OpenRaiser/Intern-Atlas huggingface dataset:
Compressive classification and the rare eclipse problem
Venue: arXiv cs.LG 2014
Year: 2014

This paper addresses the fundamental question of when convex sets remain disjoint after random projection. We provide an analysis using ideas from high-dimensional convex geometry. For ellipsoids, we provide a bound in terms of the distance between these ellipsoids and simple functions of their polynomial coefficients. As an application, this theorem provides bounds for compressive classification of convex sets. Rather than assuming that the data to be classified is sparse, our results show that the data can be acquired via very few measurements yet will remain linearly separable. We demonstrate the feasibility of this approach in the context of hyperspectral imaging.
Performance Analysis of Irregular Collective Communication with the Crystal Router Algorithm
Venue: arXiv cs.DC 2014
Year: 2014

In order to achieve exascale performance it is important to detect potential bottlenecks and identify strategies to overcome them. For this, both applications and system software must be analysed and potentially improved. The EU FP7 project Collaborative Research into Exascale Systemware, Tools & Applications (CRESTA) chose the approach to co-design advanced simulation applications and system software as well as development tools. In this paper, we present the results of a co-design activity focused on the simulation code NEK5000 that aims at performance improvements of collective communication operations. We have analysed the algorithms that form the core of NEK5000's communication module in order to assess its viability on recent computer architectures before starting to improve its performance. Our results show that the crystal router algorithm performs well in sparse, irregular collective operations for medium and large processor number but improvements for even larger system sizes of the future will be needed. We sketch the needed improvements, which will make the communication algorithms also beneficial for other applications that need to implement latency-dominated communication schemes with short messages. The latency-optimised communication operations will also become used in a runtime-system providing dynamic load balancing, under development within CRESTA.
Portfolio Selection Under Buy-In Threshold Constraints Using DC Programming and DCA
Venue: arXiv cs.CE 2014
Year: 2014

In matter of Portfolio selection, we consider a generalization of the Markowitz Mean-Variance model which includes buy-in threshold constraints. These constraints limit the amount of capital to be invested in each asset and prevent very small investments in any asset. The new model can be converted into a NP-hard mixed integer quadratic programming problem. The purpose of this paper is to investigate a continuous approach based on DC programming and DCA for solving this new model. DCA is a local continuous approach to solve a wide variety of nonconvex programs for which it provided quite often a global solution and proved to be more robust and efficient than standard methods. Preliminary comparative results of DCA and a classical Branch-and-Bound algorithm will be presented. These results show that DCA is an efficient and promising approach for the considered portfolio selection problem.
Web Search of New Linearized Medical Drug Leads
Venue: arXiv cs.IR 2014
Year: 2014

The Web is a potentially huge source of medical drug leads. But despite the significant amount of multi- dimensional information about drugs, currently commercial search engines accept only linear keyword strings as inputs. This work uses linearized fragments of molecular structures as knowledge representation units to serve as inputs to search engines. It is shown that quite arbitrary fragments are surprisingly free of ambiguity, obtaining relatively small result sets, which are both manageable and rich in novel potential drug leads.
Scalable Steiner Tree for Multicast Communications in Software-Defined Networking
Venue: arXiv cs.NI 2014
Year: 2014

Software-Defined Networking (SDN) enables flexible network resource allocations for traffic engineering, but at the same time the scalability problem becomes more serious since traffic is more difficult to be aggregated. Those crucial issues in SDN have been studied for unicast but have not been explored for multicast traffic, and addressing those issues for multicast is more challenging since the identities and the number of members in a multicast group can be arbitrary. In this paper, therefore, we propose a new multicast tree for SDN, named Branch-aware Steiner Tree (BST). The BST problem is difficult since it needs to jointly minimize the numbers of the edges and the branch nodes in a tree, and we prove that it is NP-Hard and inapproximable within $k$, which denotes the number of group members. We further design an approximation algorithm, called Branch Aware Edge Reduction Algorithm (BAERA), to solve the problem. Simulation results demonstrate that the trees obtained by BAERA are more bandwidth-efficient and scalable than the shortest-path trees and traditional Steiner trees. Most importantly, BAERA is computation-efficient to be deployed in SDN since it can generate a tree on massive networks in small time.
On the hardness of the decoding and the minimum distance problems for rank codes
Venue: arXiv cs.CC 2014
Year: 2014

