305 research outputs found

    Classical and quantum algorithms for scaling problems

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    This thesis is concerned with scaling problems, which have a plethora of connections to different areas of mathematics, physics and computer science. Although many structural aspects of these problems are understood by now, we only know how to solve them efficiently in special cases.We give new algorithms for non-commutative scaling problems with complexity guarantees that match the prior state of the art. To this end, we extend the well-known (self-concordance based) interior-point method (IPM) framework to Riemannian manifolds, motivated by its success in the commutative setting. Moreover, the IPM framework does not obviously suffer from the same obstructions to efficiency as previous methods. It also yields the first high-precision algorithms for other natural geometric problems in non-positive curvature.For the (commutative) problems of matrix scaling and balancing, we show that quantum algorithms can outperform the (already very efficient) state-of-the-art classical algorithms. Their time complexity can be sublinear in the input size; in certain parameter regimes they are also optimal, whereas in others we show no quantum speedup over the classical methods is possible. Along the way, we provide improvements over the long-standing state of the art for searching for all marked elements in a list, and computing the sum of a list of numbers.We identify a new application in the context of tensor networks for quantum many-body physics. We define a computable canonical form for uniform projected entangled pair states (as the solution to a scaling problem), circumventing previously known undecidability results. We also show, by characterizing the invariant polynomials, that the canonical form is determined by evaluating the tensor network contractions on networks of bounded size

    LIPIcs, Volume 261, ICALP 2023, Complete Volume

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    LIPIcs, Volume 261, ICALP 2023, Complete Volum

    Geometric Inhomogeneous Random Graphs for Algorithm Engineering

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    The design and analysis of graph algorithms is heavily based on the worst case. In practice, however, many algorithms perform much better than the worst case would suggest. Furthermore, various problems can be tackled more efficiently if one assumes the input to be, in a sense, realistic. The field of network science, which studies the structure and emergence of real-world networks, identifies locality and heterogeneity as two frequently occurring properties. A popular model that captures these properties are geometric inhomogeneous random graphs (GIRGs), which is a generalization of hyperbolic random graphs (HRGs). Aside from their importance to network science, GIRGs can be an immensely valuable tool in algorithm engineering. Since they convincingly mimic real-world networks, guarantees about quality and performance of an algorithm on instances of the model can be transferred to real-world applications. They have model parameters to control the amount of heterogeneity and locality, which allows to evaluate those properties in isolation while keeping the rest fixed. Moreover, they can be efficiently generated which allows for experimental analysis. While realistic instances are often rare, generated instances are readily available. Furthermore, the underlying geometry of GIRGs helps to visualize the network, e.g.,~for debugging or to improve understanding of its structure. The aim of this work is to demonstrate the capabilities of geometric inhomogeneous random graphs in algorithm engineering and establish them as routine tools to replace previous models like the Erd\H{o}s-R{\\u27e}nyi model, where each edge exists with equal probability. We utilize geometric inhomogeneous random graphs to design, evaluate, and optimize efficient algorithms for realistic inputs. In detail, we provide the currently fastest sequential generator for GIRGs and HRGs and describe algorithms for maximum flow, directed spanning arborescence, cluster editing, and hitting set. For all four problems, our implementations beat the state-of-the-art on realistic inputs. On top of providing crucial benchmark instances, GIRGs allow us to obtain valuable insights. Most notably, our efficient generator allows us to experimentally show sublinear running time of our flow algorithm, investigate the solution structure of cluster editing, complement our benchmark set of arborescence instances with a density for which there are no real-world networks available, and generate networks with adjustable locality and heterogeneity to reveal the effects of these properties on our algorithms

    RankSEG: A Consistent Ranking-based Framework for Segmentation

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    Segmentation has emerged as a fundamental field of computer vision and natural language processing, which assigns a label to every pixel/feature to extract regions of interest from an image/text. To evaluate the performance of segmentation, the Dice and IoU metrics are used to measure the degree of overlap between the ground truth and the predicted segmentation. In this paper, we establish a theoretical foundation of segmentation with respect to the Dice/IoU metrics, including the Bayes rule and Dice-/IoU-calibration, analogous to classification-calibration or Fisher consistency in classification. We prove that the existing thresholding-based framework with most operating losses are not consistent with respect to the Dice/IoU metrics, and thus may lead to a suboptimal solution. To address this pitfall, we propose a novel consistent ranking-based framework, namely RankDice/RankIoU, inspired by plug-in rules of the Bayes segmentation rule. Three numerical algorithms with GPU parallel execution are developed to implement the proposed framework in large-scale and high-dimensional segmentation. We study statistical properties of the proposed framework. We show it is Dice-/IoU-calibrated, and its excess risk bounds and the rate of convergence are also provided. The numerical effectiveness of RankDice/mRankDice is demonstrated in various simulated examples and Fine-annotated CityScapes, Pascal VOC and Kvasir-SEG datasets with state-of-the-art deep learning architectures.Comment: 50 page

