Ole-Christoffer Granmo

Orcid: 0000-0002-7287-030X

According to our database1, Ole-Christoffer Granmo authored at least 214 papers between 2002 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

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Bibliography

2024
Towards misinformation mitigation on social media: novel user activity representation for modeling societal acceptance.
J. Comput. Soc. Sci., April, 2024

Towards safe and sustainable reinforcement learning for real-time strategy games.
Inf. Sci., 2024

Exploring State Space and Reasoning by Elimination in Tsetlin Machines.
CoRR, 2024

Exploring Effects of Hyperdimensional Vectors for Tsetlin Machines.
CoRR, 2024

An Optimized Toolbox for Advanced Image Processing with Tsetlin Machine Composites.
CoRR, 2024

Streamlining Attention for Text Classification: Sequence Length Reduction with Pooling Attention.
Proceedings of the Artificial Intelligence XLI, 2024

Tsetlin Machine Embedding: Representing Words Using Logical Expressions.
Proceedings of the Findings of the Association for Computational Linguistics: EACL 2024, 2024

2023
Combining unsupervised, supervised and rule-based learning: the case of detecting patient allergies in electronic health records.
BMC Medical Informatics Decis. Mak., December, 2023

Machine learning-driven clinical decision support system for concept-based searching: a field trial in a Norwegian hospital.
BMC Medical Informatics Decis. Mak., December, 2023

REDRESS: Generating Compressed Models for Edge Inference Using Tsetlin Machines.
IEEE Trans. Pattern Anal. Mach. Intell., September, 2023

On the Convergence of Tsetlin Machines for the XOR Operator.
IEEE Trans. Pattern Anal. Mach. Intell., May, 2023

Using Tsetlin Machine to discover interpretable rules in natural language processing applications.
Expert Syst. J. Knowl. Eng., May, 2023

A multi-step finite-state automaton for arbitrarily deterministic Tsetlin Machine learning.
Expert Syst. J. Knowl. Eng., May, 2023

Off-policy and on-policy reinforcement learning with the Tsetlin machine.
Appl. Intell., April, 2023

Convolutional Tsetlin Machine-based Training and Inference Accelerator for 2-D Pattern Classification.
Microprocess. Microsystems, 2023

Efficient Data Fusion using the Tsetlin Machine.
CoRR, 2023

Harnessing Attention Mechanisms: Efficient Sequence Reduction using Attention-based Autoencoders.
CoRR, 2023

Contracting Tsetlin Machine with Absorbing Automata.
CoRR, 2023

Generalized Convergence Analysis of Tsetlin Machines: A Probabilistic Approach to Concept Learning.
CoRR, 2023

Learning Minimalistic Tsetlin Machine Clauses with Markov Boundary-Guided Pruning.
CoRR, 2023

TMComposites: Plug-and-Play Collaboration Between Specialized Tsetlin Machines.
CoRR, 2023

An FPGA Architecture for Online Learning using the Tsetlin Machine.
CoRR, 2023

Energy-frugal and Interpretable AI Hardware Design using Learning Automata.
CoRR, 2023

Verifying Properties of Tsetlin Machines.
CoRR, 2023

Interpretable Tsetlin Machine-based Premature Ventricular Contraction Identification.
CoRR, 2023

Towards artificial virtuous agents: games, dilemmas and machine learning.
AI Ethics, 2023

Extension of Regression Tsetlin Machine for Interpretable Uncertainty Assessment.
Proceedings of the Rules and Reasoning - 7th International Joint Conference, 2023

A Logic-Based Explainable Framework for Relation Classification of Human Rights Violations.
Proceedings of the 21st International Workshop on Non-Monotonic Reasoning co-located with the 20th International Conference on Principles of Knowledge Representation and Reasoning (KR 2023) and co-located with the 36th International Workshop on Description Logics (DL 2023), 2023

Building Concise Logical Patterns by Constraining Tsetlin Machine Clause Size.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Transfer Learning Through Knowledge-Infused Representations with Contextual Experts.
Proceedings of the Artificial Intelligence Applications and Innovations, 2023

