Blar i ODA Open Digital Archive på forfatter "Oommen, John"
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A novel strategy for solving the stochastic point location problem using a hierarchical searching scheme
Yazidi, Anis; Granmo, Ole-Christoffer; Oommen, John; Goodwin, Morten (Journal article; Peer reviewed, 2014)Stochastic point location (SPL) deals with the problem of a learning mechanism (LM) determining the optimal point on the line when the only input it receives are stochastic signals about the direction in which it should ... -
Achieving Fair Load Balancing by Invoking a Learning Automata-based Two Time Scale Separation Paradigm
Yazidi, Anis; Hassan, Ismail; Hammer, Hugo Lewi; Oommen, John (IEEE Transactions on Neural Networks and Learning Systems;, Journal article; Peer reviewed, 2020-08-05)In this article, we consider the problem of load balancing (LB), but, unlike the approaches that have been proposed earlier, we attempt to resolve the problem in a fair manner (or rather, it would probably be more appropriate ... -
Achieving Intelligent Traffic-aware Consolidation of Virtual Machines in a Data Center Using Learning Automata
Jobava, Akaki; Yazidi, Anis; Oommen, John; Begnum, Kyrre (Chapter; Peer reviewed, 2016)Cloud Computing (CC) is becoming increasingly pertinent and popular. A natural consequence of this is that many modern-day data centers experience very high internal traffic within the data centers themselves. The ... -
“Anti-Bayesian” Flat and Hierarchical Clustering Using Symmetric Quantiloids
Yazidi, Anis; Hammer, Hugo Lewi; Oommen, John (Chapter; Peer reviewed; Journal article, 2016)A myriad of works has been published for achieving data clustering based on the Bayesian paradigm, where the clustering sometimes resorts to Naïve-Bayes decisions. Within the domain of clustering, the Bayesian principle ... -
“Anti-Bayesian” flat and hierarchical clustering using symmetric quantiloids
Hammer, Hugo Lewi; Yazidi, Anis; Oommen, John (Journal article; Peer reviewed, 2017)A Pattern Recognition (PR) system that does not involve labelled samples requires the clustering of the samples into their respective classes before the training and testing can be achieved. All of the reported clustering ... -
Concept drift detection using online histogram-based bayesian classifiers
Astudillo, César A.; Gonzalez, Javier I.; Oommen, John; Yazidi, Anis (Lecture Notes in Computer Science;9992, Journal article; Peer reviewed, 2016)In this paper, we present a novel algorithm that performs online histogram-based classification, i.e., specifically designed for the case when the data is dynamic and its distribution is non-stationary. Our method, called ... -
Dynamic Ordering of Firewall Rules Using a Novel Swapping Window-based Paradigm
Mohan, Ratish; Yazidi, Anis; Feng, Boning; Oommen, John (Peer reviewed; Chapter, 2016)Designing and implementing efficient firewall strategies in the age of the Internet of Things (IoT) is far from trivial. This is because, as time proceeds, an increasing number of devices will be connected, accessed and ... -
The Hierarchical Continuous Pursuit Learning Automation for Large Numbers of Actions
Yazidi, Anis; Zhang, Xuan; Lei, Jiao; Oommen, John (Chapter; Peer reviewed, 2018-05-22)Although the field of Learning Automata (LA) has made significant progress in the last four decades, the LA-based methods to tackle problems involving environments with a large number of actions are, in reality, relatively ... -
The Hierarchical Continuous Pursuit Learning Automation: A Novel Scheme for Environments With Large Numbers of Actions
Yazidi, Anis; Zhang, Xuan; Lei, Jiao; Oommen, John (IEEE Transactions on Neural Networks and Learning Systems;Volume: 31, Issue: 2, Journal article; Peer reviewed, 2019)Although the field of learning automata (LA) has made significant progress in the past four decades, the LA-based methods to tackle problems involving environments with a large number of actions is, in reality, relatively ... -
A Learning Automaton-based Scheme for Scheduling Domestic Shiftable Loads in Smart Grids
Thapa, Rajan; Lei, Jiao; Oommen, John; Yazidi, Anis (Journal article; Peer reviewed, 2017)In this paper, we consider the problem of scheduling shiftable loads, over multiple users, in smart electrical grids. We approach the problem, which is becoming increasingly pertinent in our present energy-thirsty society, ... -