In this paper we give a randomized reduction for the Rank Syndrome Decoding problem and Rank Minimum Distance problem for rank codes. Our results are based on an embedding from linear codes equipped with Hamming distance unto linear codes over an extension field equipped with the rank metric. We prove that if both previous problems for rank metric are in ZPP = RP$\cap$coRP, then we would have NP=ZPP. We also give complexity results for the respective approximation problems in rank metric.
Polynomial Delay Algorithm for Listing Minimal Edge Dominating sets in Graphs
Venue: arXiv cs.DS 2014
Year: 2014

The Transversal problem, i.e, the enumeration of all the minimal transversals of a hypergraph in output-polynomial time, i.e, in time polynomial in its size and the cumulated size of all its minimal transversals, is a fifty years old open problem, and up to now there are few examples of hypergraph classes where the problem is solved. A minimal dominating set in a graph is a subset of its vertex set that has a non empty intersection with the closed neighborhood of every vertex. It is proved in [M. M. Kanté, V. Limouzy, A. Mary, L. Nourine, On the Enumeration of Minimal Dominating Sets and Related Notions, In Revision 2014] that the enumeration of minimal dominating sets in graphs and the enumeration of minimal transversals in hypergraphs are two equivalent problems. Hoping this equivalence can help to get new insights in the Transversal problem, it is natural to look inside graph classes. It is proved independently and with different techniques in [Golovach et al. - ICALP 2013] and [Kanté et al. - ISAAC 2012] that minimal edge dominating sets in graphs (i.e, minimal dominating sets in line graphs) can be enumerated in incremental output-polynomial time. We provide the first polynomial delay and polynomial space algorithm that lists all the minimal edge dominating sets in graphs, answering an open problem of [Golovach et al. - ICALP 2013]. Besides the result, we hope the used techniques that are a mix of a modification of the well-known Berge's algorithm and a strong use of the structure of line graphs, are of great interest and could be used to get new output-polynomial time algorithms.
Distributed Asynchronous Optimization Framework for the MISO Interference Channel
Venue: arXiv cs.IT 2014
Year: 2014

We study the distributed optimization of transmit strategies in a multiple-input, single-output (MISO) interference channel (IFC). Existing distributed algorithms rely on stricly synchronized update steps by the individual users. They require a global synchronization mechanism and potentially suffer from the synchronization penalty caused by e.g., backhaul communication delays and fixed update sequences. We establish a general optimization framework that allows asynchronous update steps. The users perform their computations at arbitrary instants of time, and do not wait for information that has been sent to them. Based on certain bounds on the amount of asynchronism that is present in the execution of the algorithm, we are able to characterize its convergence. As illustrated by our numerical results, the proposed algorithm can alleviate communication overloads and is not excessively slowed down by neither communication delays, nor by differences in the computation intervals.
Cache-Oblivious VAT-Algorithms
Venue: arXiv cs.DS 2014
Year: 2014

The VAT-model (virtual address translation model) extends the EM-model (external memory model) and takes the cost of address translation in virtual memories into account. In this model, the cost of a single memory access may be logarithmic in the largest address used. We show that the VAT-cost of cache-oblivious algorithms is only by a constant factor larger than their EM-cost; this requires a somewhat more stringent tall cache assumption as for the EM-model.
Constant-factor approximations for Capacitated Arc Routing without triangle inequality
Venue: arXiv cs.DS 2014
Year: 2014