Natural Language Modeling with the Tsetlin Machine.
Proceedings of the Advances and Trends in Artificial Intelligence. Theory and Applications, 2023

An Interpretable Knowledge Representation Framework for Natural Language Processing with Cross-Domain Application.
Proceedings of the Advances in Information Retrieval, 2023

Drop Clause: Enhancing Performance, Robustness and Pattern Recognition Capabilities of the Tsetlin Machine.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
MMSS: A storytelling simulation software to mitigate misinformation on social media.
Softw. Impacts, 2022

On the Convergence of Tsetlin Machines for the IDENTITY- and NOT Operators.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

A relational tsetlin machine with applications to natural language understanding.
J. Intell. Inf. Syst., 2022

On the Equivalence of the Weighted Tsetlin Machine and the Perceptron.
CoRR, 2022

Word-level human interpretable scoring mechanism for novel text detection using Tsetlin Machines.
Appl. Intell., 2022

Tsetlin Machine for Solving Contextual Bandit Problems.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Knowledge Infused Representations Through Combination of Expert Knowledge and Original Input.
Proceedings of the Nordic Artificial Intelligence Research and Development, 2022

Explainable Tsetlin Machine Framework for Fake News Detection with Credibility Score Assessment.
Proceedings of the Thirteenth Language Resources and Evaluation Conference, 2022

ConvTextTM: An Explainable Convolutional Tsetlin Machine Framework for Text Classification.
Proceedings of the Thirteenth Language Resources and Evaluation Conference, 2022

Logic-based AI for Interpretable Board Game Winner Prediction with Tsetlin Machine.
Proceedings of the International Joint Conference on Neural Networks, 2022

Robust Interpretable Text Classification against Spurious Correlations Using AND-rules with Negation.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Cyclostationary Random Number Sequences for the Tsetlin Machine.
Proceedings of the Advances and Trends in Artificial Intelligence. Theory and Practices in Artificial Intelligence, 2022

CaiRL: A High-Performance Reinforcement Learning Environment Toolkit.
Proceedings of the IEEE Conference on Games, CoG 2022, Beijing, 2022

Socially Fair Mitigation of Misinformation on Social Networks via Constraint Stochastic Optimization.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Deep Q-Learning With Q-Matrix Transfer Learning for Novel Fire Evacuation Environment.
IEEE Trans. Syst. Man Cybern. Syst., 2021

Positionless aspect based sentiment analysis using attention mechanism.
Knowl. Based Syst., 2021

Learning Automata-based Misinformation Mitigation via Hawkes Processes.
Inf. Syst. Frontiers, 2021

Increasing sample efficiency in deep reinforcement learning using generative environment modelling.
Expert Syst. J. Knowl. Eng., 2021

On the Convergence of Tsetlin Machines for the AND and the OR Operators.
CoRR, 2021

Coalesced Multi-Output Tsetlin Machines with Clause Sharing.
CoRR, 2021

Human Interpretable AI: Enhancing Tsetlin Machine Stochasticity with Drop Clause.
CoRR, 2021

Distributed Word Representation in Tsetlin Machine.
CoRR, 2021

Low-Power Audio Keyword Spotting using Tsetlin Machines.
CoRR, 2021

Extending the Tsetlin Machine With Integer-Weighted Clauses for Increased Interpretability.
IEEE Access, 2021

ORACLE: End-to-End Model Based Reinforcement Learning.
Proceedings of the Artificial Intelligence XXXVIII, 2021

Modelling Emotion Dynamics in Chatbots with Neural Hawkes Processes.
Proceedings of the Artificial Intelligence XXXVIII, 2021

Emergency Analysis: Multitask Learning with Deep Convolutional Neural Networks for Fire Emergency Scene Parsing.
Proceedings of the Advances and Trends in Artificial Intelligence. Artificial Intelligence Practices, 2021

Explainable Reinforcement Learning with the Tsetlin Machine.
Proceedings of the Advances and Trends in Artificial Intelligence. Artificial Intelligence Practices, 2021

