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Title: Quiescence of Self-stabilizing Gossiping among Mobile Agents in Graphs |
Abstract: This paper considers gossiping among mobile agents in graphs: agents move on the graph and have to disseminate their initial information to every other agent. We focus on self-stabilizing solutions for the gossip problem, where agents may start from arbitrary locations in arbitrary states. Self-stabilization ... |
Title: Acquisition Accuracy Evaluation in Visual Inspection Systems - a Practical Approach |
Abstract: This paper draws a proposal of a set of parameters and methods for accuracy evaluation of visual inspection systems. The case of a monochrome board is treated, but practically all conclusions and methods may be extended for colour acquisition. Basically, the proposed parameters are grouped in five sets as fol... |
Title: Multiscale Inference for High-Frequency Data |
Abstract: This paper proposes a novel multiscale estimator for the integrated volatility of an Ito process, in the presence of market microstructure noise (observation error). The multiscale structure of the observed process is represented frequency-by-frequency and the concept of the multiscale ratio is introduced to ... |
Title: An EM algorithm for estimation in the Mixture Transition Distribution model |
Abstract: The Mixture Transition Distribution (MTD) model was introduced by Raftery to face the need for parsimony in the modeling of high-order Markov chains in discrete time. The particularity of this model comes from the fact that the effect of each lag upon the present is considered separately and additively, so th... |
Title: The Rank of the Covariance Matrix of an Evanescent Field |
Abstract: Evanescent random fields arise as a component of the 2-D Wold decomposition of homogenous random fields. Besides their theoretical importance, evanescent random fields have a number of practical applications, such as in modeling the observed signal in the space time adaptive processing (STAP) of airborne rada... |
Title: What Can We Learn Privately? |
Abstract: Learning problems form an important category of computational tasks that generalizes many of the computations researchers apply to large real-life data sets. We ask: what concept classes can be learned privately, namely, by an algorithm whose output does not depend too heavily on any one input or specific tra... |
Title: New probabilistic interest measures for association rules |
Abstract: Mining association rules is an important technique for discovering meaningful patterns in transaction databases. Many different measures of interestingness have been proposed for association rules. However, these measures fail to take the probabilistic properties of the mined data into account. In this paper,... |
Title: The Future of Scientific Simulations: from Artificial Life to Artificial Cosmogenesis |
Abstract: This philosophical paper explores the relation between modern scientific simulations and the future of the universe. We argue that a simulation of an entire universe will result from future scientific activity. This requires us to tackle the challenge of simulating open-ended evolution at all levels in a sing... |
Title: Serious Flaws in Korf et al.'s Analysis on Time Complexity of A* |
Abstract: This paper has been withdrawn. |
Title: Non-Singular Assembly-mode Changing Motions for 3-RPR Parallel Manipulators |
Abstract: When moving from one arbitrary location at another, a parallel manipulator may change its assembly-mode without crossing a singularity. Because the non-singular change of assembly-mode cannot be simply detected, the actual assembly-mode during motion is difficult to track. This paper proposes a global explana... |
Title: Hybrid Reasoning and the Future of Iconic Representations |
Abstract: We give a brief overview of the main characteristics of diagrammatic reasoning, analyze a case of human reasoning in a mastermind game, and explain why hybrid representation systems (HRS) are particularly attractive and promising for Artificial General Intelligence and Computer Science in general. |
Title: Privacy Preserving ID3 over Horizontally, Vertically and Grid Partitioned Data |
Abstract: We consider privacy preserving decision tree induction via ID3 in the case where the training data is horizontally or vertically distributed. Furthermore, we consider the same problem in the case where the data is both horizontally and vertically distributed, a situation we refer to as grid partitioned data. ... |
Title: Dempster-Shafer for Anomaly Detection |
Abstract: In this paper, we implement an anomaly detection system using the Dempster-Shafer method. Using two standard benchmark problems we show that by combining multiple signals it is possible to achieve better results than by using a single signal. We further show that by applying this approach to a real-world emai... |
Title: A class of statistical models to weaken independence in two-way contingency tables |
Abstract: In this paper we study a new class of statistical models for contingency tables. We define this class of models through a subset of the binomial equations of the classical independence model. We use some notions from Algebraic Statistics to compute their sufficient statistic, and to prove that they are log-li... |
Title: Spatio-activity based object detection |
Abstract: We present the SAMMI lightweight object detection method which has a high level of accuracy and robustness, and which is able to operate in an environment with a large number of cameras. Background modeling is based on DCT coefficients provided by cameras. Foreground detection uses similarity in temporal char... |
Title: Genetic-Algorithm Seeding Of Idiotypic Networks For Mobile-Robot Navigation |
Abstract: Robot-control designers have begun to exploit the properties of the human immune system in order to produce dynamic systems that can adapt to complex, varying, real-world tasks. Jernes idiotypic-network theory has proved the most popular artificial-immune-system (AIS) method for incorporation into behaviour-b... |
Title: Component models for large networks |
Abstract: Being among the easiest ways to find meaningful structure from discrete data, Latent Dirichlet Allocation (LDA) and related component models have been applied widely. They are simple, computationally fast and scalable, interpretable, and admit nonparametric priors. In the currently popular field of network mo... |
