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Abstract: There are many on-line settings in which users publicly express opinions. A number of these offer mechanisms for other users to evaluate these opinions; a canonical example is Amazon.com, where reviews come with annotations like "26 of 32 people found the following review helpful." Opinion evaluation appears ... |
Title: Automatic Defect Detection and Classification Technique from Image: A Special Case Using Ceramic Tiles |
Abstract: Quality control is an important issue in the ceramic tile industry. On the other hand maintaining the rate of production with respect to time is also a major issue in ceramic tile manufacturing. Again, price of ceramic tiles also depends on purity of texture, accuracy of color, shape etc. Considering this cri... |
Title: Hybrid Rules with Well-Founded Semantics |
Abstract: A general framework is proposed for integration of rules and external first order theories. It is based on the well-founded semantics of normal logic programs and inspired by ideas of Constraint Logic Programming (CLP) and constructive negation for logic programs. Hybrid rules are normal clauses extended with... |
Title: Squeezing the Arimoto-Blahut algorithm for faster convergence |
Abstract: The Arimoto--Blahut algorithm for computing the capacity of a discrete memoryless channel is revisited. A so-called ``squeezing'' strategy is used to design algorithms that preserve its simplicity and monotonic convergence properties, but have provably better rates of convergence. |
Title: Bayesian Forecasting of WWW Traffic on the Time Varying Poisson Model |
Abstract: Traffic forecasting from past observed traffic data with small calculation complexity is one of important problems for planning of servers and networks. Focusing on World Wide Web (WWW) traffic as fundamental investigation, this paper would deal with Bayesian forecasting of network traffic on the time varying... |
Title: Soft Constraints for Quality Aspects in Service Oriented Architectures |
Abstract: We propose the use of Soft Constraints as a natural way to model Service Oriented Architecture. In the framework, constraints are used to model components and connectors and constraint aggregation is used to represent their interactions. The "quality of a service" is measured and considered when performing qu... |
Title: Accurate Parametric Inference for Small Samples |
Abstract: We outline how modern likelihood theory, which provides essentially exact inferences in a variety of parametric statistical problems, may routinely be applied in practice. Although the likelihood procedures are based on analytical asymptotic approximations, the focus of this paper is not on theory but on impl... |
Title: Principal Fitted Components for Dimension Reduction in Regression |
Abstract: We provide a remedy for two concerns that have dogged the use of principal components in regression: (i) principal components are computed from the predictors alone and do not make apparent use of the response, and (ii) principal components are not invariant or equivariant under full rank linear transformatio... |
Title: The Golden Age of Statistical Graphics |
Abstract: Statistical graphics and data visualization have long histories, but their modern forms began only in the early 1800s. Between roughly 1850 and 1900 ($\pm10$), an explosive growth occurred in both the general use of graphic methods and the range of topics to which they were applied. Innovations were prodigiou... |
Title: Remembering Wassily Hoeffding |
Abstract: Wasssily Hoeffding's terminal illness and untimely death in 1991 put an end to efforts that were made to interview him for Statistical Science. An account of his scientific work is given in Fisher and Sen [The Collected Works of Wassily Hoeffding (1994) Springer], but the present authors felt that the statist... |
Title: Bayesian two-sample tests |
Abstract: In this paper, we present two classes of Bayesian approaches to the two-sample problem. Our first class of methods extends the Bayesian t-test to include all parametric models in the exponential family and their conjugate priors. Our second class of methods uses Dirichlet process mixtures (DPM) of such conjug... |
Title: Physical Modeling Techniques in Active Contours for Image Segmentation |
Abstract: Physical modeling method, represented by simulation and visualization of the principles in physics, is introduced in the shape extraction of the active contours. The objectives of adopting this concept are to address the several major difficulties in the application of Active Contours. Primarily, a technique ... |
Title: Recommender Systems for the Conference Paper Assignment Problem |
Abstract: Conference paper assignment, i.e., the task of assigning paper submissions to reviewers, presents multi-faceted issues for recommender systems research. Besides the traditional goal of predicting `who likes what?', a conference management system must take into account aspects such as: reviewer capacity constr... |
Title: An Event Based Approach To Situational Representation |
Abstract: Many application domains require representing interrelated real-world activities and/or evolving physical phenomena. In the crisis response domain, for instance, one may be interested in representing the state of the unfolding crisis (e.g., forest fire), the progress of the response activities such as evacuat... |
Title: Automatic Spatially-Adaptive Balancing of Energy Terms for Image Segmentation |
Abstract: Image segmentation techniques are predominately based on parameter-laden optimization. The objective function typically involves weights for balancing competing image fidelity and segmentation regularization cost terms. Setting these weights suitably has been a painstaking, empirical process. Even if such ide... |
Title: A Conversation with Pranab Kumar Sen |
Abstract: Pranab Kumar Sen was born on November 7, 1937 in Calcutta, India. His father died when Pranab was 10 years old, so his mother raised the family of seven children. Given his superior performance on an exam, Pranab nearly went into medical school, but did not because he was underage. He received a B.Sc. degree ... |
Title: Rough Set Model for Discovering Hybrid Association Rules |
Abstract: In this paper, the mining of hybrid association rules with rough set approach is investigated as the algorithm RSHAR.The RSHAR algorithm is constituted of two steps mainly. At first, to join the participant tables into a general table to generate the rules which is expressing the relationship between two or m... |
Title: On Chase Termination Beyond Stratification |