Closed-Form Expressions for Global and Local Interpretation of Tsetlin Machines.
Proceedings of the Advances and Trends in Artificial Intelligence. Artificial Intelligence Practices, 2021

Convolutional Regression Tsetlin Machine: An Interpretable Approach to Convolutional Regression.
Proceedings of the ICMLT 2021: 6th International Conference on Machine Learning Technologies, Jeju Island, Republic of Korea, April 23, 2021

Massively Parallel and Asynchronous Tsetlin Machine Architecture Supporting Almost Constant-Time Scaling.
Proceedings of the 38th International Conference on Machine Learning, 2021

Interpretability in Word Sense Disambiguation using Tsetlin Machine.
Proceedings of the 13th International Conference on Agents and Artificial Intelligence, 2021

An Interpretable Word Sense Classifier for Human Explainable Chatbot.
Proceedings of the Agents and Artificial Intelligence - 13th International Conference, 2021

Measuring the Novelty of Natural Language Text using the Conjunctive Clauses of a Tsetlin Machine Text Classifier.
Proceedings of the 13th International Conference on Agents and Artificial Intelligence, 2021

A Tsetlin Machine Framework for Universal Outlier and Novelty Detection.
Proceedings of the Agents and Artificial Intelligence - 13th International Conference, 2021

Enhancing Interpretable Clauses Semantically using Pretrained Word Representation.
Proceedings of the Fourth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, 2021

Human-Level Interpretable Learning for Aspect-Based Sentiment Analysis.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
A Conclusive Analysis of the Finite-Time Behavior of the Discretized Pursuit Learning Automaton.
IEEE Trans. Neural Networks Learn. Syst., 2020

Towards safe reinforcement-learning in industrial grid-warehousing.
Inf. Sci., 2020

Combining a context aware neural network with a denoising autoencoder for measuring string similarities.
Comput. Speech Lang., 2020

Closed-Form Expressions for Global and Local Interpretation of Tsetlin Machines with Applications to Explaining High-Dimensional Data.
CoRR, 2020

A Regression Tsetlin Machine with Integer Weighted Clauses for Compact Pattern Representation.
CoRR, 2020

Intrusion Detection with Interpretable Rules Generated Using the Tsetlin Machine.
Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

Adaptive Continuous Feature Binarization for Tsetlin Machines Applied to Forecasting Dengue Incidences in the Philippines.
Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

On Obtaining Classification Confidence, Ranked Predictions and AUC with Tsetlin Machines.
Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

Mining Interpretable Rules for Sentiment and Semantic Relation Analysis Using Tsetlin Machines.
Proceedings of the Artificial Intelligence XXXVII, 2020

CostNet: An End-to-End Framework for Goal-Directed Reinforcement Learning.
Proceedings of the Artificial Intelligence XXXVII, 2020

A Novel Multi-step Finite-State Automaton for Arbitrarily Deterministic Tsetlin Machine Learning.
Proceedings of the Artificial Intelligence XXXVII, 2020

Safer Reinforcement Learning for Agents in Industrial Grid-Warehousing.
Proceedings of the Machine Learning, Optimization, and Data Science, 2020

Environment Sound Classification Using Multiple Feature Channels and Attention Based Deep Convolutional Neural Network.
Proceedings of the 21st Annual Conference of the International Speech Communication Association, 2020

Interpretable Option Discovery Using Deep Q-Learning and Variational Autoencoders.
Proceedings of the Intelligent Technologies and Applications, 2020

Increasing the Inference and Learning Speed of Tsetlin Machines with Clause Indexing.
Proceedings of the Trends in Artificial Intelligence Theory and Applications. Artificial Intelligence Practices, 2020

Integer Weighted Regression Tsetlin Machines.
Proceedings of the Trends in Artificial Intelligence Theory and Applications. Artificial Intelligence Practices, 2020

From Arithmetic to Logic based AI: A Comparative Analysis of Neural Networks and Tsetlin Machine.
Proceedings of the 27th IEEE International Conference on Electronics, Circuits and Systems, 2020

