecutions, Deciding Algorithms

This paper is intended as an attempt to describe logical consequence in branching time logics. We study temporal branching time logics $\mathcal {BTL}^{\mathrm {U,S}}_{\mathrm {N},\mathrm {N}^{-1}}(\mathcal {Z})_{\alpha }$ which use the standard operations Until and Next and dual operations Since and Previous (LTL, as standard, uses only Until and Next). Temporal logics $\mathcal {BTL}^{\mathrm {U,S}}_{\mathrm {N},\mathrm {N}^{-1}}(\mathcal {Z})_{\alpha }$ are generated by semantics based on Kripke/Hinttikka structures with linear frames of integer numbers $\mathcal {Z}$ with a single node (glued zeros). For $\mathcal {BTL}^{\mathrm {U,S}}_{\mathrm {N},\mathrm {N}^{-1}}(\mathcal {Z})_{\alpha }$ , the permissible branching of the node is limited by α (where 1≤α≤ω). We prove that any logic $\mathcal {BTL}^{\mathrm {U,S}}_{\mathrm {N},\mathrm {N}^{-1}}(\mathcal {Z})_{\alpha }$ is decidable w.r.t. admissible consecutions (inference rules), i.e. we find an algorithm recognizing consecutions admissible in $\mathcal {BTL}^{\mathrm {U,S}}_{\mathrm {N},\mathrm {N}^{-1}}(\mathcal {Z})_{\alpha }$ . As a consequence, it implies that $\mathcal {BTL}^{\mathrm {U,S}}_{\mathrm {N},\mathrm {N}^{-1}}(\mathcal {Z})_{\alpha }$ itself is decidable and solves the satisfiability problem.     

Constructing Minimal Phylogenetic Networks from Softwired Clusters is Fixed Parameter Tractable

Here we show that, given a set of clusters ${\mathcal{C}}$ on a set of taxa ${\mathcal{X}}$ , where $|{\mathcal{X}}|=n$ , it is possible to determine in time f(k)?poly(n) whether there exists a level-≤k network (i.e. a network where each biconnected component has reticulation number at most k) that represents all the clusters in ${\mathcal{C}}$ in the softwired sense, and if so to construct such a network. This extends a result from Kelk et al. (in IEEE/ACM Trans. Comput. Biol. Bioinform. 9:517–534, 2012) which showed that the problem is polynomial-time solvable for fixed k. By defining “k-reticulation generators” analogous to “level-k generators”, we then extend this fixed parameter tractability result to the problem where k refers not to the level but to the reticulation number of the whole network.     

Augmenting Edge-Connectivity between Vertex Subsets

Given a directed or undirected graph G=(V,E), a collection ${\mathcal{R}}=\{(S_{i},T_{i}) \mid i=1,2,\ldots,|{\mathcal{R}}|, S_{i},T_{i} \subseteq V, S_{i} \cap T_{i} =\emptyset\}$ of two disjoint subsets of V, and a requirement function $r: {\mathcal{R}} \to\mathbb{R}_{+}$ , we consider the problem (called area-to-area edge-connectivity augmentation problem) of augmenting G by a smallest number of new edges so that the resulting graph $\hat{G}$ satisfies $d_{\hat{G}}(X)\geq r(S,T)$ for all X?V, $(S,T) \in{\mathcal{R}}$ with S?X?V?T, where d _G (X) denotes the degree of a vertex set X in G. This problem can be regarded as a natural generalization of the global, local, and node-to-area edge-connectivity augmentation problems. In this paper, we show that there exists a constant c such that the problem is inapproximable within a ratio of $c\log{|{\mathcal{R}}|}$ , unless P=NP, even restricted to the directed global node-to-area edge-connectivity augmentation or undirected local node-to-area edge-connectivity augmentation. We also provide an ${\mathrm{O}}(\log{|{\mathcal{R}}|})$ -approximation algorithm for the area-to-area edge-connectivity augmentation problem, which is a natural extension of Kortsarz and Nutov’s algorithm (Kortsarz and Nutov, J. Comput. Syst. Sci., 74:662–670, 2008). This together with the negative result implies that the problem is ${\varTheta}(\log{|{\mathcal{R}}|})$ -approximable, unless P=NP, which solves open problems for node-to-area edge-connectivity augmentation in Ishii et al. (Algorithmica, 56:413–436, 2010), Ishii and Hagiwara (Discrete Appl. Math., 154:2307–2329, 2006), Miwa and Ito (J. Oper. Res. Soc. Jpn., 47:224–243, 2004). Furthermore, we characterize the node-to-area and area-to-area edge-connectivity augmentation problems as the augmentation problems with modulotone and k-modulotone functions.     

