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Title: Concept-based Recommendations for Internet Advertisement |
Abstract: The problem of detecting terms that can be interesting to the advertiser is considered. If a company has already bought some advertising terms which describe certain services, it is reasonable to find out the terms bought by competing companies. A part of them can be recommended as future advertising terms to... |
Title: Chemical Power for Microscopic Robots in Capillaries |
Abstract: The power available to microscopic robots (nanorobots) that oxidize bloodstream glucose while aggregated in circumferential rings on capillary walls is evaluated with a numerical model using axial symmetry and time-averaged release of oxygen from passing red blood cells. Robots about one micron in size can pr... |
Title: A Novel Two-Stage Dynamic Decision Support based Optimal Threat Evaluation and Defensive Resource Scheduling Algorithm for Multi Air-borne threats |
Abstract: This paper presents a novel two-stage flexible dynamic decision support based optimal threat evaluation and defensive resource scheduling algorithm for multi-target air-borne threats. The algorithm provides flexibility and optimality by swapping between two objective functions, i.e. the preferential and subtr... |
Title: A new approach for digit recognition based on hand gesture analysis |
Abstract: We present in this paper a new approach for hand gesture analysis that allows digit recognition. The analysis is based on extracting a set of features from a hand image and then combining them by using an induction graph. The most important features we extract from each image are the fingers locations, their ... |
Title: Towards the Patterns of Hard CSPs with Association Rule Mining |
Abstract: The hardness of finite domain Constraint Satisfaction Problems (CSPs) is a very important research area in Constraint Programming (CP) community. However, this problem has not yet attracted much attention from the researchers in the association rule mining community. As a popular data mining technique, associ... |
Title: Statistical Analysis of Privacy and Anonymity Guarantees in Randomized Security Protocol Implementations |
Abstract: Security protocols often use randomization to achieve probabilistic non-determinism. This non-determinism, in turn, is used in obfuscating the dependence of observable values on secret data. Since the correctness of security protocols is very important, formal analysis of security protocols has been widely st... |
Title: Non-Parametric Bayesian Areal Linguistics |
Abstract: We describe a statistical model over linguistic areas and phylogeny. Our model recovers known areas and identifies a plausible hierarchy of areal features. The use of areas improves genetic reconstruction of languages both qualitatively and quantitatively according to a variety of metrics. We model linguistic... |
Title: General combination rules for qualitative and quantitative beliefs |
Abstract: Martin and Osswald have recently proposed many generalizations of combination rules on quantitative beliefs in order to manage the conflict and to consider the specificity of the responses of the experts. Since the experts express themselves usually in natural language with linguistic labels, Smarandache and ... |
Title: Comments on "A new combination of evidence based on compromise" by K. Yamada |
Abstract: Comments on ``A new combination of evidence based on compromise'' by K. Yamada |
Title: Explicit probabilistic models for databases and networks |
Abstract: Recent work in data mining and related areas has highlighted the importance of the statistical assessment of data mining results. Crucial to this endeavour is the choice of a non-trivial null model for the data, to which the found patterns can be contrasted. The most influential null models proposed so far ar... |
Title: Unsupervised Search-based Structured Prediction |
Abstract: We describe an adaptation and application of a search-based structured prediction algorithm "Searn" to unsupervised learning problems. We show that it is possible to reduce unsupervised learning to supervised learning and demonstrate a high-quality unsupervised shift-reduce parsing model. We additionally show... |
Title: Testing for white noise under unknown dependence and its applications to goodness-of-fit for time series models |
Abstract: Testing for white noise has been well studied in the literature of econometrics and statistics. For most of the proposed test statistics, such as the well-known Box-Pierce's test statistic with fixed lag truncation number, the asymptotic null distributions are obtained under independent and identically distri... |
Title: High Dimensional Nonlinear Learning using Local Coordinate Coding |
Abstract: This paper introduces a new method for semi-supervised learning on high dimensional nonlinear manifolds, which includes a phase of unsupervised basis learning and a phase of supervised function learning. The learned bases provide a set of anchor points to form a local coordinate system, such that each data po... |
Title: Restricted Global Grammar Constraints |
Abstract: We investigate the global GRAMMAR constraint over restricted classes of context free grammars like deterministic and unambiguous context-free grammars. We show that detecting disentailment for the GRAMMAR constraint in these cases is as hard as parsing an unrestricted context free grammar.We also consider the... |
Title: Multiple Hypothesis Testing in Pattern Discovery |
Abstract: The problem of multiple hypothesis testing arises when there are more than one hypothesis to be tested simultaneously for statistical significance. This is a very common situation in many data mining applications. For instance, assessing simultaneously the significance of all frequent itemsets of a single dat... |
Title: Online Reinforcement Learning for Dynamic Multimedia Systems |
Abstract: In our previous work, we proposed a systematic cross-layer framework for dynamic multimedia systems, which allows each layer to make autonomous and foresighted decisions that maximize the system's long-term performance, while meeting the application's real-time delay constraints. The proposed solution solved ... |
Title: Relative Density of the Random r-Factor Proximity Catch Digraph for Testing Spatial Patterns of Segregation and Association (Technical Report) |
Abstract: Statistical pattern classification methods based on data-random graphs were introduced recently. In this approach, a random directed graph is constructed from the data using the relative positions of the data points from various classes. Different random graphs result from different definitions of the proximi... |