2019
Thompson Sampling Guided Stochastic Searching on the Line for Deceptive Environments with Applications to Root-Finding Problems.
J. Mach. Learn. Res., 2019

Multi-layer intrusion detection system with ExtraTrees feature selection, extreme learning machine ensemble, and softmax aggregation.
EURASIP J. Inf. Secur., 2019

The Weighted Tsetlin Machine: Compressed Representations with Weighted Clauses.
CoRR, 2019

A Neural Turing~Machine for Conditional Transition Graph Modeling.
CoRR, 2019

The Convolutional Tsetlin Machine.
CoRR, 2019

Using the Tsetlin Machine to Learn Human-Interpretable Rules for High-Accuracy Text Categorization With Medical Applications.
IEEE Access, 2019

A Tsetlin Machine with Multigranular Clauses.
Proceedings of the Artificial Intelligence XXXVI, 2019

Towards Model-Based Reinforcement Learning for Industry-Near Environments.
Proceedings of the Artificial Intelligence XXXVI, 2019

Hydropower Optimization Using Deep Learning.
Proceedings of the Advances and Trends in Artificial Intelligence. From Theory to Practice, 2019

On Using "Stochastic Learning on the Line" to Design Novel Distance Estimation Methods for Three-Dimensional Environments.
Proceedings of the Advances and Trends in Artificial Intelligence. From Theory to Practice, 2019

Thompson Sampling Based Active Learning in Probabilistic Programs with Application to Travel Time Estimation.
Proceedings of the Advances and Trends in Artificial Intelligence. From Theory to Practice, 2019

A Scheme for Continuous Input to the Tsetlin Machine with Applications to Forecasting Disease Outbreaks.
Proceedings of the Advances and Trends in Artificial Intelligence. From Theory to Practice, 2019

An Iterative Information Retrieval Approach from Social Media in Crisis Situations.
Proceedings of the 5th International Conference on Information and Communication Technologies for Disaster Management, 2019

Hydropower Optimization Using Split-Window, Meta-Heuristic and Genetic Algorithms.
Proceedings of the 18th IEEE International Conference On Machine Learning And Applications, 2019

Causality-based Social Media Analysis for Normal Users Credibility Assessment in a Political Crisis.
Proceedings of the 25th Conference of Open Innovations Association, 2019

The Regression Tsetlin Machine: A Tsetlin Machine for Continuous Output Problems.
Proceedings of the Progress in Artificial Intelligence, 2019

2018
The Tsetlin Machine - A Game Theoretic Bandit Driven Approach to Optimal Pattern Recognition with Propositional Logic.
CoRR, 2018

A Bayesian network based solution scheme for the constrained Stochastic On-line Equi-Partitioning Problem.
Appl. Intell., 2018

Novel Distance Estimation Methods Using "Stochastic Learning on the Line" Strategies.
IEEE Access, 2018

The Dreaming Variational Autoencoder for Reinforcement Learning Environments.
Proceedings of the Artificial Intelligence XXXV, 2018

Effect of Data from Neighbouring Regions to Forecast Dengue Incidences in Different Regions of Philippines Using Artificial Neural Networks.
Proceedings of the 31st Norsk Informatikkonferanse, 2018

On Using "Stochastic Learning on the Line" to Design Novel Distance Estimation Methods.
Proceedings of the Recent Trends and Future Technology in Applied Intelligence, 2018

A Novel Tsetlin Automata Scheme to Forecast Dengue Outbreaks in the Philippines.
Proceedings of the IEEE 30th International Conference on Tools with Artificial Intelligence, 2018

Deep CNN-ELM Hybrid Models for Fire Detection in Images.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2018, 2018

Deep RTS: A Game Environment for Deep Reinforcement Learning in Real-Time Strategy Games.
Proceedings of the 2018 IEEE Conference on Computational Intelligence and Games, 2018