A Novel Clustering Algorithm based on a Non-parametric "Anti-Bayesian" Paradigm
Hammer, Hugo Lewi; Yazidi, Anis; Oommen, John (Lecture Notes in Computer Science;, Journal article; Peer reviewed, 2015-05-01)The problem of clustering, or unsupervised classification, has been solved by a myriad of techniques, all of which depend, either directly or implicitly, on the Bayesian principle of optimal classification. To be more ... -
A novel technique for stochastic root-finding: Enhancing the search with adaptive d-ary search
Yazidi, Anis; Oommen, John (Information Sciences;Volume 393, Journal article; Peer reviewed, 2017-07)The most fundamental problem encountered in the field of stochastic optimization, is the Stochastic Root Finding (SRF) problem where the task is to locate an unknown point x∗ for which g(x∗) = 0 for a given function g ... -
On achieving intelligent traffic-aware consolidation of virtual machines in a data center using Learning Automata
Jobava, Akaki; Yazidi, Anis; Oommen, John; Begnum, Kyrre (Journal of Computational Science;Volume 24, Journal article; Peer reviewed, 2018-01)Unlike the computational mechanisms of the past many decades, that involved individual (extremely powerful) computers or clusters of machines, Cloud Computing (CC) is becoming increasingly pertinent and popular. Computing ... -
On Distinguishing between Reliable and Unreliable Sensors Without a Knowledge of the Ground Truth
Yazidi, Anis; Oommen, John; Goodwin, Morten (Peer reviewed; Chapter, 2015)In many applications, data from different sensors are aggregated in order to obtain more reliable information about the process that the sensors are monitoring. However, the quality of the aggregated ... -
On optimizing firewall performance in dynamic networks by invoking a novel swapping window-based paradigm
Mohan, Ratish; Yazidi, Anis; Feng, Boning; Oommen, John (International Journal of Communication Systems;Volume 31, Issue 15 October 2018, Journal article; Peer reviewed, 2018-07-24)Designing and implementing efficient firewall strategies in the age of the Internet of Things (IoT) is far from trivial. This is because, as time proceeds, an increasing number of devices will be connected, accessed and ... -
On the analysis of a random walk-jump chain with tree-based transitions and its applications to faulty dichotomous search
Yazidi, Anis; Oommen, John (Sequential Analysis;Volume 37, 2018 - Issue 1, Journal article; Peer reviewed, 2018-03-08)Random Walks (RWs) have been extensively studied for more than a century [1]. These walks have traditionally been on a line, and the generalizations for two and three dimensions, have been by extending the random steps to ... -
On the Classification of Dynamical Data Streams Using Novel “Anti–Bayesian” Techniques
Hammer, Hugo Lewi; Yazidi, Anis; Oommen, John (Journal article; Peer reviewed, 2018)The classification of dynamical data streams is among the most complex problems encountered in classification. This is, firstly, because the distribution of the data streams is non-stationary, ... -
On the Online Classification of Data Streams Using Weak Estimators
Tavasoli, Hanane; Oommen, John; Yazidi, Anis (Lecture Notes in Computer Science;9799, Journal article; Peer reviewed, 2016)In this paper, we propose a novel online classifier for complex data streams which are generated from non-stationary stochastic properties. Instead of using a single training model and counters to keep important data ... -
On Using Novel "Anti-Bayesian" Techniques for the Classification of Dynamical Data Streams
Hammer, Hugo Lewi; Yazidi, Anis; Oommen, John (Chapter; Peer reviewed, 2017)The classification of dynamical data streams is among the most complex problems encountered in classification. This is, firstly, because the distribution of the data streams is non-stationary, and it changes without any ... -
On utilizing weak estimators to achieve the online classification of data streams
Tavasoli, Hanane; Oommen, John; Yazidi, Anis (Engineering Applications of Artificial Intelligence;Volume 86, November 2019, Journal article; Peer reviewed, 2019-09-02)Classification, typically, deals with unique and distinct training and testing phases. This paper pioneers the concept when these phases are not so clearly well-defined. More specifically, we consider the case where the ...