Given an undirected graph with edge costs and edge demands, the Capacitated Arc Routing problem (CARP) asks for minimum-cost routes for equal-capacity vehicles so as to satisfy all demands. Constant-factor polynomial-time approximation algorithms were proposed for CARP with triangle inequality, while CARP was claimed to be NP-hard to approximate within any constant factor in general. Correcting this claim, we show that any factor α approximation for CARP with triangle inequality yields a factor α approximation for the general CARP.
Upgrade of A Robot Workstation for Positioning of Measuring Objects on CMM
Venue: arXiv cs.RO 2014
Year: 2014

In order to decrease the measuring cycle time on the coordinate measuring machine (CMM) a robot workstation for the positioning of measuring objects was created. The application of a simple 5-axis industrial robot enables the positioning of the objects within the working space of CMM and measuring of different surfaces on the same object without human intervention. In this article an upgrade of an existing robot workstation through different design measures is shown. The main goal of this upgrade is to improve the measuring accuracy of the complex robot-CMM system.
Inheritance patterns in citation networks reveal scientific memes
Venue: arXiv cs.SI 2014
Year: 2014

Memes are the cultural equivalent of genes that spread across human culture by means of imitation. What makes a meme and what distinguishes it from other forms of information, however, is still poorly understood. Our analysis of memes in the scientific literature reveals that they are governed by a surprisingly simple relationship between frequency of occurrence and the degree to which they propagate along the citation graph. We propose a simple formalization of this pattern and we validate it with data from close to 50 million publication records from the Web of Science, PubMed Central, and the American Physical Society. Evaluations relying on human annotators, citation network randomizations, and comparisons with several alternative approaches confirm that our formula is accurate and effective, without a dependence on linguistic or ontological knowledge and without the application of arbitrary thresholds or filters.
Shortest reconfiguration paths in the solution space of Boolean formulas
Venue: arXiv cs.CC 2014
Year: 2014

Given a Boolean formula and a satisfying assignment, a flip is an operation that changes the value of a variable in the assignment so that the resulting assignment remains satisfying. We study the problem of computing the shortest sequence of flips (if one exists) that transforms a given satisfying assignment $s$ to another satisfying assignment $t$ of a Boolean formula. Earlier work characterized the complexity of finding any (not necessarily the shortest) sequence of flips from one satisfying assignment to another using Schaefer's framework for classification of Boolean formulas. We build on it to provide a trichotomy for the complexity of finding the shortest sequence of flips and show that it is either in P, NP-complete, or PSPACE-complete. Our result adds to the small set of complexity results known for shortest reconfiguration sequence problems by providing an example where the shortest sequence can be found in polynomial time even though its length is not equal to the symmetric difference of the values of the variables in $s$ and $t$. This is in contrast to all reconfiguration problems studied so far, where polynomial time algorithms for computing the shortest path were known only for cases where the path modified the symmetric difference only.
Collision Tolerant Packet Scheduling for Underwater Acoustic Localization
Venue: arXiv cs.IT 2014
Year: 2014

This article considers the joint problem of packet scheduling and self-localization in an underwater acoustic sensor network where sensor nodes are distributed randomly in an operating area. In terms of packet scheduling, our goal is to minimize the localization time, and to do so we consider two packet transmission schemes, namely a collision-free scheme (CFS), and a collision-tolerant scheme (CTS). The required localization time is formulated for these schemes, and through analytical results and numerical examples their performances are shown to be generally comparable. However, when the packet duration is short (as is the case for a localization packet), and the operating area is large (above 3km in at least one dimension), the collision-tolerant scheme requires a smaller localization time than the collision-free scheme. After gathering enough measurements, an iterative Gauss-Newton algorithm is employed by each sensor node for self-localization, and the Cramer Rao lower bound is evaluated as a benchmark. Although CTS consumes more energy for packet transmission, it provides a better localization accuracy. Additionally, in this scheme the anchor nodes work independently of each other, and can operate asynchronously which leads to a simplified implementation.
An effective AHP-based metaheuristic approach to solve supplier selection problem
Venue: arXiv cs.NE 2014
Year: 2014