Solution of Dual Fuzzy Equations Using a New Iterative Method.
Proceedings of the Intelligent Information and Database Systems - 10th Asian Conference, 2018

2017
The design of absorbing Bayesian pursuit algorithms and the formal analyses of their ε-optimality.
Pattern Anal. Appl., 2017

An Optimal Bayesian Network Based Solution Scheme for the Constrained Stochastic On-line Equi-Partitioning Problem.
CoRR, 2017

A Learning Automata Local Contribution Sampling Applied to Hydropower Production Optimisation.
Proceedings of the Artificial Intelligence XXXIV, 2017

Towards a Deep Reinforcement Learning Approach for Tower Line Wars.
Proceedings of the Artificial Intelligence XXXIV, 2017

FlashRL: A Reinforcement Learning Platform for Flash Games.
Proceedings of the 30th Norsk Informatikkonferanse, 2017

Combining Unsupervised, Supervised, and Rule-based Algorithms for Text Mining of Electronic Health Records - A Clinical Decision Support System for Identifying and Classifying Allergies of Concern for Anesthesia During Surgery.
Proceedings of the Information Systems Development: Advances in Methods, Tools and Management, 2017

Towards Open Domain Chatbots - A GRU Architecture for Data Driven Conversations.
Proceedings of the Internet Science, 2017

Deep Convolutional Neural Networks for Fire Detection in Images.
Proceedings of the Engineering Applications of Neural Networks, 2017

Vector representation of non-standard spellings using dynamic time warping and a denoising autoencoder.
Proceedings of the 2017 IEEE Congress on Evolutionary Computation, 2017

2016
Stochastic discretized learning-based weak estimation: a novel estimation method for non-stationary environments.
Pattern Recognit., 2016

A formal proof of the 𝜀-optimality of discretized pursuit algorithms.
Appl. Intell., 2016

Optimizing channel selection for cognitive radio networks using a distributed Bayesian learning automata-based approach.
Appl. Intell., 2016

Deep Learning for Social Media Analysis in Crises Situations (Position paper).
Proceedings of the 29th Annual Workshop of the Swedish Artificial Intelligence Society, 2016

Towards Evacuation Planning of Groups with Genetic Algorithms.
Proceedings of the 29th Annual Workshop of the Swedish Artificial Intelligence Society, 2016

Information Abstraction from Crises Related Tweets Using Recurrent Neural Network.
Proceedings of the Artificial Intelligence Applications and Innovations, 2016

Bayesian Unification of Gradient and Bandit-Based Learning for Accelerated Global Optimisation.
Proceedings of the 15th IEEE International Conference on Machine Learning and Applications, 2016

2015
Fire simulation-based adaptation of SmartRescue App for serious game: Design, setup and user experience.
Eng. Appl. Artif. Intell., 2015

A spatio-temporal probabilistic model of hazard- and crowd dynamics for evacuation planning in disasters.
Appl. Intell., 2015

Escape planning in realistic fire scenarios with Ant Colony Optimisation.
Appl. Intell., 2015

A Bayesian Network Model for Fire Assessment and Prediction.
Proceedings of the Machine Learning, Optimization, and Big Data, 2015

SmartRescue: Architecture for Fire Crisis Assessment and Prediction.
Proceedings of the 12th Proceedings of the International Conference on Information Systems for Crisis Response and Management, 2015

Thompson Sampling Guided Stochastic Searching on the Line for Adversarial Learning.
Proceedings of the Artificial Intelligence Applications and Innovations, 2015

Modeling Snow Dynamics Using a Bayesian Network.
Proceedings of the Current Approaches in Applied Artificial Intelligence, 2015

A methodology for fire data analysis based on pattern recognition towards the disaster management.
Proceedings of the 2nd International Conference on Information and Communication Technologies for Disaster Management, 2015

Thompson Sampling Guided Stochastic Searching on the Line for Non-stationary Adversarial Learning.
Proceedings of the 14th IEEE International Conference on Machine Learning and Applications, 2015

2014
A Novel Strategy for Solving the Stochastic Point Location Problem Using a Hierarchical Searching Scheme.
IEEE Trans. Cybern., 2014

