Showing papers in "Journal of the ACM in 2020"

Fully Functional Suffix Trees and Optimal Text Searching in BWT-Runs Bounded Space

Abstract: Indexing highly repetitive texts—such as genomic databases, software repositories and versioned text collections—has become an important problem since the turn of the millennium. A relevant compressibility measure for repetitive texts is r, the number of runs in their Burrows-Wheeler Transforms (BWTs). One of the earliest indexes for repetitive collections, the Run-Length FM-index, used O(r) space and was able to efficiently count the number of occurrences of a pattern of length m in a text of length n (in O(m log log n) time, with current techniques). However, it was unable to locate the positions of those occurrences efficiently within a space bounded in terms of r. In this article, we close this long-standing problem, showing how to extend the Run-Length FM-index so that it can locate the occ occurrences efficiently (in O(occ log log n) time) within O(r) space. By raising the space to O(r log log n), our index counts the occurrences in optimal time, O(m), and locates them in optimal time as well, O(m + occ). By further raising the space by an O(w/ log σ) factor, where σ is the alphabet size and w = Ω (log n) is the RAM machine size in bits, we support count and locate in O(⌈ m log (σ)/w ⌉) and O(⌈ m log (σ)/w ⌉ + occ) time, which is optimal in the packed setting and had not been obtained before in compressed space. We also describe a structure using O(r log (n/r)) space that replaces the text and extracts any text substring of length e in the almost-optimal time O(log (n/r)+e log (σ)/w). Within that space, we similarly provide access to arbitrary suffix array, inverse suffix array, and longest common prefix array cells in time O(log (n/r)), and extend these capabilities to full suffix tree functionality, typically in O(log (n/r)) time per operation. Our experiments show that our O(r)-space index outperforms the space-competitive alternatives by 1--2 orders of magnitude in time. Competitive implementations of the original FM-index are outperformed by 1--2 orders of magnitude in space and/or 2--3 in time.

Planar Graphs Have Bounded Queue-Number

Abstract: We show that planar graphs have bounded queue-number, thus proving a conjecture of Heath et al. [66] from 1992. The key to the proof is a new structural tool called layered partitions, and the result that every planar graph has a vertex-partition and a layering, such that each part has a bounded number of vertices in each layer, and the quotient graph has bounded treewidth. This result generalises for graphs of bounded Euler genus. Moreover, we prove that every graph in a minor-closed class has such a layered partition if and only if the class excludes some apex graph. Building on this work and using the graph minor structure theorem, we prove that every proper minor-closed class of graphs has bounded queue-number. Layered partitions have strong connections to other topics, including the following two examples. First, they can be interpreted in terms of strong products. We show that every planar graph is a subgraph of the strong product of a path with some graph of bounded treewidth. Similar statements hold for all proper minor-closed classes. Second, we give a simple proof of the result by DeVos et al. [31] that graphs in a proper minor-closed class have low treewidth colourings.

A Proof of the CSP Dichotomy Conjecture

Abstract: Many natural combinatorial problems can be expressed as constraint satisfaction problems. This class of problems is known to be NP-complete in general, but certain restrictions on the form of the constraints can ensure tractability. The standard way to parameterize interesting subclasses of the constraint satisfaction problem is via finite constraint languages. The main problem is to classify those subclasses that are solvable in polynomial time and those that are NP-complete. It was conjectured that if a constraint language has a weak near-unanimity polymorphism then the corresponding constraint satisfaction problem is tractable; otherwise, it is NP-complete. In the article, we present an algorithm that solves Constraint Satisfaction Problem in polynomial time for constraint languages having a weak near unanimity polymorphism, which proves the remaining part of the conjecture.1

Universally Composable Security

Abstract: This work presents a general framework for describing cryptographic protocols and analyzing their security. The framework allows specifying the security requirements of practically any cryptographic task in a unified and systematic way. Furthermore, in this framework the security of protocols is preserved under a general composition operation, called universal composition. The proposed framework with its security-preserving composition operation allows for modular design and analysis of complex cryptographic protocols from simpler building blocks. Moreover, within this framework, protocols are guaranteed to maintain their security in any context, even in the presence of an unbounded number of arbitrary protocol sessions that run concurrently in an adversarially controlled manner. This is a useful guarantee, which allows arguing about the security of cryptographic protocols in complex and unpredictable environments such as modern communication networks.