    LIPIcs, Volume 274, ESA 2023, Complete Volume

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    LIPIcs, Volume 274, ESA 2023, Complete Volum

    Pliability and approximating max-CSPs

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    We identify a sufficient condition, treewidth-pliability, that gives a polynomial-time algorithm for an arbitrarily good approximation of the optimal value in a large class of Max-2-CSPs parameterised by the class of allowed constraint graphs (with arbitrary constraints on an unbounded alphabet). Our result applies more generally to the maximum homomorphism problem between two rational-valued structures. The condition unifies the two main approaches for designing a polynomial-time approximation scheme. One is Baker’s layering technique, which applies to sparse graphs such as planar or excluded-minor graphs. The other is based on Szemer´edi’s regularity lemma and applies to dense graphs. We extend the applicability of both techniques to new classes of Max-CSPs. On the other hand, we prove that the condition cannot be used to find solutions (as opposed to approximating the optimal value) in general. Treewidth-pliability turns out to be a robust notion that can be defined in several equivalent ways, including characterisations via size, treedepth, or the Hadwiger number. We show connections to the notions of fractional-treewidth-fragility from structural graph theory, hyperfiniteness from the area of property testing, and regularity partitions from the theory of dense graph limits. These may be of independent interest. In particular we show that a monotone class of graphs is hyperfinite if and only if it is fractionallytreewidth-fragile and has bounded degree

    Modern Cryptography Volume 1

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    This open access book systematically explores the statistical characteristics of cryptographic systems, the computational complexity theory of cryptographic algorithms and the mathematical principles behind various encryption and decryption algorithms. The theory stems from technology. Based on Shannon's information theory, this book systematically introduces the information theory, statistical characteristics and computational complexity theory of public key cryptography, focusing on the three main algorithms of public key cryptography, RSA, discrete logarithm and elliptic curve cryptosystem. It aims to indicate what it is and why it is. It systematically simplifies and combs the theory and technology of lattice cryptography, which is the greatest feature of this book. It requires a good knowledge in algebra, number theory and probability statistics for readers to read this book. The senior students majoring in mathematics, compulsory for cryptography and science and engineering postgraduates will find this book helpful. It can also be used as the main reference book for researchers in cryptography and cryptographic engineering areas

    LIPIcs, Volume 244, ESA 2022, Complete Volume

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    LIPIcs, Volume 244, ESA 2022, Complete Volum