Equiparadoxicality of Yablo’s Paradox and the Liar

It is proved that Yablo’s paradox and the Liar paradox are equiparadoxical, in the sense that their paradoxicality is based upon exactly the same circularity condition—for any frame ${\mathcal{K}}$ , the following are equivalent: (1) Yablo’s sequence leads to a paradox in ${\mathcal{K}}$ ; (2) the Liar sentence leads to a paradox in ${\mathcal{K}}$ ; (3) ${\mathcal{K}}$ contains odd cycles. This result does not conflict with Yablo’s claim that his sequence is non-self-referential. Rather, it gives Yablo’s paradox a new significance: his construction contributes a method by which we can eliminate the self-reference of a paradox without changing its circularity condition.     

On set consensus numbers

It is conjectured that the only way a failure detector (FD) can help solving n-process tasks is by providing k-set consensus for some ${k\in\{1,\ldots,n\}}$ among all the processes. It was recently shown by Zieli??ski that any FD that allows for solving a given n-process task that is unsolvable read-write wait-free, also solves (n ? 1)-set consensus. In this paper, we provide a generalization of Zieli??ski??s result. We show that any FD that solves a colorless task that cannot be solved read-write k-resiliently, also solves k-set consensus. More generally, we show that every colorless task ${\mathcal{T}}$ can be characterized by its set consensus number: the largest ${k\in\{1,\ldots,n\}}$ such that ${\mathcal{T}}$ is solvable (k ? 1)-resiliently. A task ${\mathcal{T}}$ with set consensus number k is, in the failure detector sense, equivalent to k-set consensus, i.e., a FD solves ${\mathcal{T}}$ if and only if it solves k-set consensus. As a corollary, we determine the weakest FD for solving k-set consensus in every environment, i.e., for all assumptions on when and where failures might occur.     

Improved Approximation of Linear Threshold Functions

We prove two main results on how arbitrary linear threshold functions ${f(x) = {\rm sign}(w \cdot x - \theta)}$ over the n-dimensional Boolean hypercube can be approximated by simple threshold functions. Our first result shows that every n-variable threshold function f is ${\epsilon}$ -close to a threshold function depending only on ${{\rm Inf}(f)^2 \cdot {\rm poly}(1/\epsilon)}$ many variables, where ${{\rm Inf}(f)}$ denotes the total influence or average sensitivity of f. This is an exponential sharpening of Friedgut’s well-known theorem (Friedgut in Combinatorica 18(1):474–483, 1998), which states that every Boolean function f is ${\epsilon}$ -close to a function depending only on ${2^{O({\rm Inf}(f)/\epsilon)}}$ many variables, for the case of threshold functions. We complement this upper bound by showing that ${\Omega({\rm Inf}(f)^2 + 1/\epsilon^2)}$ many variables are required for ${\epsilon}$ -approximating threshold functions. Our second result is a proof that every n-variable threshold function is ${\epsilon}$ -close to a threshold function with integer weights at most ${{\rm poly}(n) \cdot 2^{\tilde{O}(1/\epsilon^{2/3})}.}$ This is an improvement, in the dependence on the error parameter ${\epsilon}$ , on an earlier result of Servedio (Comput Complex 16(2):180–209, 2007) which gave a ${{\rm poly}(n) \cdot 2^{\tilde{O}(1/\epsilon^{2})}}$ bound. Our improvement is obtained via a new proof technique that uses strong anti-concentration bounds from probability theory. The new technique also gives a simple and modular proof of the original result of Servedio (Comput Complex 16(2):180–209, 2007) and extends to give low-weight approximators for threshold functions under a range of probability distributions other than the uniform distribution.     