Differential Equation Invariance Axiomatization

Abstract: This article proves the completeness of an axiomatization for differential equation invariants described by Noetherian functions. First, the differential equation axioms of differential dynamic logic are shown to be complete for reasoning about analytic invariants. Completeness crucially exploits differential ghosts, which introduce additional variables that can be chosen to evolve freely along new differential equations. Cleverly chosen differential ghosts are the proof-theoretical counterpart of dark matter. They create a new hypothetical state, whose relationship to the original state variables satisfies invariants that did not exist before. The reflection of these new invariants in the original system then enables its analysis.An extended axiomatization with existence and uniqueness axioms is complete for all local progress properties, and, with a real induction axiom, is complete for all semianalytic invariants. This parsimonious axiomatization serves as the logical foundation for reasoning about invariants of differential equations. Indeed, it is precisely this logical treatment that enables the generalization of completeness to the Noetherian case.

Detecting an Odd Hole

Abstract: We give a polynomial-time algorithm to test whether a graph contains an induced cycle with length more than three and odd.

Fully Online Matching

Abstract: We introduce a fully online model of maximum cardinality matching in which all vertices arrive online. On the arrival of a vertex, its incident edges to previously arrived vertices are revealed. Each vertex has a deadline that is after all its neighbors’ arrivals. If a vertex remains unmatched until its deadline, then the algorithm must irrevocably either match it to an unmatched neighbor or leave it unmatched. The model generalizes the existing one-sided online model and is motivated by applications including ride-sharing platforms, real-estate agency, and so on. We show that the Ranking algorithm by Karp et al. (STOC 1990) is 0.5211-competitive in our fully online model for general graphs. Our analysis brings a novel charging mechanic into the randomized primal dual technique by Devanur et al. (SODA 2013), allowing a vertex other than the two endpoints of a matched edge to share the gain. To our knowledge, this is the first analysis of Ranking that beats 0.5 on general graphs in an online matching problem, a first step toward solving the open problem by Karp et al. (STOC 1990) about the optimality of Ranking on general graphs. If the graph is bipartite, then we show a tight competitive ratio a0.5671 of Ranking. Finally, we prove that the fully online model is strictly harder than the previous model as no online algorithm can be 0.6317

Representative Sets and Irrelevant Vertices: New Tools for Kernelization

Abstract: We continue the development of matroid-based techniques for kernelization, initiated by the present authors [47] We significantly extend the usefulness of matroid theory in kernelization by showing applications of a result on representative sets due to Lovasz [51] and Marx [53] As a first result, we show how representative sets can be used to derive a polynomial kernel for the elusive ALMOST 2-SAT problem (where the task is to remove at most k clauses to make a 2-CNF formula satisfiable), solving a major open problem in kernelization This result also yields a new O(√log OPT)-approximation for the problem, improving on the O(√log n)-approximation of Agarwal et al [3] and an implicit O(log OPT)-approximation due to Even et al [24] We further apply the representative sets tool to the problem of finding irrelevant vertices in graph cut problems, that is, vertices that can be made undeletable without affecting the answer to the problem This gives the first significant progress towards a polynomial kernel for the MULTIWAY CUT problem; in particular, we get a kernel of O(ks+1) vertices for MULTIWAY CUT instances with at most s terminals Both these kernelization results have significant spin-off effects, producing the first polynomial kernels for a range of related problems More generally, the irrelevant vertex results have implications for covering min cuts in graphs For a directed graph G=(V,E) and sets S, T ⊆ V, let r be the size of a minimum (S,T)-vertex cut (which may intersect S and T) We can find a set Z ⊆ V of size O(|S| |T| r) that contains a minimum (A,B)-vertex cut for every A ⊆ S, B ⊆ T Similarly, for an undirected graph G=(V,E), a set of terminals X ⊆ V, and a constant s, we can find a set Z⊆ V of size O(|X|s+1) that contains a minimum multiway cut for every partition of X into at most s pairwise disjoint subsets Both results are polynomial time We expect this to have further applications; in particular, we get direct, reduction rule-based kernelizations for all problems above, in contrast to the indirect compression-based kernel previously given for ODD CYCLE TRANSVERSAL [47] All our results are randomized, with failure probabilities that can be made exponentially small in n, due to needing a representation of a matroid to apply the representative sets tool