The supplier selection problem is based on electing the best supplier from a group of pre-specified candidates, is identified as a Multi Criteria Decision Making (MCDM), is proportionately significant in terms of qualitative and quantitative attributes. It is a fundamental issue to achieve a trade-off between such quantifiable and unquantifiable attributes with an aim to accomplish the best solution to the abovementioned problem. This article portrays a metaheuristic based optimization model to solve this NP-Complete problem. Initially the Analytic Hierarchy Process (AHP) is implemented to generate an initial feasible solution of the problem. Thereafter a Simulated Annealing (SA) algorithm is exploited to improve the quality of the obtained solution. The Taguchi robust design method is exploited to solve the critical issues on the subject of the parameter selection of the SA technique. In order to verify the proposed methodology the numerical results are demonstrated based on tangible industry data.
Covering problems in edge- and node-weighted graphs
Venue: arXiv cs.DS 2014
Year: 2014

This paper discusses the graph covering problem in which a set of edges in an edge- and node-weighted graph is chosen to satisfy some covering constraints while minimizing the sum of the weights. In this problem, because of the large integrality gap of a natural linear programming (LP) relaxation, LP rounding algorithms based on the relaxation yield poor performance. Here we propose a stronger LP relaxation for the graph covering problem. The proposed relaxation is applied to designing primal-dual algorithms for two fundamental graph covering problems: the prize-collecting edge dominating set problem and the multicut problem in trees. Our algorithms are an exact polynomial-time algorithm for the former problem, and a 2-approximation algorithm for the latter problem, respectively. These results match the currently known best results for purely edge-weighted graphs.
Big Data: Overview
Venue: arXiv cs.OH 2014
Year: 2014

Big data is data that exceeds the processing capacity of traditional databases. The data is too big to be processed by a single machine. New and innovative methods are required to process and store such large volumes of data. This paper provides an overview on big data, its importance in our live and some technologies to handle big data.
Information Hiding and Attacks : Review
Venue: arXiv cs.CR 2014
Year: 2014

Information Hiding is considered very important part of our lives. There exist many techniques for securing the information. This paper briefs on the techniques for information hiding and the potential threats to those methods. This paper briefs about cryptanalysis and stegananlysis, two methods for breaching into the security methods.
Factor Complexity of S-adic sequences generated by the Arnoux-Rauzy-Poincaré Algorithm
Venue: arXiv cs.DM 2014
Year: 2014

The Arnoux-Rauzy-Poincaré multidimensional continued fraction algorithm is obtained by combining the Arnoux-Rauzy and Poincaré algorithms. It is a generalized Euclidean algorithm. Its three-dimensional linear version consists in subtracting the sum of the two smallest entries to the largest if possible (Arnoux-Rauzy step), and otherwise, in subtracting the smallest entry to the median and the median to the largest (the Poincaré step), and by performing when possible Arnoux-Rauzy steps in priority. After renormalization it provides a piecewise fractional map of the standard $2$-simplex. We study here the factor complexity of its associated symbolic dynamical system, defined as an $S$-adic system. It is made of infinite words generated by the composition of sequences of finitely many substitutions, together with some restrictions concerning the allowed sequences of substitutions expressed in terms of a regular language. Here, the substitutions are provided by the matrices of the linear version of the algorithm. We give an upper bound for the linear growth of the factor complexity. We then deduce the convergence of the associated algorithm by unique ergodicity.
Broder's Chain Is Not Rapidly Mixing
Venue: arXiv cs.DM 2014
Year: 2014

We prove that Broder's Markov chain for approximate sampling near-perfect and perfect matchings is not rapidly mixing for Hamiltonian, regular, threshold and planar bipartite graphs, filling a gap in the literature. In the second part we experimentally compare Broder's chain with the Markov chain by Jerrum, Sinclair and Vigoda from 2004. For the first time, we provide a systematic experimental investigation of mixing time bounds for these Markov chains. We observe that the exact total mixing time is in many cases significantly lower than known upper bounds using canonical path or multicommodity flow methods, even if the structure of an underlying state graph is known. In contrast we observe comparatively tighter upper bounds using spectral gaps.
Strong Divergence of Reconstruction Procedures for the Paley-Wiener Space $\mathcal{PW}^1_π$ and the Hardy Space $\mathcal{H}^1$
Venue: arXiv cs.IT 2014
Year: 2014

