OpenRaiser/Intern-Atlas huggingface dataset:
A Model-Based Frequency Constraint for Mining Associations from Transaction Data
Venue: arXiv cs.DB 2008
Year: 2008

Mining frequent itemsets is a popular method for finding associated items in databases. For this method, support, the co-occurrence frequency of the items which form an association, is used as the primary indicator of the associations's significance. A single user-specified support threshold is used to decided if associations should be further investigated. Support has some known problems with rare items, favors shorter itemsets and sometimes produces misleading associations. In this paper we develop a novel model-based frequency constraint as an alternative to a single, user-specified minimum support. The constraint utilizes knowledge of the process generating transaction data by applying a simple stochastic mixture model (the NB model) which allows for transaction data's typically highly skewed item frequency distribution. A user-specified precision threshold is used together with the model to find local frequency thresholds for groups of itemsets. Based on the constraint we develop the notion of NB-frequent itemsets and adapt a mining algorithm to find all NB-frequent itemsets in a database. In experiments with publicly available transaction databases we show that the new constraint provides improvements over a single minimum support threshold and that the precision threshold is more robust and easier to set and interpret by the user.
A Local Mean Field Analysis of Security Investments in Networks
Venue: arXiv cs.GT 2008
Year: 2008

Getting agents in the Internet, and in networks in general, to invest in and deploy security features and protocols is a challenge, in particular because of economic reasons arising from the presence of network externalities. Our goal in this paper is to carefully model and quantify the impact of such externalities on the investment in, and deployment of, security features and protocols in a network. Specifically, we study a network of interconnected agents, which are subject to epidemic risks such as those caused by propagating viruses and worms, and which can decide whether or not to invest some amount to self-protect and deploy security solutions. We make three contributions in the paper. First, we introduce a general model which combines an epidemic propagation model with an economic model for agents which captures network effects and externalities. Second, borrowing ideas and techniques used in statistical physics, we introduce a Local Mean Field (LMF) model, which extends the standard mean-field approximation to take into account the correlation structure on local neighborhoods. Third, we solve the LMF model in a network with externalities, and we derive analytic solutions for sparse random graphs, for which we obtain asymptotic results. We explicitly identify the impact of network externalities on the decision to invest in and deploy security features. In other words, we identify both the economic and network properties that determine the adoption of security technologies.
Robustness and Regularization of Support Vector Machines
Venue: arXiv cs.LG 2008
Year: 2008

We consider regularized support vector machines (SVMs) and show that they are precisely equivalent to a new robust optimization formulation. We show that this equivalence of robust optimization and regularization has implications for both algorithms, and analysis. In terms of algorithms, the equivalence suggests more general SVM-like algorithms for classification that explicitly build in protection to noise, and at the same time control overfitting. On the analysis front, the equivalence of robustness and regularization, provides a robust optimization interpretation for the success of regularized SVMs. We use the this new robustness interpretation of SVMs to give a new proof of consistency of (kernelized) SVMs, thus establishing robustness as the reason regularized SVMs generalize well.
Geographic Information Systems in Evaluation and Visualization of Construction Schedule
Venue: arXiv cs.OH 2008
Year: 2008

Commercially available scheduling tools such as Primavera and Microsoft Project fail to provide information pertaining to the spatial aspects of construction project. A methodology using geographical information systems (GIS) is developed to represent spatial aspects of the construction progress graphically by synchronizing it with construction schedule. The spatial aspects are depicted by 3D model developed in AutoCAD and construction schedule is generated using Microsoft Excel. Spatial and scheduling information are linked together into the GIS environment (ArcGIS). The GIS-based system developed in this study may help in better understanding the schedule along with its spatial aspects.
Distributed Averaging in the presence of a Sparse Cut
Venue: arXiv cs.DC 2008
Year: 2008

We consider the question of averaging on a graph that has one sparse cut separating two subgraphs that are internally well connected. While there has been a large body of work devoted to algorithms for distributed averaging, nearly all algorithms involve only {\it convex} updates. In this paper, we suggest that {\it non-convex} updates can lead to significant improvements. We do so by exhibiting a decentralized algorithm for graphs with one sparse cut that uses non-convex averages and has an averaging time that can be significantly smaller than the averaging time of known distributed algorithms, such as those of \cite{tsitsiklis, Boyd}. We use stochastic dominance to prove this result in a way that may be of independent interest.
On the cubicity of AT-free graphs and circular-arc graphs
Venue: arXiv cs.DM 2008
Year: 2008