Approximating Edit Distance Within Constant Factor in Truly Sub-quadratic Time

Abstract: Edit distance is a measure of similarity of two strings based on the minimum number of character insertions, deletions, and substitutions required to transform one string into the other. The edit distance can be computed exactly using a dynamic programming algorithm that runs in quadratic time. Andoni, Krauthgamer, and Onak (2010) gave a nearly linear time algorithm that approximates edit distance within approximation factor poly(log n). In this article, we provide an algorithm with running time O(n2−2/7) that approximates the edit distance within a constant factor.

Near-optimal Sample Complexity Bounds for Robust Learning of Gaussian Mixtures via Compression Schemes

Abstract: We introduce a novel technique for distribution learning based on a notion of sample compression. Any class of distributions that allows such a compression scheme can be learned with few samples. Moreover, if a class of distributions has such a compression scheme, then so do the classes of products and mixtures of those distributions. As an application of this technique, we prove that ˜Θ(kd2/e2) samples are necessary and sufficient for learning a mixture of k Gaussians in Rd, up to error e in total variation distance. This improves both the known upper bounds and lower bounds for this problem. For mixtures of axis-aligned Gaussians, we show that O(kd/e2) samples suffice, matching a known lower bound. Moreover, these results hold in an agnostic learning (or robust estimation) setting, in which the target distribution is only approximately a mixture of Gaussians. Our main upper bound is proven by showing that the class of Gaussians in Rd admits a small compression scheme.

A Simple and Approximately Optimal Mechanism for an Additive Buyer

Abstract: We consider a monopolist seller with n heterogeneous items, facing a single buyer The buyer has a value for each item drawn independently according to (non-identical) distributions, and her value for a set of items is additive The seller aims to maximize his revenue We suggest using the a priori better of two simple pricing methods: selling the items separately, each at its optimal price, and bundling together, in which the entire set of items is sold as one bundle at its optimal price We show that for any distribution, this mechanism achieves a constant-factor approximation to the optimal revenue Beyond its simplicity, this is the first computationally tractable mechanism to obtain a constant-factor approximation for this multi-parameter problem We additionally discuss extensions to multiple buyers and to valuations that are correlated across items

The Reachability Problem for Petri Nets Is Not Elementary

Abstract: Petri nets, also known as vector addition systems, are a long established model of concurrency with extensive applications in modeling and analysis of hardware, software, and database systems, as well as chemical, biological, and business processes. The central algorithmic problem for Petri nets is reachability: whether from the given initial configuration there exists a sequence of valid execution steps that reaches the given final configuration. The complexity of the problem has remained unsettled since the 1960s, and it is one of the most prominent open questions in the theory of verification. Decidability was proved by Mayr in his seminal STOC 1981 work, and, currently, the best published upper bound is non-primitive recursive Ackermannian of Leroux and Schmitz from Symposium on Logic in Computer Science 2019. We establish a non-elementary lower bound, i.e., that the reachability problem needs a tower of exponentials of time and space. Until this work, the best lower bound has been exponential space, due to Lipton in 1976. The new lower bound is a major breakthrough for several reasons. Firstly, it shows that the reachability problem is much harder than the coverability (i.e., state reachability) problem, which is also ubiquitous but has been known to be complete for exponential space since the late 1970s. Secondly, it implies that a plethora of problems from formal languages, logic, concurrent systems, process calculi, and other areas, which are known to admit reductions from the Petri nets reachability problem, are also not elementary. Thirdly, it makes obsolete the current best lower bounds for the reachability problems for two key extensions of Petri nets: with branching and with a pushdown stack. We develop a construction that uses arbitrarily large pairs of values with ratio R to provide zero testable counters that are bounded by R. At the heart of our proof is then a novel gadget, the so-called factorial amplifier that, assuming availability of counters that are zero testable and bounded by k, guarantees to produce arbitrarily large pairs of values whose ratio is exactly the factorial of k. Repeatedly composing the factorial amplifier with itself by means of the former construction enables us to compute, in linear time, Petri nets that simulate Minsky machines whose counters are bounded by a tower of exponentials, which yields the non-elementary lower bound. By refining this scheme further, we, in fact, already establish hardness for h-exponential space for Petri nets with h + 13 counters.

