Browsing Scientific Publications in Information and Communication Technology by Subject "VDP::Mathematics and natural science: 400::Information and communication science: 420::Knowledge based systems: 425"
Now showing items 1-20 of 20
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A hierarchical learning scheme for solving the Stochastic Point Location problem
(Lecture Notes in Computer Science;7345, Chapter; Peer reviewed, 2012)This paper deals with the Stochastic-Point Location (SPL) problem. It presents a solution which is novel in both philosophy and strategy to all the reported related learning algorithms. The SPL problem concerns the task ... -
A new frontier in novelty detection : Pattern recognition of stochastically episodic events
(Lecture Notes in Computer Science; no. 6591, Chapter; Peer reviewed, 2011)A particularly challenging class of PR problems in which the, generally required, representative set of data drawn from the second class is unavailable, has recently received much consideration under the guise of One-Class ... -
A Stochastic Search on the Line-Based Solution to Discretized Estimation
(Lecture Notes in Computer Science;7345, Chapter; Peer reviewed, 2012)Recently, Oommen and Rueda [11] presented a strategy by which the parameters of a binomial/multinomial distribution can be estimated when the underlying distribution is nonstationary. The method has been referred to as the ... -
Ideal Chaotic Pattern Recognition is achievable: The Ideal-M-AdNN - its design and properties
(Lecture Notes in Computer Science;8065, Chapter; Peer reviewed, 2013)This paper deals with the relatively new field of designing a Chaotic Pattern Recognition (PR) system. The benchmark of such a system is the following: First of all, one must be able to train the system with a set of ... -
Improving the performance metric of wireless sensor networks with clustering Markov chain model and multilevel fusion
(Journal article; Peer reviewed, 2013)The paper proposes a performance metric evaluation for a distributed detection wireless sensor network with respect to IEEE 802.15.4 standard. A distributed detection scheme is considered with presence of the fusion node ... -
A Learning Automata Based Solution to Service Selection in Stochastic Environments
(Chapter; Peer reviewed, 2010)With the abundance of services available in today’s world, identifying those of high quality is becoming increasingly difficult. Reputation systems can offer generic recommendations by aggregating user provided opinions ... -
Learning automata-based solutions to the optimal web polling problem modelled as a nonlinear fractional knapsack problem
(Journal article; Peer reviewed, 2011)We consider the problem of polling web pages as a strategy for monitoring the world wide web. The problem consists of repeatedly polling a selection of web pages so that changes that occur over time are detected. In ... -
Networking logistic neurons can yield chaotic and pattern recognition properties
(Chapter; Peer reviewed, 2011)Over the last few years, the field of Chaotic Neural Networks (CNNs) has been extensively studied because of their potential applications in the understanding/recognition of patterns and images, their associative memory ... -
A new tool for the modeling of AI and machine learning applications: Random walk-jump processes
(Lecture notes in computer science;6678, Chapter; Peer reviewed, 2011)There are numerous applications in Artificial Intelligence (AI) and Machine Learning (ML) where the criteria for decisions are based on testing procedures. The most common tools used in such random phenomena involve Random ... -
On achieving near-optimal “Anti-Bayesian” Order Statistics-Based classification fora asymmetric exponential distributions
(Lecture Notes in Computer Science;8047, Chapter; Peer reviewed, 2013)This paper considers the use of Order Statistics (OS) in the theory of Pattern Recognition (PR). The pioneering work on using OS for classification was presented in [1] for the Uniform distribution, where it was shown that ... -
On incorporating the paradigms of discretization and Bayesian estimation to create a new family of pursuit learning automata
(Journal article; Peer reviewed, 2013)There are currently two fundamental paradigms that have been used to enhance the convergence speed of Learning Automata (LA). The first involves the concept of utilizing the estimates of the reward probabilities, while the ... -
On the pattern recognition and classification of stochastically episodic events
(Lecture Notes in Computer Science; 7190;, Chapter; Peer reviewed, 2012)Researchers in the field of Pattern Recognition (PR) have traditionally presumed the availability of a representative set of data drawn from the classes of interest, say ω 1 and ω 2 in a 2-class problem. These samples are ... -
On using prototype reduction schemes to optimize locally linear reconstruction methods
(Journal article; Peer reviewed, 2012)This paper concerns the use of prototype reduction schemes (PRS) to optimize the computations involved in typical k-nearest neighbor (k-NN) rules. These rules have been successfully used for decades in statistical pattern ... -
On utilizing dependence-based information to enhance micro-aggregation for secure statistical databases
(Journal article; Peer reviewed, 2013)We consider the micro-aggregation problem which involves partitioning a set of individual records in a micro-data file into a number of mutually exclusive and exhaustive groups. This problem, which seeks for the best ... -
Optimal “anti-Bayesian” parametric pattern classification for the exponential family using Order Statistics criteria
(Lecture Notes in Computer Science;7324, Chapter; Peer reviewed, 2012)This paper reports some pioneering results in which optimal parametric classification is achieved in a counter-intuitive manner, quite opposed to the Bayesian paradigm. The paper, which builds on the results of [1], ... -
Semi-supervised classification using tree-based self-organizing maps
(Lecture Notes in Computer Science;7106, Chapter; Peer reviewed, 2011)This paper presents a classifier which uses a tree-based Neural Network (NN), and uses both, unlabeled and labeled instances. First, we learn the structure of the data distribution in an unsupervised manner. After convergence, ... -
Service selection in stochastic environments: a learning-automaton based solution
(Journal article; Peer reviewed, 2011)In this paper, we propose a novel solution to the problem of identifying services of high quality. The reported solutions to this problem have, in one way or the other, resorted to using so-called “Reputation Systems” ... -
Solving Non-Stationary Bandit Problems by Random Sampling from Sibling Kalman Filters
(Lecture Notes in Computer Science ; 6098, Chapter; Peer reviewed, 2010)The multi-armed bandit problem is a classical optimization problem where an agent sequentially pulls one of multiple arms attached to a gambling machine, with each pull resulting in a random reward. The reward distributions ... -
Tracking the preferences of users using weak estimators
(Lecture Notes in Computer Science;7106, Chapter; Peer reviewed, 2011)Since a social network, by definition, is so diverse, the problem of estimating the preferences of its users is becoming increasingly essential for personalized applications which range from service recommender systems to ... -
Using artificial intelligence techniques for strategy generation in the Commons game
(Lecture Notes in Computer Science;6678, Chapter; Peer reviewed, 2011)In this paper, we consider the use of artificial intelligence techniques to aid in discovery of winning strategies for the Commons Game (CG). The game represents a common scenario in which multiple parties share the use ...