A unit cube in $k$ dimensions ($k$-cube) is defined as the the Cartesian product $R_1\times R_2\times...\times R_k$ where $R_i$(for $1\leq i\leq k$) is a closed interval of the form $[a_i,a_i+1]$ on the real line. A graph $G$ on $n$ nodes is said to be representable as the intersection of $k$-cubes (cube representation in $k$ dimensions) if each vertex of $G$ can be mapped to a $k$-cube such that two vertices are adjacent in $G$ if and only if their corresponding $k$-cubes have a non-empty intersection. The \emph{cubicity} of $G$ denoted as $\cubi(G)$ is the minimum $k$ for which $G$ can be represented as the intersection of $k$-cubes. We give an $O(bw\cdot n)$ algorithm to compute the cube representation of a general graph $G$ in $bw+1$ dimensions given a bandwidth ordering of the vertices of $G$, where $bw$ is the \emph{bandwidth} of $G$. As a consequence, we get $O(Δ)$ upper bounds on the cubicity of many well-known graph classes such as AT-free graphs, circular-arc graphs and co-comparability graphs which have $O(Δ)$ bandwidth. Thus we have: 1) $\cubi(G)\leq 3Δ-1$, if $G$ is an AT-free graph. 2) $\cubi(G)\leq 2Δ+1$, if $G$ is a circular-arc graph. 3) $\cubi(G)\leq 2Δ$, if $G$ is a co-comparability graph. Also for these graph classes, there are constant factor approximation algorithms for bandwidth computation that generate orderings of vertices with $O(Δ)$ width. We can thus generate the cube representation of such graphs in $O(Δ)$ dimensions in polynomial time.
Approaching the Capacity of Wireless Networks through Distributed Interference Alignment
Venue: arXiv cs.IT 2008
Year: 2008

Recent results establish the optimality of interference alignment to approach the Shannon capacity of interference networks at high SNR. However, the extent to which interference can be aligned over a finite number of signalling dimensions remains unknown. Another important concern for interference alignment schemes is the requirement of global channel knowledge. In this work we provide examples of iterative algorithms that utilize the reciprocity of wireless networks to achieve interference alignment with only local channel knowledge at each node. These algorithms also provide numerical insights into the feasibility of interference alignment that are not yet available in theory.
A Component Based Heuristic Search method with Adaptive Perturbations for Hospital Personnel Scheduling
Venue: arXiv cs.NE 2008
Year: 2008

Nurse rostering is a complex scheduling problem that affects hospital personnel on a daily basis all over the world. This paper presents a new component-based approach with adaptive perturbations, for a nurse scheduling problem arising at a major UK hospital. The main idea behind this technique is to decompose a schedule into its components (i.e. the allocated shift pattern of each nurse), and then mimic a natural evolutionary process on these components to iteratively deliver better schedules. The worthiness of all components in the schedule has to be continuously demonstrated in order for them to remain there. This demonstration employs a dynamic evaluation function which evaluates how well each component contributes towards the final objective. Two perturbation steps are then applied: the first perturbation eliminates a number of components that are deemed not worthy to stay in the current schedule; the second perturbation may also throw out, with a low level of probability, some worthy components. The eliminated components are replenished with new ones using a set of constructive heuristics using local optimality criteria. Computational results using 52 data instances demonstrate the applicability of the proposed approach in solving real-world problems.
Product theorems via semidefinite programming
Venue: arXiv cs.CC 2008
Year: 2008

The tendency of semidefinite programs to compose perfectly under product has been exploited many times in complexity theory: for example, by Lovasz to determine the Shannon capacity of the pentagon; to show a direct sum theorem for non-deterministic communication complexity and direct product theorems for discrepancy; and in interactive proof systems to show parallel repetition theorems for restricted classes of games. Despite all these examples of product theorems--some going back nearly thirty years--it was only recently that Mittal and Szegedy began to develop a general theory to explain when and why semidefinite programs behave perfectly under product. This theory captured many examples in the literature, but there were also some notable exceptions which it could not explain--namely, an early parallel repetition result of Feige and Lovasz, and a direct product theorem for the discrepancy method of communication complexity by Lee, Shraibman, and Spalek. We extend the theory of Mittal and Szegedy to explain these cases as well. Indeed, to the best of our knowledge, our theory captures all examples of semidefinite product theorems in the literature.
Common Permutation Problem
Venue: arXiv cs.CC 2008
Year: 2008

In this paper we show that the following problem is NP-complete: Given an alphabet $Σ$ and two strings over $Σ$, the question is whether there exists a permutation of $Σ$ which is a subsequence of both of the given strings.
Discrete Frequency Selection of Frame-Based Stochastic Real-Time Tasks
Venue: arXiv cs.OS 2008
Year: 2008