Oracle-efficient Online Learning and Auction Design

Abstract: We consider the design of computationally efficient online learning algorithms in an adversarial setting in which the learner has access to an offline optimization oracle. We present an algorithm called Generalized Follow-the-Perturbed-Leader and provide conditions under which it is oracle-efficient while achieving vanishing regret. Our results make significant progress on an open problem raised by Hazan and Koren [31], who showed that oracle-efficient algorithms do not exist in general [30] and asked whether one can identify properties under which oracle-efficient online learning may be possible. Our auction-design framework considers an auctioneer learning an optimal auction for a sequence of adversarially selected valuations with the goal of achieving revenue that is almost as good as the optimal auction in hindsight, among a class of auctions. We give oracle-efficient learning results for: (1) VCG auctions with bidder-specific reserves in single-parameter settings, (2) envy-free item pricing in multi-item auctions, and (3) s-level auctions of Morgenstern and Roughgarden [43] for single-item settings. The last result leads to an approximation of the overall optimal Myerson auction when bidders’ valuations are drawn according to a fast-mixing Markov process, extending prior work that only gave such guarantees for the i.i.d. setting. Finally, we derive various extensions, including: (1) oracle-efficient algorithms for the contextual learning setting in which the learner has access to side information (such as bidder demographics), (2) learning with approximate oracles such as those based on Maximal-in-Range algorithms, and (3) no-regret bidding in simultaneous auctions, resolving an open problem of Daskalakis and Syrgkanis [14].

A Constant-factor Approximation Algorithm for the Asymmetric Traveling Salesman Problem

Abstract: We give a constant-factor approximation algorithm for the asymmetric traveling salesman problem (ATSP). Our approximation guarantee is analyzed with respect to the standard LP relaxation, and thus our result confirms the conjectured constant integrality gap of that relaxation. The main idea of our approach is a reduction to Subtour Partition Cover, an easier problem obtained by significantly relaxing the general connectivity requirements into local connectivity conditions. We first show that any algorithm for Subtour Partition Cover can be turned into an algorithm for ATSP while only losing a small constant factor in the performance guarantee. Next, we present a reduction from general ATSP instances to structured instances, on which we then solve Subtour Partition Cover, yielding our constant-factor approximation algorithm for ATSP.

Enhanced Phase Clocks, Population Protocols, and Fast Space Optimal Leader Election

Abstract: The model of population protocols refers to the growing in popularity theoretical framework suitable for studying pairwise interactions within a large collection of simple indistinguishable entities, frequently called agents. In this article, the emphasis is on the space complexity of fast leader election in population protocols governed by the random scheduler, which uniformly at random selects pairwise interactions between n agents. One of the main results of this article is the first fast space optimal leader election protocol, which works with high probability. The new protocol operates in parallel time O(log2 n) equivalent to O(nlog2 n) sequential pairwise interactions with each agent’s memory space limited to O(log log n) states. This double logarithmic space utilisation matches asymptotically the lower bound ½log log n on the number of states utilised by agents in any leader election algorithm with the running time o(n\polylog n); see Reference [7]. Our new solution expands also on the classical concept of phase clocks used to synchronise and to coordinate computations in distributed algorithms. In particular, we formalise the concept and provide a rigorous analysis of phase clocks operating in nested modes. Our arguments are also valid for phase clocks propelled by multiple leaders. The combination of the two results in the first time-space efficient leader election algorithm. We also provide a complete formal argumentation, indicating that our solution is always correct, fast, and it works with high probability.