DNF sparsification and a faster deterministic counting algorithm

Given a DNF formula f on n variables, the two natural size measures are the number of terms or size s(f) and the maximum width of a term w(f). It is folklore that small DNF formulas can be made narrow: if a formula has m terms, it can be ${\epsilon}$ -approximated by a formula with width ${{\rm log}(m/{\epsilon})}$ . We prove a converse, showing that narrow formulas can be sparsified. More precisely, any width w DNF irrespective of its size can be ${\epsilon}$ -approximated by a width w DNF with at most ${(w\, {\rm log}(1/{\epsilon}))^{O(w)}}$ terms. We combine our sparsification result with the work of Luby & Velickovic (1991, Algorithmica 16(4/5):415–433, 1996) to give a faster deterministic algorithm for approximately counting the number of satisfying solutions to a DNF. Given a formula on n variables with poly(n) terms, we give a deterministic ${n^{\tilde{O}({\rm log}\, {\rm log} (n))}}$ time algorithm that computes an additive ${\epsilon}$ approximation to the fraction of satisfying assignments of f for ${\epsilon = 1/{\rm poly}({\rm log}\, n)}$ . The previous best result due to Luby and Velickovic from nearly two decades ago had a run time of ${n^{{\rm exp}(O(\sqrt{{\rm log}\, {\rm log} n}))}}$ (Luby & Velickovic 1991, in Algorithmica 16(4/5):415–433, 1996).     

Query language-based inverses of schema mappings: semantics, computation, and closure properties

The inversion of schema mappings has been identified as one of the fundamental operators for the development of a general framework for metadata management. During the last few years, three alternative notions of inversion for schema mappings have been proposed (Fagin-inverse (Fagin, TODS 32(4), 25:1–25:53, 2007), quasi-inverse (Fagin et?al., TODS 33(2), 11:1–11:52, 2008), and maximum recovery (Arenas et?al., TODS 34(4), 22:1–22:48, 2009)). However, these notions lack some fundamental properties that limit their practical applicability: most of them are expressed in languages including features that are difficult to use in practice, some of these inverses are not guaranteed to exist for mappings specified with source-to-target tuple-generating dependencies (st-tgds), and it has been futile to search for a meaningful mapping language that is closed under any of these notions of inverse. In this paper, we develop a framework for the inversion of schema mappings that fulfills all of the above requirements. It is based on the notion of ${\mathcal{C}}$ -maximum recovery, for a query language ${\mathcal{C}}$ , a notion designed to generate inverse mappings that recover back only the information that can be retrieved with queries in ${\mathcal{C}}$ . By focusing on the language of conjunctive queries (CQ), we are able to find a mapping language that contains the class of st-tgds, is closed under CQ-maximum recovery, and for which the chase procedure can be used to exchange data efficiently. Furthermore, we show that our choices of inverse notion and mapping language are optimal, in the sense that choosing a more expressive inverse operator or mapping language causes the loss of these properties.     

Plaintext awareness in identity-based key encapsulation

The notion of plaintext awareness ( ${\mathsf{PA}}$ ) has many applications in public key cryptography: it offers unique, stand-alone security guarantees for public key encryption schemes, has been used as a sufficient condition for proving indistinguishability against adaptive chosen-ciphertext attacks ( ${\mathsf{IND}\hbox {-}{\mathsf{CCA}}}$ ), and can be used to construct privacy-preserving protocols such as deniable authentication. Unlike many other security notions, plaintext awareness is very fragile when it comes to differences between the random oracle and standard models; for example, many implications involving ${\mathsf{PA}}$ in the random oracle model are not valid in the standard model and vice versa. Similarly, strategies for proving ${\mathsf{PA}}$ of schemes in one model cannot be adapted to the other model. Existing research addresses ${\mathsf{PA}}$ in detail only in the public key setting. This paper gives the first formal exploration of plaintext awareness in the identity-based setting and, as initial work, proceeds in the random oracle model. The focus is laid mainly on identity-based key encapsulation mechanisms (IB-KEMs), for which the paper presents the first definitions of plaintext awareness, highlights the role of ${\mathsf{PA}}$ in proof strategies of ${\mathsf{IND}\hbox {-}{\mathsf{CCA}}}$ security, and explores relationships between ${\mathsf{PA}}$ and other security properties. On the practical side, our work offers the first, highly efficient, general approach for building IB-KEMs that are simultaneously plaintext-aware and ${\mathsf{IND}\hbox {-}{\mathsf{CCA}}}$ -secure. Our construction is inspired by the Fujisaki-Okamoto (FO) transform, but demands weaker and more natural properties of its building blocks. This result comes from a new look at the notion of $\gamma $ -uniformity that was inherent in the original FO transform. We show that for IB-KEMs (and PK-KEMs), this assumption can be replaced with a weaker computational notion, which is in fact implied by one-wayness. Finally, we give the first concrete IB-KEM scheme that is ${\mathsf{PA}}$ and ${\mathsf{IND}\hbox {-}{\mathsf{CCA}}}$ -secure by applying our construction to a popular IB-KEM and optimizing it for better performance.     