Title: Improved evolutionary generation of XSLT stylesheets |
Abstract: This paper introduces a procedure based on genetic programming to evolve XSLT programs (usually called stylesheets or logicsheets). XSLT is a general purpose, document-oriented functional language, generally used to transform XML documents (or, in general, solve any problem that can be coded as an XML documen... |
Title: Danger Theory: The Link between AIS and IDS? |
Abstract: We present ideas about creating a next generation Intrusion Detection System based on the latest immunological theories. The central challenge with computer security is determining the difference between normal and potentially harmful activity. For half a century, developers have protected their systems by co... |
Title: An Ant-Based Model for Multiple Sequence Alignment |
Abstract: Multiple sequence alignment is a key process in today's biology, and finding a relevant alignment of several sequences is much more challenging than just optimizing some improbable evaluation functions. Our approach for addressing multiple sequence alignment focuses on the building of structures in a new grap... |
Title: Locally D-optimal designs based on a class of composed models resulted from blending Emax and one-compartment models |
Abstract: A class of nonlinear models combining a pharmacokinetic compartmental model and a pharmacodynamic Emax model is introduced. The locally D-optimal (LD) design for a four-parameter composed model is found to be a saturated four-point uniform LD design with the two boundary points of the design space in the LD d... |
Title: Adaptive Ridge Selector (ARiS) |
Abstract: We introduce a new shrinkage variable selection operator for linear models which we term the (ARiS). This approach is inspired by the (RVM), which uses a Bayesian hierarchical linear setup to do variable selection and model estimation. Extending the RVM algorithm, we include a proper prior distribution for th... |
Title: Conditioning Probabilistic Databases |
Abstract: Past research on probabilistic databases has studied the problem of answering queries on a static database. Application scenarios of probabilistic databases however often involve the conditioning of a database using additional information in the form of new evidence. The conditioning problem is thus to transf... |
Title: Tableau-based decision procedures for logics of strategic ability in multi-agent systems |
Abstract: We develop an incremental tableau-based decision procedures for the Alternating-time temporal logic ATL and some of its variants. While running within the theoretically established complexity upper bound, we claim that our tableau is practically more efficient in the average case than other decision procedure... |
Title: lambda-Connectedness Determination for Image Segmentation |
Abstract: Image segmentation is to separate an image into distinct homogeneous regions belonging to different objects. It is an essential step in image analysis and computer vision. This paper compares some segmentation technologies and attempts to find an automated way to better determine the parameters for image segm... |
Title: The adjusted Viterbi training for hidden Markov models |
Abstract: The EM procedure is a principal tool for parameter estimation in the hidden Markov models. However, applications replace EM by Viterbi extraction, or training (VT). VT is computationally less intensive, more stable and has more of an intuitive appeal, but VT estimation is biased and does not satisfy the follo... |
Title: Quantile Estimation of A general Single-Index Model |
Abstract: The single-index model is one of the most popular semiparametric models in Econometrics. In this paper, we define a quantile regression single-index model, which includes the single-index structure for conditional mean and for conditional variance. |
Title: Heteroscedastic controlled calibration model applied to analytical chemistry |
Abstract: In chemical analysis made by laboratories one has the problem of determining the concentration of a chemical element in a sample. In order to tackle this problem the guide EURACHEM/CITAC recommends the application of the linear calibration model, so implicitly assume that there is no measurement error in the ... |
Title: KohonAnts: A Self-Organizing Ant Algorithm for Clustering and Pattern Classification |
Abstract: In this paper we introduce a new ant-based method that takes advantage of the cooperative self-organization of Ant Colony Systems to create a naturally inspired clustering and pattern recognition method. The approach considers each data item as an ant, which moves inside a grid changing the cells it goes thro... |
Title: Using Spatially Varying Pixels Exposures and Bayer-covered Photosensors for High Dynamic Range Imaging |
Abstract: The method of a linear high dynamic range imaging using solid-state photosensors with Bayer colour filters array is provided in this paper. Using information from neighbour pixels, it is possible to reconstruct linear images with wide dynamic range from the oversaturated images. Bayer colour filters array is ... |
Title: Figuring out Actors in Text Streams: Using Collocations to establish Incremental Mind-maps |
Abstract: The recognition, involvement, and description of main actors influences the story line of the whole text. This is of higher importance as the text per se represents a flow of words and expressions that once it is read it is lost. In this respect, the understanding of a text and moreover on how the actor exact... |
Title: Extensions of smoothing via taut strings |
Abstract: Suppose that we observe independent random pairs $(X_1,Y_1)$, $(X_2,Y_2)$, >..., $(X_n,Y_n)$. Our goal is to estimate regression functions such as the conditional mean or $\beta$--quantile of $Y$ given $X$, where $0<\beta <1$. In order to achieve this we minimize criteria such as, for instance, $$ \sum_i=1^n ... |
Title: An Indirect Genetic Algorithm for Set Covering Problems |
Abstract: This paper presents a new type of genetic algorithm for the set covering problem. It differs from previous evolutionary approaches first because it is an indirect algorithm, i.e. the actual solutions are found by an external decoder function. The genetic algorithm itself provides this decoder with permutation... |
Title: On the Application of Hierarchical Coevolutionary Genetic Algorithms: Recombination and Evaluation Partners |
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