A Unified Translation of Linear Temporal Logic to ω-Automata

Abstract: We present a unified translation of linear temporal logic (LTL) formulas into deterministic Rabin automata (DRA), limit-deterministic Buchi automata (LDBA), and nondeterministic Buchi automata (NBA). The translations yield automata of asymptotically optimal size (double or single exponential, respectively). All three translations are derived from one single Master Theorem of purely logical nature. The Master Theorem decomposes the language of a formula into a positive Boolean combination of languages that can be translated into ω-automata by elementary means. In particular, Safra’s, ranking, and breakpoint constructions used in other translations are not needed. We further give evidence that this theoretical clean and compositional approach does not lead to large automata per se and in fact in the case of DRAs yields significantly smaller automata compared to the previously known approach using determinisation of NBAs.

Polynomiality for Bin Packing with a Constant Number of Item Types

Abstract: We consider the bin packing problem with d different item sizes si and item multiplicities ai, where all numbers are given in binary encoding. This problem formulation is also known as the one-dimensional cutting stock problem. In this work, we provide an algorithm that, for constant d, solves bin packing in polynomial time. This was an open problem for all d\ge 3. In fact, for constant d our algorithm solves the following problem in polynomial time: Given two d-dimensional polytopes P and Q, find the smallest number of integer points in P whose sum lies in Q. Our approach also applies to high multiplicity scheduling problems in which the number of copies of each job type is given in binary encoding and each type comes with certain parameters such as release dates, processing times, and deadlines. We show that a variety of high multiplicity scheduling problems can be solved in polynomial time if the number of job types is constant.

Frege Systems for Quantified Boolean Logic

Abstract: We define and investigate Frege systems for quantified Boolean formulas (QBF). For these new proof systems, we develop a lower bound technique that directly lifts circuit lower bounds for a circuit class C to the QBF Frege system operating with lines from C. Such a direct transfer from circuit to proof complexity lower bounds has often been postulated for propositional systems but had not been formally established in such generality for any proof systems prior to this work. This leads to strong lower bounds for restricted versions of QBF Frege, in particular an exponential lower bound for QBF Frege systems operating with AC0[p] circuits. In contrast, any non-trivial lower bound for propositional AC0[p]-Frege constitutes a major open problem.Improving these lower bounds to unrestricted QBF Frege tightly corresponds to the major problems in circuit complexity and propositional proof complexity. In particular, proving a lower bound for QBF Frege systems operating with arbitrary P/poly circuits is equivalent to either showing a lower bound for P/poly or for propositional extended Frege (which operates with P/poly circuits). We also compare our new QBF Frege systems to standard sequent calculi for QBF and establish a correspondence to intuitionistic bounded arithmetic.

Polynomial Counting in Anonymous Dynamic Networks with Applications to Anonymous Dynamic Algebraic Computations

Abstract: Starting with with work of Michail et al., the problem of Counting the number of nodes in Anonymous Dynamic Networks has attracted a lot of attention. The problem is challenging because nodes are indistinguishable (they lack identifiers and execute the same program), and the topology may change arbitrarily from round to round of communication, as long as the network is connected in each round. The problem is central in distributed computing, as the number of participants is frequently needed to make important decisions, including termination, agreement, synchronization, among others. A variety of distributed algorithms built on top of mass-distribution techniques have been presented, analyzed, and experimentally evaluated; some of them assumed additional knowledge of network characteristics, such as bounded degree or given upper bound on the network size. However, the question of whether Counting can be solved deterministically in sub-exponential time remained open. In this work, we answer this question positively by presenting Methodical Counting, which runs in polynomial time and requires no knowledge of network characteristics. Moreover, we also show how to extend Methodical Counting to compute the sum of input values and more complex functions without extra cost. Our analysis leverages previous work on random walks in evolving graphs, combined with carefully chosen alarms in the algorithm that control the process and its parameters. To the best of our knowledge, our Counting algorithm and its extensions to other algebraic and Boolean functions are the first that can be implemented in practice with worst-case guarantees.