Pseudorandom generators for CC0[p] and the Fourier spectrum of low-degree polynomials over finite fields

In this paper, we give the first construction of a pseudorandom generator, with seed length O(log n), for CC⁰[p], the class of constant-depth circuits with unbounded fan-in MOD _p gates, for some prime p. More accurately, the seed length of our generator is O(log n) for any constant error ${\epsilon > 0}$ . In fact, we obtain our generator by fooling distributions generated by low-degree polynomials, over ${\mathbb{F}_p}$ , when evaluated on the Boolean cube. This result significantly extends previous constructions that either required a long seed (Luby et al. 1993) or could only fool the distribution generated by linear functions over ${\mathbb{F}_p}$ , when evaluated on the Boolean cube (Lovett et al. 2009; Meka & Zuckerman 2009). En route of constructing our PRG, we prove two structural results for low-degree polynomials over finite fields that can be of independent interest.

1. Let f be an n-variate degree d polynomial over ${\mathbb{F}_p}$ . Then, for every ${\epsilon > 0}$ , there exists a subset ${S \subset [n]}$ , whose size depends only on d and ${\epsilon}$ , such that ${\sum_{\alpha \in \mathbb{F}_p^n: \alpha \ne 0, \alpha_S=0}|\hat{f}(\alpha)|^2 \leq \epsilon}$ . Namely, there is a constant size subset S such that the total weight of the nonzero Fourier coefficients that do not involve any variable from S is small.
2. Let f be an n-variate degree d polynomial over ${\mathbb{F}_p}$ . If the distribution of f when applied to uniform zero–one bits is ${\epsilon}$ -far (in statistical distance) from its distribution when applied to biased bits, then for every ${\delta > 0}$ , f can be approximated over zero–one bits, up to error δ, by a function of a small number (depending only on ${\epsilon,\delta}$ and d) of lower degree polynomials.

     

Anti-unification for Unranked Terms and Hedges

We study anti-unification for unranked terms and hedges that may contain term and hedge variables. The anti-unification problem of two hedges ${\tilde{s}}_1$ and ${\tilde{s}}_2$ is concerned with finding their generalization, a hedge ${\tilde{q}}$ such that both ${\tilde{s}}_1$ and ${\tilde{s}}_2$ are instances of ${\tilde{q}}$ under some substitutions. Hedge variables help to fill in gaps in generalizations, while term variables abstract single (sub)terms with different top function symbols. First, we design a complete and minimal algorithm to compute least general generalizations. Then, we improve the efficiency of the algorithm by restricting possible alternatives permitted in the generalizations. The restrictions are imposed with the help of a rigidity function, which is a parameter in the improved algorithm and selects certain common subsequences from the hedges to be generalized. The obtained rigid anti-unification algorithm is further made more precise by permitting combination of hedge and term variables in generalizations. Finally, we indicate a possible application of the algorithm in software engineering.     

VE dimension induced by Bayesian networks over the boolean domain

In this paper, we focus on the concept classes \({\mathcal {C}}_{{\mathcal{N}}}\) induced by Bayesian networks. The relationship between two-dimensional values induced by these concept classes is studied, one of which is the VC-dimension of the concept class \({\mathcal {C}}_{\cal {N}},\) denoted as \(VCdim({\mathcal {N}}), \) and other is the smallest dimensional of Euclidean spaces into which \({\mathcal {C}}_{{\mathcal {N}}}\) can be embedded, denoted as \(Edim({\mathcal {N}}). \) As a main result, we show that the two-dimensional values are equal for the Bayesian networks with n ≤ 4 variables, called the VE-dimension for that Bayesian networks.