Energy-efficient real-time task scheduling has been actively explored in the past decade. Different from the past work, this paper considers schedulability conditions for stochastic real-time tasks. A schedulability condition is first presented for frame-based stochastic real-time tasks, and several algorithms are also examined to check the schedulability of a given strategy. An approach is then proposed based on the schedulability condition to adapt a continuous-speed-based method to a discrete-speed system. The approach is able to stay as close as possible to the continuous-speed-based method, but still guaranteeing the schedulability. It is shown by simulations that the energy saving can be more than 20% for some system configurations
The aDORe Federation Architecture
Venue: arXiv cs.DL 2008
Year: 2008

The need to federate repositories emerges in two distinctive scenarios. In one scenario, scalability-related problems in the operation of a repository reach a point beyond which continued service requires parallelization and hence federation of the repository infrastructure. In the other scenario, multiple distributed repositories manage collections of interest to certain communities or applications, and federation is an approach to present a unified perspective across these repositories. The high-level, 3-Tier aDORe federation architecture can be used as a guideline to federate repositories in both cases. This paper describes the architecture, consisting of core interfaces for federated repositories in Tier-1, two shared infrastructure components in Tier-2, and a single-point of access to the federation in Tier-3. The paper also illustrates two large-scale deployments of the aDORe federation architecture: the aDORe Archive repository (over 100,000,000 digital objects) at the Los Alamos National Laboratory and the Ghent University Image Repository federation (multiple terabytes of image files).
Binary Decision Diagrams for Affine Approximation
Venue: arXiv cs.LO 2008
Year: 2008

Selman and Kautz's work on ``knowledge compilation'' established how approximation (strengthening and/or weakening) of a propositional knowledge-base can be used to speed up query processing, at the expense of completeness. In this classical approach, querying uses Horn over- and under-approximations of a given knowledge-base, which is represented as a propositional formula in conjunctive normal form (CNF). Along with the class of Horn functions, one could imagine other Boolean function classes that might serve the same purpose, owing to attractive deduction-computational properties similar to those of the Horn functions. Indeed, Zanuttini has suggested that the class of affine Boolean functions could be useful in knowledge compilation and has presented an affine approximation algorithm. Since CNF is awkward for presenting affine functions, Zanuttini considers both a sets-of-models representation and the use of modulo 2 congruence equations. In this paper, we propose an algorithm based on reduced ordered binary decision diagrams (ROBDDs). This leads to a representation which is more compact than the sets of models and, once we have established some useful properties of affine Boolean functions, a more efficient algorithm.
Private Handshakes
Venue: arXiv cs.CR 2008
Year: 2008

Private handshaking allows pairs of users to determine which (secret) groups they are both a member of. Group membership is kept secret to everybody else. Private handshaking is a more private form of secret handshaking, because it does not allow the group administrator to trace users. We extend the original definition of a handshaking protocol to allow and test for membership of multiple groups simultaneously. We present simple and efficient protocols for both the single group and multiple group membership case. Private handshaking is a useful tool for mutual authentication, demanded by many pervasive applications (including RFID) for privacy. Our implementations are efficient enough to support such usually resource constrained scenarios.
From Random Graph to Small World by Wandering
Venue: arXiv cs.DS 2008
Year: 2008

Numerous studies show that most known real-world complex networks share similar properties in their connectivity and degree distribution. They are called small worlds. This article gives a method to turn random graphs into Small World graphs by the dint of random walks.
Outage behavior of slow fading channels with power control using noisy quantized CSIT
Venue: arXiv cs.IT 2008
Year: 2008

The topic of this study is the outage behavior of multiple-antenna slow fading channels with quantized feedback and partial power control. A fixed-rate communication system is considered. It is known from the literature that with error-free feedback, the outage-optimal quantizer for power control has a circular structure. Moreover, the diversity gain of the system increases polynomially with the cardinality of the power control codebook. Here, a similar system is studied, but when the feedback link is error-prone. We prove that in the high-SNR regime, the optimal quantizer structure with noisy feedback is still circular and the optimal Voronoi regions are contiguous non-zero probability intervals. Furthermore, the optimal power control codebook resembles a channel optimized scalar quantizer (COSQ), i.e., the Voronoi regions merge with erroneous feedback information. Using a COSQ, the outage performance of the system is superior to that of a no-feedback scheme. However, asymptotic analysis shows that the diversity gain of the system is the same as a no-CSIT scheme if there is a non-zero and non-vanishing feedback error probability.
Kalman Filtered Compressed Sensing
Venue: arXiv cs.IT 2008
Year: 2008

