Blar i Scientific Publications in Information and Communication Technology på emneord "VDP::Mathematics and natural science: 400::Information and communication science: 420::Algorithms and computability theory: 422"

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    • A framework for assessing the condition of crowds exposed to a fire hazard using a probabilistic model 

      Radianti, Jaziar; Granmo, Ole-Christoffer (Journal article; Peer reviewed, 2014)
      Allocating limited resources in an optimal manner when rescuing victims from a hazard is a complex and error prone task, because the involved hazards are typically evolving over time; stagnating, building up or diminishing. ...

    • A new paradigm for pattern classification: Nearest Border Techniques 

      Li, Yifeng; Oommen, B. John; Ngom, Alioune; Rueda, Luis (Lecture Notes in Computer Science;8272, Chapter; Peer reviewed, 2013)
      There are many paradigms for pattern classification. As opposed to these, this paper introduces a paradigm that has not been reported in the literature earlier, which we shall refer to as the Nearest Border (NB) paradigm. ...

    • A novel Border Identification algorithm based on an “Anti-Bayesian” paradigm 

      Thomas, Anu; Oommen, B. John (Lecture Notes in Computer Science;8047, Chapter; Peer reviewed, 2013)
      Border Identification (BI) algorithms, a subset of Prototype Reduction Schemes (PRS) aim to reduce the number of training vectors so that the reduced set (the border set) contains only those patterns which lie near the ...

    • A two-armed bandit collective for examplar based mining of frequent itemsets with applications to intrusion detection 

      Haugland, Vegard; Kjølleberg, Marius; Larsen, Svein-Erik; Granmo, Ole-Christoffer (Lecture Notes in Computer Science;6922, Chapter; Peer reviewed, 2011)
      Over the last decades, frequent itemset mining has become a major area of research, with applications including indexing and similarity search, as well as mining of data streams, web, and software bugs. Although several ...

    • Discretized Bayesian pursuit – A new scheme for reinforcement learning 

      Zhang, Xuan; Granmo, Ole-Christoffer; Oommen, B. John (Lecture Notes in Computer Science;7345, Chapter; Peer reviewed, 2012)
      The success of Learning Automata (LA)-based estimator algorithms over the classical, Linear Reward-Inaction ( L RI )-like schemes, can be explained by their ability to pursue the actions with the highest reward probability ...

    • Formal verification of a Cooperative Automatic Repeat reQuest MAC protocol 

      He, Xin; Kumar, Ram; Mu, Liping; Gjøsæter, Terje; Li, Frank Y. (Journal article; Peer reviewed, 2012)
      Cooperative communications, in which a relay node helps the source node to deliver its packets to the destination node, are able to obtain significant benefits in terms of transmission reliability, coverage extension and ...

    • Generalized Bayesian pursuit: A novel scheme for multi-armed Bernoulli bandit problems 

      Zhang, Xuan; Oommen, B. John; Granmo, Ole-Christoffer (IFIP Advances in Information and Communication Technology;364, Chapter; Peer reviewed, 2011)
      In the last decades, a myriad of approaches to the multi-armed bandit problem have appeared in several different fields. The current top performing algorithms from the field of Learning Automata reside in the Pursuit family, ...

    • Imposing tree-based topologies onto self organizing maps 

      Astudillo, César A.; Oommen, B. John (Journal article; Peer reviewed, 2011)
      The beauty of the Kohonen map is that it has the property of organizing the codebook vectors, which represent the data points, both with respect to the underlying distribution and topologically. This topology is traditionally ...

    • Multi-class pairwise linear dimensionality reduction using heteroscedastic schemes 

      Rueda, Luis; Oommen, B. John; Henríquez, Claudio (Peer reviewed; Journal article, 2010)
      Linear dimensionality reduction (LDR) techniques have been increasingly important in pattern recognition (PR) due to the fact that they permit a relatively simple mapping of the problem onto a lower-dimensional subspace, ...

    • On Optimizing Locally Linear Nearest Neighbour Reconstructions Using Prototype Reduction Schemes 

      Kim, Sang-Woon; Oommen, B. John (Lecture Notes in Computer Science;, Chapter; Peer reviewed, 2010)
      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 using the theory of regular functions to prove the ε-Optimality of the Continuous Pursuit Learning Automaton 

      Zhang, Xuan; Granmo, Ole-Christoffer; Oommen, B. John; Jiao, Lei (Lecture Notes in Computer Science;7906, Chapter; Peer reviewed, 2013)
      There are various families of Learning Automata (LA) such as Fixed Structure, Variable Structure, Discretized etc. Informally, if the environment is stationary, their ε-optimality is defined as their ability to converge ...

    • Peptide classification using optimal and information theoretic syntactic modeling 

      Aygün, Ezra; Oommen, B. John; Cataltepe, Z (Journal article; Peer reviewed, 2010)
      We consider the problem of classifying peptides using the information residing in their syntactic representations. This problem, which has been studied for more than a decade, has typically been investigated using ...

    • Ultimate Order Statistics-Based Prototype Reduction Schemes 

      Thomas, Anu; Oommen, B. John (Lecture Notes in Computer Science;8272, Chapter; Peer reviewed, 2013)
      The objective of Prototype Reduction Schemes (PRSs) and Border Identification (BI) algorithms is to reduce the number of training vectors, while simultaneously attempting to guarantee that the classifier built on the reduced ...