    Size bounds for algebraic and semialgebraic proof systems

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    This thesis concerns the proof complexity of algebraic and semialgebraic proof systems Polynomial Calculus, Sums-of-Squares and Sherali-Adams. The most studied complexity measure for these systems is the degree of the proofs. This thesis concentrates on other possible complexity measures of interest to proof complexity, monomial-size and bit-complexity. We aim to showcase that there is a reasonably well-behaved theory for these measures also. Firstly we tie the complexity measures of degree and monomial size together by proving a size-degree trade-off for Sums-of-Squares and Sherali-Adams. We show that if there is a refutation with at most s many monomials, then there is a refutation whose degree is of order square root of n log s plus k, where k is the maximum degree of the constraints and n is the number of variables. For Polynomial Calculus similar trade-off was obtained earlier by Impagliazzo, Pudlák and Sgall. Secondly we prove a feasible interpolation property for all three systems. We show that for each system there is a polynomial time algorithm that given two sets P(x,z) and Q(y,z) of polynomial constraints in disjoint sequences x,y and z of variables, a refutation of the union of P(x,z) and Q(y,z), and an assignment a to the z-variables, finds either a refutation of P(x,a) or a refutation of Q(y,a). Finally we consider the relation between monomial-size and bit-complexity in Polynomial Calculus and Sums-of-Squares. We show that there is an unsatisfiable set of polynomial constraints that has both Polynomial Calculus and Sums-of-Squares refutations of polynomial monomial-size, but for which any Polynomial Calculus or Sums-of-Squares refutation requires exponential bit-complexity. Besides the emphasis on complexity measures other than degree, another unifying theme in all the three results is the use of semantic characterizations of resource-bounded proofs and refutations. All results make heavy use of the completeness properties of such characterizations. All in all, the work on these semantic characterizations presents itself as the fourth central contribution of this thesis.Aquesta tesi tracta de la complexitat de les proves en els sistemes de prova algebraics i semialgebraics Càlcul Polinomial (Polynomial Calculus), Sumes de Quadrats (Sums of Squares), i Sherali-Adams. La mesura de complexitat més estudiada per a aquests sistemes és el grau dels polinomis. Aquesta tesi se centra en altres possibles mesures de complexitat d'interès per a la complexitat de proves: el nombre de monomis i la longitud de representació en nombre de bits. Pretenem demostrar que aquestes mesures admeten una teoria comparable i complementària a la teoria del grau com a mesura de complexitat. En primer lloc, establim una relació entre les mesures de grau i de nombre de monomis demostrant una propietat d'intercanvi (trade-off) entre les dues mesures per als sistemes Sumes de Quadrats i Sherali-Adams. Demostrem que si hi ha una refutació amb com a màxim s monomis, aleshores hi ha una refutació el grau de la qual és d'ordre de l'arrel quadrada de n.log(s) més k, on k és el grau màxim de les restriccions i n és el nombre de variables. Per al Càlcul Polinomial, una propietat d'intercanvi similar va ser obtinguda per Impagliazzo, Pudlák i Sgall. En segon lloc, demostrem que els tres sistemes admeten la propietat d'interpolació eficient. Mostrem que, per a cadascun dels sistemes, hi ha un algorisme de temps polinomial que, donat dos conjunts P(x,z) i Q(y,z) de restriccions polinomials en successions disjuntes de variables x, y i z, donada una refutació de la unió de les restriccions de P(x,z) i Q(y,z), i donada una assignació per a les variables z, troba una refutació de P(x,a) o una refutació de Q(y,a). Finalment considerem la relació entre el nombre de monomis i la longitud de representació en bits per al Càlcul Polinomial i per a Sumes de Quadrats. Mostrem que hi ha un conjunt insatisfactible de restriccions polinomials que admet refutacions tant en Càlcul Polinomial com en Sumes de Quadrats amb un nombre polinòmic de monomis, però per a les quals qualsevol refutació en Càlcul Polinomial o en Sumes de Quadrats requereix complexitat en nombre de bits exponencial. A més de l'èmfasi en les mesures de complexitat diferents del grau, un altre tema unificador en els tres resultats és l'ús de certes caracteritzacions semàntiques de proves i refutacions limitades en recursos. Tots els resultats fan un ús clau de la propietat de completesa d'aquestes caracteritzacions. Amb tot, el treball sobre aquestes caracteritzacions semàntiques es presenta com la quarta aportació central d'aquesta tesi.Postprint (published version

    Testing vertex connectivity of bowtie 1-plane graphs

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    A separating set of a connected graph GG is a set of vertices SS such that GSG-S is disconnected. SS is a minimum separating set of GG if there is no separating set of GG with fewer vertices than SS. The size of a minimum separating set of GG is called the vertex connectivity of GG. A separating set of GG that is a cycle is called a separating cycle of GG. Let GG be a planar graph with a given planar embedding. Let Λ(G)\Lambda(G) be a supergraph of GG obtained by inserting a face vertex in each face of GG and connecting the face vertex to all vertices on the boundary of the face. It is well known that a set SS is a minimum separating set of a planar graph GG if and only if the vertices of SS can be connected together using face vertices to get a cycle XX of length 2S2|S| that is separating in Λ(G)\Lambda(G). We extend this correspondence between separating sets and separating cycles from planar graphs to the class of bowtie 1-plane graphs. These are graphs that are embedded on the plane such that each edge is crossed at most once by another edge, and the endpoints of each such crossing induce either K4K_4, K4{e}K_4 \setminus \{e\} or C4C_4. Using this result, we give an algorithm to compute the vertex connectivity of a bowtie 1-plane graph in linear time
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