We consider the problem of reconstructing time sequences of spatially sparse signals (with unknown and time-varying sparsity patterns) from a limited number of linear "incoherent" measurements, in real-time. The signals are sparse in some transform domain referred to as the sparsity basis. For a single spatial signal, the solution is provided by Compressed Sensing (CS). The question that we address is, for a sequence of sparse signals, can we do better than CS, if (a) the sparsity pattern of the signal's transform coefficients' vector changes slowly over time, and (b) a simple prior model on the temporal dynamics of its current non-zero elements is available. The overall idea of our solution is to use CS to estimate the support set of the initial signal's transform vector. At future times, run a reduced order Kalman filter with the currently estimated support and estimate new additions to the support set by applying CS to the Kalman innovations or filtering error (whenever it is "large").
On the Influence of Selection Operators on Performances in Cellular Genetic Algorithms
Venue: arXiv cs.AI 2008
Year: 2008

In this paper, we study the influence of the selective pressure on the performance of cellular genetic algorithms. Cellular genetic algorithms are genetic algorithms where the population is embedded on a toroidal grid. This structure makes the propagation of the best so far individual slow down, and allows to keep in the population potentially good solutions. We present two selective pressure reducing strategies in order to slow down even more the best solution propagation. We experiment these strategies on a hard optimization problem, the quadratic assignment problem, and we show that there is a value for of the control parameter for both which gives the best performance. This optimal value does not find explanation on only the selective pressure, measured either by take over time and diversity evolution. This study makes us conclude that we need other tools than the sole selective pressure measures to explain the performances of cellular genetic algorithms.
Efficient Spacetime Meshing with Nonlocal Cone Constraints
Venue: arXiv cs.CG 2008
Year: 2008

Spacetime Discontinuous Galerkin (DG) methods are used to solve hyperbolic PDEs describing wavelike physical phenomena. When the PDEs are nonlinear, the speed of propagation of the phenomena, called the wavespeed, at any point in the spacetime domain is computed as part of the solution. We give an advancing front algorithm to construct a simplicial mesh of the spacetime domain suitable for DG solutions. Given a simplicial mesh of a bounded linear or planar space domain M, we incrementally construct a mesh of the spacetime domain M x [0,infinity) such that the solution can be computed in constant time per element. We add a patch of spacetime elements to the mesh at every step. The boundary of every patch is causal which means that the elements in the patch can be solved immediately and that the patches in the mesh are partially ordered by dependence. The elements in a single patch are coupled because they share implicit faces; however, the number of elements in each patch is bounded. The main contribution of this paper is sufficient constraints on the progress in time made by the algorithm at each step which guarantee that a new patch with causal boundary can be added to the mesh at every step even when the wavespeed is increasing discontinuously. Our algorithm adapts to the local gradation of the space mesh as well as the wavespeed that most constrains progress at each step. Previous algorithms have been restricted at each step by the maximum wavespeed throughout the entire spacetime domain.
Testing data types implementations from algebraic specifications
Venue: arXiv cs.PL 2008
Year: 2008

Algebraic specifications of data types provide a natural basis for testing data types implementations. In this framework, the conformance relation is based on the satisfaction of axioms. This makes it possible to formally state the fundamental concepts of testing: exhaustive test set, testability hypotheses, oracle. Various criteria for selecting finite test sets have been proposed. They depend on the form of the axioms, and on the possibilities of observation of the implementation under test. This last point is related to the well-known oracle problem. As the main interest of algebraic specifications is data type abstraction, testing a concrete implementation raises the issue of the gap between the abstract description and the concrete representation. The observational semantics of algebraic specifications bring solutions on the basis of the so-called observable contexts. After a description of testing methods based on algebraic specifications, the chapter gives a brief presentation of some tools and case studies, and presents some applications to other formal methods involving datatypes.
Adaptive Dynamics of Realistic Small-World Networks
Venue: arXiv cs.DS 2008
Year: 2008

Continuing in the steps of Jon Kleinberg's and others celebrated work on decentralized search in small-world networks, we conduct an experimental analysis of a dynamic algorithm that produces small-world networks. We find that the algorithm adapts robustly to a wide variety of situations in realistic geographic networks with synthetic test data and with real world data, even when vertices are uneven and non-homogeneously distributed. We investigate the same algorithm in the case where some vertices are more popular destinations for searches than others, for example obeying power-laws. We find that the algorithm adapts and adjusts the networks according to the distributions, leading to improved performance. The ability of the dynamic process to adapt and create small worlds in such diverse settings suggests a possible mechanism by which such networks appear in nature.