Previous results on certain sampling series have left open if divergence only occurs for certain subsequences or, in fact, in the limit. Here we prove that divergence occurs in the limit. We consider three canonical reconstruction methods for functions in the Paley-Wiener space $\mathcal{PW}^1_π$. For each of these we prove an instance when the reconstruction diverges in the limit. This is a much stronger statement than previous results that provide only $\limsup$ divergence. We also address reconstruction for functions in the Hardy space $\mathcal{H}^1$ and show that for any subsequence of the natural numbers there exists a function in $\mathcal{H}^1$ for which reconstruction diverges in $\limsup$. For two of these sampling series we show that when divergence occurs, the sampling series has strong oscillations so that the maximum and the minimum tend to positive and negative infinity. Our results are of interest in functional analysis because they go beyond the type of result that can be obtained using the Banach-Steinhaus Theorem. We discuss practical implications of this work; in particular the work shows that methods using specially chosen subsequences of reconstructions cannot yield convergence for the Paley-Wiener Space $\mathcal{PW}^1_π$.
A characterization of eventually periodicity
Venue: arXiv cs.CC 2014
Year: 2014

In this article, we show that the Kamae-Xue complexity function for an infinite sequence classifies eventual periodicity completely. We prove that an infinite binary word $x_1x_2 \cdots $ is eventually periodic if and only if $Σ(x_1x_2\cdots x_n)/n^3$ has a positive limit, where $Σ(x_1x_2\cdots x_n)$ is the sum of the squares of all the numbers of appearance of finite words in $x_1 x_2 \cdots x_n$, which was introduced by Kamae-Xue as a criterion of randomness in the sense that $x_1x_2\cdots x_n$ is more random if $Σ(x_1x_2\cdots x_n)$ is smaller. In fact, it is known that the lower limit of $Σ(x_1x_2\cdots x_n) /n^2 $ is at least 3/2 for any sequence $x_1x_2 \cdots$, while the limit exists as 3/2 almost surely for the $(1/2,1/2)$ product measure. For the other extreme, the upper limit of $Σ(x_1x_2\cdots x_n)/n^3$ is bounded by 1/3. There are sequences which are not eventually periodic but the lower limit of $Σ(x_1x_2\cdots x_n)/n^3$ is positive, while the limit does not exist.
Efficient Decoding Algorithms for the Compute-and-Forward Strategy
Venue: arXiv cs.IT 2014
Year: 2014

We address in this paper decoding aspects of the Compute-and-Forward (CF) physical-layer network coding strategy. It is known that the original decoder for the CF is asymptotically optimal. However, its performance gap to optimal decoders in practical settings are still not known. In this work, we develop and assess the performance of novel decoding algorithms for the CF operating in the multiple access channel. For the fading channel, we analyze the ML decoder and develop a novel diophantine approximation-based decoding algorithm showed numerically to outperform the original CF decoder. For the Gaussian channel, we investigate the maximum a posteriori (MAP) decoder. We derive a novel MAP decoding metric and develop practical decoding algorithms proved numerically to outperform the original one.
PReaCH: A Fast Lightweight Reachability Index using Pruning and Contraction Hierarchies
Venue: arXiv cs.DS 2014
Year: 2014

We develop the data structure PReaCH (for Pruned Reachability Contraction Hierarchies) which supports reachability queries in a directed graph, i.e., it supports queries that ask whether two nodes in the graph are connected by a directed path. PReaCH adapts the contraction hierarchy speedup techniques for shortest path queries to the reachability setting. The resulting approach is surprisingly simple and guarantees linear space and near linear preprocessing time. Orthogonally to that, we improve existing pruning techniques for the search by gathering more information from a single DFS-traversal of the graph. PReaCH-indices significantly outperform previous data structures with comparable preprocessing cost. Methods with faster queries need significantly more preprocessing time in particular for the most difficult instances.