Abstract: We study the termination problem of the chase algorithm, a central tool in various database problems such as the constraint implication problem, Conjunctive Query optimization, rewriting queries using views, data exchange, and data integration. The basic idea of the chase is, given a database instance and a s... |
Title: The Feature Importance Ranking Measure |
Abstract: Most accurate predictions are typically obtained by learning machines with complex feature spaces (as e.g. induced by kernels). Unfortunately, such decision rules are hardly accessible to humans and cannot easily be used to gain insights about the application domain. Therefore, one often resorts to linear mod... |
Title: Constructive Decision Theory |
Abstract: In most contemporary approaches to decision making, a decision problem is described by a sets of states and set of outcomes, and a rich set of acts, which are functions from states to outcomes over which the decision maker (DM) has preferences. Most interesting decision problems, however, do not come with a s... |
Title: Reasoning About Knowledge of Unawareness Revisited |
Abstract: In earlier work, we proposed a logic that extends the Logic of General Awareness of Fagin and Halpern [1988] by allowing quantification over primitive propositions. This makes it possible to express the fact that an agent knows that there are some facts of which he is unaware. In that logic, it is not possibl... |
Title: A Logical Characterization of Iterated Admissibility |
Abstract: Brandenburger, Friedenberg, and Keisler provide an epistemic characterization of iterated admissibility (i.e., iterated deletion of weakly dominated strategies) where uncertainty is represented using LPSs (lexicographic probability sequences). Their characterization holds in a rich structure called a complete... |
Title: A Bayes factor with reasonable model selection consistency for ANOVA model |
Abstract: For the ANOVA model, we propose a new g-prior based Bayes factor without integral representation, with reasonable model selection consistency for any asymptotic situations (either number of levels of the factor and/or number of replication in each level goes to infinity). Exact analytic calculation of the mar... |
Title: Updating Sets of Probabilities |
Abstract: There are several well-known justifications for conditioning as the appropriate method for updating a single probability measure, given an observation. However, there is a significant body of work arguing for sets of probability measures, rather than single measures, as a more realistic model of uncertainty. ... |
Title: KNIFE: Kernel Iterative Feature Extraction |
Abstract: Selecting important features in non-linear or kernel spaces is a difficult challenge in both classification and regression problems. When many of the features are irrelevant, kernel methods such as the support vector machine and kernel ridge regression can sometimes perform poorly. We propose weighting the fe... |
Title: Learning with Spectral Kernels and Heavy-Tailed Data |
Abstract: Two ubiquitous aspects of large-scale data analysis are that the data often have heavy-tailed properties and that diffusion-based or spectral-based methods are often used to identify and extract structure of interest. Perhaps surprisingly, popular distribution-independent methods such as those based on the VC... |
Title: On landmark selection and sampling in high-dimensional data analysis |
Abstract: In recent years, the spectral analysis of appropriately defined kernel matrices has emerged as a principled way to extract the low-dimensional structure often prevalent in high-dimensional data. Here we provide an introduction to spectral methods for linear and nonlinear dimension reduction, emphasizing ways ... |
Title: Acquiring Knowledge for Evaluation of Teachers Performance in Higher Education using a Questionnaire |
Abstract: In this paper, we present the step by step knowledge acquisition process by choosing a structured method through using a questionnaire as a knowledge acquisition tool. Here we want to depict the problem domain as, how to evaluate teachers performance in higher education through the use of expert system techno... |
Title: Bayesian separation of spectral sources under non-negativity and full additivity constraints |
Abstract: This paper addresses the problem of separating spectral sources which are linearly mixed with unknown proportions. The main difficulty of the problem is to ensure the full additivity (sum-to-one) of the mixing coefficients and non-negativity of sources and mixing coefficients. A Bayesian estimation approach b... |
Title: Minimum Probability Flow Learning |
Abstract: Fitting probabilistic models to data is often difficult, due to the general intractability of the partition function and its derivatives. Here we propose a new parameter estimation technique that does not require computing an intractable normalization factor or sampling from the equilibrium distribution of th... |
Title: Efficient IRIS Recognition through Improvement of Feature Extraction and subset Selection |
Abstract: The selection of the optimal feature subset and the classification has become an important issue in the field of iris recognition. In this paper we propose several methods for iris feature subset selection and vector creation. The deterministic feature sequence is extracted from the iris image by using the co... |
Title: A Bounded Derivative Method for the Maximum Likelihood Estimation on Weibull Parameters |
Abstract: For the basic maximum likelihood estimating function of the two parameters Weibull distribution, a simple proof on its global monotonicity is given to ensure the existence and uniqueness of its solution. The boundary of the function's first-order derivative is defined based on its scale-free property. With a ... |
Title: Vision Based Navigation for a Mobile Robot with Different Field of Views |
Abstract: The basic idea behind evolutionary robotics is to evolve a set of neural controllers for a particular task at hand. It involves use of various input parameters such as infrared sensors, light sensors and vision based methods. This paper aims to explore the evolution of vision based navigation in a mobile robo... |
Title: Inference for graphs and networks: Extending classical tools to modern data |
Abstract: Graphs and networks provide a canonical representation of relational data, with massive network data sets becoming increasingly prevalent across a variety of scientific fields. Although tools from mathematics and computer science have been eagerly adopted by practitioners in the service of network inference, ... |
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