A Two-Armed Bandit Collective for Hierarchical Examplar Based Mining of Frequent Itemsets with Applications to Intrusion Detection.
Trans. Comput. Collect. Intell., 2014

Comparing Different Crowd Emergency Evacuation Models Based on Human Centered Sensing Criteria.
Int. J. Inf. Syst. Crisis Response Manag., 2014

A formal proof of the ε-optimality of absorbing continuous pursuit algorithms using the theory of regular functions.
Appl. Intell., 2014

Publish-subscribe smartphone sensing platform for the acute phase of a disaster: A framework for emergency management support.
Proceedings of the 2014 IEEE International Conference on Pervasive Computing and Communication Workshops, 2014

Smartphone sensing platform for emergency management.
Proceedings of the 11th Proceedings of the International Conference on Information Systems for Crisis Response and Management, 2014

Using the Theory of Regular Functions to Formally Prove the ε-Optimality of Discretized Pursuit Learning Algorithms.
Proceedings of the Modern Advances in Applied Intelligence, 2014

A Bayesian Learning Automata-Based Distributed Channel Selection Scheme for Cognitive Radio Networks.
Proceedings of the Modern Advances in Applied Intelligence, 2014

A Novel Bayesian Network Based Scheme for Finding the Optimal Solution to Stochastic Online Equi-partitioning Problems.
Proceedings of the 13th International Conference on Machine Learning and Applications, 2014

On Utilizing Stochastic Non-linear Fractional Bin Packing to Resolve Distributed Web Crawling.
Proceedings of the 17th IEEE International Conference on Computational Science and Engineering, 2014

2013
Learning-Automaton-Based Online Discovery and Tracking of Spatiotemporal Event Patterns.
IEEE Trans. Cybern., 2013

The Use of Weak estimators to Achieve Language Detection and Tracking in Multilingual Documents.
Int. J. Pattern Recognit. Artif. Intell., 2013

On incorporating the paradigms of discretization and Bayesian estimation to create a new family of pursuit learning automata.
Appl. Intell., 2013

Accelerated Bayesian learning for decentralized two-armed bandit based decision making with applications to the Goore Game.
Appl. Intell., 2013

Channel selection in Cognitive Radio Networks: A Switchable Bayesian Learning Automata approach.
Proceedings of the 24th IEEE Annual International Symposium on Personal, 2013

Gaussian Process Based Optimistic Knapsack Sampling with Applications to Stochastic Resource Allocation.
Proceedings of the 24th Midwest Artificial Intelligence and Cognitive Science Conference 2013, 2013

On Using the Theory of Regular Functions to Prove the <i>ε</i>-Optimality of the Continuous Pursuit Learning Automaton.
Proceedings of the Recent Trends in Applied Artificial Intelligence, 2013

Ant Colony Optimisation for Planning Safe Escape Routes.
Proceedings of the Recent Trends in Applied Artificial Intelligence, 2013

A Spatio-temporal Probabilistic Model of Hazard and Crowd Dynamics in Disasters for Evacuation Planning.
Proceedings of the Recent Trends in Applied Artificial Intelligence, 2013

Arm Space Decomposition as a Strategy for Tackling Large Scale Multi-armed Bandit Problems.
Proceedings of the 12th International Conference on Machine Learning and Applications, 2013

Crowd Models for Emergency Evacuation: A Review Targeting Human-Centered Sensing.
Proceedings of the 46th Hawaii International Conference on System Sciences, 2013

A Bayesian network model for evacuation time analysis during a ship fire.
Proceedings of the 2013 IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments, 2013

2012
An Adaptive Approach to Learning the Preferences of Users in a Social Network Using Weak Estimators.
J. Inf. Process. Syst., 2012

Service selection in stochastic environments: a learning-automaton based solution.
Appl. Intell., 2012

Multidisciplinary challenges in an integrated emergency management approach.
Proceedings of the 9th Proceedings of the International Conference on Information Systems for Crisis Response and Management, 2012