Embeddability in R3 is NP-hard

Abstract: We prove that the problem of deciding whether a two- or three-dimensional simplicial complex embeds into R3 is NP-hard. Our construction also shows that deciding whether a 3-manifold with boundary tori admits an S3 filling is NP-hard. The former stands in contrast with the lower-dimensional cases, which can be solved in linear time, and the latter with a variety of computational problems in 3-manifold topology, for example, unknot or 3-sphere recognition, which are in NP ∩ co- NP. (Membership of the latter problem in co-NP assumes the Generalized Riemann Hypotheses.) Our reduction encodes a satisfiability instance into the embeddability problem of a 3-manifold with boundary tori, and relies extensively on techniques from low-dimensional topology, most importantly Dehn fillings of manifolds with boundary tori.

Automating Resolution is NP-Hard

Abstract: We show that the problem of finding a Resolution refutation that is at most polynomially longer than a shortest one is NP-hard. In the parlance of proof complexity, Resolution is not automatable unless P = NP. Indeed, we show that it is NP-hard to distinguish between formulas that have Resolution refutations of polynomial length and those that do not have subexponential length refutations. This also implies that Resolution is not automatable in subexponential time or quasi-polynomial time unless NP is included in SUBEXP or QP, respectively.

Deterministic Factorization of Sparse Polynomials with Bounded Individual Degree

Abstract: In this article, we study the problem of deterministic factorization of sparse polynomials. We show that if f ∈ F[x1,x2,… ,xn] is a polynomial with s monomials, with individual degrees of its variables bounded by d, then f can be deterministically factored in time spoly(d)log n. Prior to our work, the only efficient factoring algorithms known for this class of polynomials were randomized, and other than for the cases of d=1 and d=2, only exponential time-deterministic factoring algorithms were known.A crucial ingredient in our proof is a quasi-polynomial sparsity bound for factors of sparse polynomials of bounded individual degree. In particular, we show that if f is an s-sparse polynomial in n variables, with individual degrees of its variables bounded by d, then the sparsity of each factor of f is bounded by s(9 d2 log n). This is the first non-trivial bound on factor sparsity for d> 2. Our sparsity bound uses techniques from convex geometry, such as the theory of Newton polytopes and an approximate version of the classical Caratheodory’s Theorem.Our work addresses and partially answers a question of von zur Gathen and Kaltofen [1985] who asked whether a quasi-polynomial bound holds for the sparsity of factors of sparse polynomials.

Forcing and Calculi for Hybrid Logics

Abstract: The definition of institution formalizes the intuitive notion of logic in a category-based setting. Similarly, the concept of stratified institution provides an abstract approach to Kripke semantics. This includes hybrid logics, a type of modal logics expressive enough to allow references to the nodes/states/worlds of the models regarded as relational structures, or multi-graphs. Applications of hybrid logics involve many areas of research, such as computational linguistics, transition systems, knowledge representation, artificial intelligence, biomedical informatics, semantic networks, and ontologies. The present contribution sets a unified foundation for developing formal verification methodologies to reason about Kripke structures by defining proof calculi for a multitude of hybrid logics in the framework of stratified institutions. To prove completeness, the article introduces a forcing technique for stratified institutions with nominal and frame extraction and studies a forcing property based on syntactic consistency. The proof calculus is shown to be complete and the significance of the general results is exhibited on a couple of benchmark examples of hybrid logical systems.