Title: Relative Edge Density of the Underlying Graphs Based on Proportional-Edge Proximity Catch Digraphs for Testing Bivariate Spatial Patterns (Technical Report) |
Abstract: The use of data-random graphs in statistical testing of spatial patterns is introduced recently. In this approach, a random directed graph is constructed from the data using the relative positions of the points from various classes. Different random graphs result from different definitions of the proximity re... |
Title: Query Significance in Databases via Randomizations |
Abstract: Many sorts of structured data are commonly stored in a multi-relational format of interrelated tables. Under this relational model, exploratory data analysis can be done by using relational queries. As an example, in the Internet Movie Database (IMDb) a query can be used to check whether the average rank of a... |
Title: A-Collapsibility of Distribution Dependence and Quantile Regression Coefficients |
Abstract: The Yule-Simpson paradox notes that an association between random variables can be reversed when averaged over a background variable. Cox and Wermuth (2003) introduced the concept of distribution dependence between two random variables X and Y, and developed two dependence conditions, each of which guarantees... |
Title: Entropic Priors and Bayesian Model Selection |
Abstract: We demonstrate that the principle of maximum relative entropy (ME), used judiciously, can ease the specification of priors in model selection problems. The resulting effect is that models that make sharp predictions are disfavoured, weakening the usual Bayesian "Occam's Razor". This is illustrated with a simp... |
Title: A Novel Two-Staged Decision Support based Threat Evaluation and Weapon Assignment Algorithm, Asset-based Dynamic Weapon Scheduling using Artificial Intelligence Techinques |
Abstract: Surveillance control and reporting (SCR) system for air threats play an important role in the defense of a country. SCR system corresponds to air and ground situation management/processing along with information fusion, communication, coordination, simulation and other critical defense oriented tasks. Threat ... |
Title: Coherent frequentism |
Abstract: By representing the range of fair betting odds according to a pair of confidence set estimators, dual probability measures on parameter space called frequentist posteriors secure the coherence of subjective inference without any prior distribution. The closure of the set of expected losses corresponding to th... |
Title: Multi-Label MRF Optimization via Least Squares s-t Cuts |
Abstract: There are many applications of graph cuts in computer vision, e.g. segmentation. We present a novel method to reformulate the NP-hard, k-way graph partitioning problem as an approximate minimal s-t graph cut problem, for which a globally optimal solution is found in polynomial time. Each non-terminal vertex i... |
Title: A new model of artificial neuron: cyberneuron and its use |
Abstract: This article describes a new type of artificial neuron, called the authors "cyberneuron". Unlike classical models of artificial neurons, this type of neuron used table substitution instead of the operation of multiplication of input values for the weights. This allowed to significantly increase the informatio... |
Title: An Iterative Fingerprint Enhancement Algorithm Based on Accurate Determination of Orientation Flow |
Abstract: We describe an algorithm to enhance and binarize a fingerprint image. The algorithm is based on accurate determination of orientation flow of the ridges of the fingerprint image by computing variance of the neighborhood pixels around a pixel in different directions. We show that an iterative algorithm which c... |
Title: Degenerate neutrality creates evolvable fitness landscapes |
Abstract: Understanding how systems can be designed to be evolvable is fundamental to research in optimization, evolution, and complex systems science. Many researchers have thus recognized the importance of evolvability, i.e. the ability to find new variants of higher fitness, in the fields of biological evolution and... |
Title: Evidence of coevolution in multi-objective evolutionary algorithms |
Abstract: This paper demonstrates that simple yet important characteristics of coevolution can occur in evolutionary algorithms when only a few conditions are met. We find that interaction-based fitness measurements such as fitness (linear) ranking allow for a form of coevolutionary dynamics that is observed when 1) ch... |
Title: Survival of the flexible: explaining the recent dominance of nature-inspired optimization within a rapidly evolving world |
Abstract: Although researchers often comment on the rising popularity of nature-inspired meta-heuristics (NIM), there has been a paucity of data to directly support the claim that NIM are growing in prominence compared to other optimization techniques. This study presents evidence that the use of NIM is not only growin... |
Title: The Self-Organization of Interaction Networks for Nature-Inspired Optimization |
Abstract: Over the last decade, significant progress has been made in understanding complex biological systems, however there have been few attempts at incorporating this knowledge into nature inspired optimization algorithms. In this paper, we present a first attempt at incorporating some of the basic structural prope... |
Title: Strategic Positioning in Tactical Scenario Planning |
Abstract: Capability planning problems are pervasive throughout many areas of human interest with prominent examples found in defense and security. Planning provides a unique context for optimization that has not been explored in great detail and involves a number of interesting challenges which are distinct from tradi... |
Title: Bounding the Probability of Error for High Precision Recognition |
Abstract: We consider models for which it is important, early in processing, to estimate some variables with high precision, but perhaps at relatively low rates of recall. If some variables can be identified with near certainty, then they can be conditioned upon, allowing further inference to be done efficiently. Speci... |
Title: Error analysis for circle fitting algorithms |
Abstract: We study the problem of fitting circles (or circular arcs) to data points observed with errors in both variables. A detailed error analysis for all popular circle fitting methods -- geometric fit, Kasa fit, Pratt fit, and Taubin fit -- is presented. Our error analysis goes deeper than the traditional expansio... |
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