The Log-Approximate-Rank Conjecture Is False

Abstract: We construct a simple and total Boolean function F e f c XOR on 2n variables that has only O(sn) spectral norm, O(n2) approximate rank, and O(n2.5) approximate nonnegative rank. We show it has polynomially large randomized bounded-error communication complexity of Ω(sn). This yields the first exponential gap between the logarithm of the approximate rank and randomized communication complexity for total functions. Thus, F witnesses a refutation of the log-approximate-rank conjecture that was posed by Lee and Shraibman as a very natural analogue for randomized communication of the still unresolved log-rank conjecture for deterministic communication. The best known previous gap for any total function between the two measures is a recent 4th-power separation by Goos et al. Additionally, our function F refutes Grolmusz’s conjecture and a variant of the log-approximate-nonnegative-rank conjecture suggested recently by Kol et al., both of which are implied by the log-approximate-rank conjecture. The complement of F has exponentially large approximate nonnegative rank. This answers a question of Lee [32], showing that approximate nonnegative rank can be exponentially larger than approximate rank. The inner function F also falsifies a conjecture about parity measures of Boolean functions made by Tsang et al. The latter conjecture implied the log-rank conjecture for XOR functions. We are pleased to note that shortly after we published our results, two independent groups of researchers, Anshu et al. and Sinha and de Wolf, used our function F to prove that the quantum-log-rank conjecture is also false by showing that F has Ω(n1/6) quantum communication complexity.

On Small-depth Frege Proofs for Tseitin for Grids

Abstract: We prove that a small-depth Frege refutation of the Tseitin contradiction on the grid requires subexponential size. We conclude that polynomial size Frege refutations of the Tseitin contradiction must use formulas of almost logarithmic depth.

A Simpler and Faster Strongly Polynomial Algorithm for Generalized Flow Maximization

Abstract: We present a new strongly polynomial algorithm for generalized flow maximization that is significantly simpler and faster than the previous strongly polynomial algorithm [34]. For the uncapacitated problem formulation, the complexity bound O(mn(m+n log n)log (n2/m)) improves on the previous estimate by almost a factor O(n2). Even for small numerical parameter values, our running time bound is comparable to the best weakly polynomial algorithms. The key new technical idea is relaxing the primal feasibility conditions. This allows us to work almost exclusively with integral flows, in contrast to all previous algorithms for the problem.

Planar Graph Perfect Matching Is in NC

Abstract: Is perfect matching in NC? That is, is there a deterministic fast parallel algorithm for it? This has been an outstanding open question in theoretical computer science for over three decades, ever since the discovery of RNC perfect matching algorithms. Within this question, the case of planar graphs has remained an enigma: On the one hand, counting the number of perfect matchings is far harder than finding one (the former is #P-complete and the latter is in P), and on the other, for planar graphs, counting has long been known to be in NC whereas finding one has resisted a solution. In this article, we give an NC algorithm for finding a perfect matching in a planar graph. Our algorithm uses the above-stated fact about counting perfect matchings in a crucial way. Our main new idea is an NC algorithm for finding a face of the perfect matching polytope at which a set (which could be polynomially large) of conditions, involving constraints of the polytope, are simultaneously satisfied. Several other ideas are also needed, such as finding, in NC, a point in the interior of the minimum-weight face of this polytope and finding a balanced tight odd set.

Distributed Exact Shortest Paths in Sublinear Time

Abstract: The distributed single-source shortest paths problem is one of the most fundamental and central problems in the message-passing distributed computing. Classical Bellman-Ford algorithm solves it in O(n) time, where n is the number of vertices in the input graph G. Peleg and Rubinovich [49] showed a lower bound of ˜Ω(D + s n) for this problem, where D is the hop-diameter of G. Whether or not this problem can be solved in O(n) time when D is relatively small is a major open question. Despite intensive research [10, 17, 33, 41, 45] that yielded near-optimal algorithms for the approximate variant of this problem, no progress was reported for the original problem. In this article, we answer this question in the affirmative. We devise an algorithm that requires O((n log n)5/6) time, for D e O(s n log n), and O(D1/3 ṡ (n log n)2/3) time, for larger D. This running time is sublinear in n in almost the entire range of parameters, specifically, for D e o(n/ log2 n). We also generalize our result in two directions. One is when edges have bandwidth b ≥ 1, and the other is the s-sources shortest paths problem. For both problems, our algorithm provides bounds that improve upon the previous state-of-the-art in almost the entire range of parameters. In particular, we provide an all-pairs shortest paths algorithm that requires O(n5/3 ṡ log 2/3 n) time, even for b e 1, for all values of D. We also devise the first algorithm with non-trivial complexity guarantees for computing exact shortest paths in the multipass semi-streaming model of computation. From the technical viewpoint, our distributed algorithm computes a hopset G′′ of a skeleton graph G′ of G without first computing G′ itself. We then conduct a Bellman-Ford exploration in G′ ∪ G′′, while computing the required edges of G′ on the fly. As a result, our distributed algorithm computes exactly those edges of G′ that it really needs, rather than computing approximately the entire G′.

Scene Grammars, Factor Graphs, and Belief Propagation

Abstract: We describe a general framework for probabilistic modeling of complex scenes and for inference from ambiguous observations. The approach is motivated by applications in image analysis and is based on the use of priors defined by stochastic grammars. We define a class of grammars that capture relationships between the objects in a scene and provide important contextual cues for statistical inference. The distribution over scenes defined by a probabilistic scene grammar can be represented by a graphical model, and this construction can be used for efficient inference with loopy belief propagation. We show experimental results with two applications. One application involves the reconstruction of binary contour maps. Another application involves detecting and localizing faces in images. In both applications, the same framework leads to robust inference algorithms that can effectively combine local information to reason about a scene.

Semantic Optimization of Conjunctive Queries

Abstract: This work deals with the problem of semantic optimization of the central class of conjunctive queries (CQs). Since CQ evaluation is NP-complete, a long line of research has focussed on identifying fragments of CQs that can be efficiently evaluated. One of the most general restrictions corresponds to generalized hypetreewidth bounded by a fixed constant k ≥ 1; the associated fragment is denoted GHWk. A CQ is semantically in GHWk if it is equivalent to a CQ in GHWk. The problem of checking whether a CQ is semantically in GHWk has been studied in the constraint-free case, and it has been shown to be NP-complete. However, in case the database is subject to constraints such as tuple-generating dependencies (TGDs) that can express, e.g., inclusion dependencies, or equality-generating dependencies (EGDs) that capture, e.g., key dependencies, a CQ may turn out to be semantically in GHWk under the constraints, while not being semantically in GHWk without the constraints. This opens avenues to new query optimization techniques. In this article, we initiate and develop the theory of semantic optimization of CQs under constraints. More precisely, we study the following natural problem: Given a CQ and a set of constraints, is the query semantically in GHWk, for a fixed k ≥ 1, under the constraints, or, in other words, is the query equivalent to one that belongs to GHWk over all those databases that satisfy the constraints? We show that, contrary to what one might expect, decidability of CQ containment is a necessary but not a sufficient condition for the decidability of the problem in question. In particular, we show that checking whether a CQ is semantically in GHW1 is undecidable in the presence of full TGDs (i.e., Datalog rules) or EGDs. In view of the above negative results, we focus on the main classes of TGDs for which CQ containment is decidable and that do not capture the class of full TGDs, i.e., guarded, non-recursive, and sticky sets of TGDs, and show that the problem in question is decidable, while its complexity coincides with the complexity of CQ containment. We also consider key dependencies over unary and binary relations, and we show that the problem in question is decidable in elementary time. Furthermore, we investigate whether being semantically in GHWk alleviates the cost of query evaluation. Finally, in case a CQ is not semantically in GHWk, we discuss how it can be approximated via a CQ that falls in GHWk in an optimal way. Such approximations might help finding “quick” answers to the input query when exact evaluation is intractable.