Discretized Bayesian Pursuit - A New Scheme for Reinforcement Learning.
Proceedings of the Advanced Research in Applied Artificial Intelligence, 2012

A Hierarchical Learning Scheme for Solving the Stochastic Point Location Problem.
Proceedings of the Advanced Research in Applied Artificial Intelligence, 2012

A Stochastic Search on the Line-Based Solution to Discretized Estimation.
Proceedings of the Advanced Research in Applied Artificial Intelligence, 2012

A novel Stochastic Discretized Weak Estimator operating in non-stationary environments.
Proceedings of the International Conference on Computing, Networking and Communications, 2012

2011
A User-Centric Approach for Personalized Service Provisioning in Pervasive Environments.
Wirel. Pers. Commun., 2011

Learning automata-based solutions to the optimal web polling problem modelled as a nonlinear fractional knapsack problem.
Eng. Appl. Artif. Intell., 2011

Successive Reduction of Arms in Multi-Armed Bandits.
Proceedings of the Research and Development in Intelligent Systems XXVIII, 2011

Generalized Bayesian Pursuit: A Novel Scheme for Multi-Armed Bernoulli Bandit Problems.
Proceedings of the Artificial Intelligence Applications and Innovations, 2011

The Bayesian Pursuit Algorithm: A New Family of Estimator Learning Automata.
Proceedings of the Modern Approaches in Applied Intelligence, 2011

A Two-Armed Bandit Based Scheme for Accelerated Decentralized Learning.
Proceedings of the Modern Approaches in Applied Intelligence, 2011

Thompson Sampling for Dynamic Multi-armed Bandits.
Proceedings of the 10th International Conference on Machine Learning and Applications and Workshops, 2011

A Two-Armed Bandit Collective for Examplar Based Mining of Frequent Itemsets with Applications to Intrusion Detection.
Proceedings of the Computational Collective Intelligence. Technologies and Applications, 2011

A New Tool for the Modeling of AI and Machine Learning Applications: Random Walk-Jump Processes.
Proceedings of the Hybrid Artificial Intelligent Systems - 6th International Conference, 2011

On the analysis of a new Markov chain which has applications in AI and machine learning.
Proceedings of the 24th Canadian Conference on Electrical and Computer Engineering, 2011

Tracking the Preferences of Users Using Weak Estimators.
Proceedings of the AI 2011: Advances in Artificial Intelligence, 2011

2010
Solving Stochastic Nonlinear Resource Allocation Problems Using a Hierarchy of Twofold Resource Allocation Automata.
IEEE Trans. Computers, 2010

Solving two-armed Bernoulli bandit problems using a Bayesian learning automaton.
Int. J. Intell. Comput. Cybern., 2010

Stochastic Learning for SAT- Encoded Graph Coloring Problems.
Int. J. Appl. Metaheuristic Comput., 2010

Combining finite learning automata with GSAT for the satisfiability problem.
Eng. Appl. Artif. Intell., 2010

Optimal sampling for estimation with constrained resources using a learning automaton-based solution for the nonlinear fractional knapsack problem.
Appl. Intell., 2010

Language Detection and Tracking in Multilingual Documents Using Weak Estimators.
Proceedings of the Structural, 2010

Learning Automaton Based On-Line Discovery and Tracking of Spatio-temporal Event Patterns.
Proceedings of the PRICAI 2010: Trends in Artificial Intelligence, 2010

A Learning Automata Based Solution to Service Selection in Stochastic Environments.
Proceedings of the Trends in Applied Intelligent Systems, 2010

Solving Non-Stationary Bandit Problems by Random Sampling from Sibling Kalman Filters.
Proceedings of the Trends in Applied Intelligent Systems, 2010

A Generic Solution to Multi-Armed Bernoulli Bandit Problems based on Random Sampling from Sibling Conjugate Priors.
Proceedings of the ICAART 2010 - Proceedings of the International Conference on Agents and Artificial Intelligence, Volume 1, 2010

Enhancing Local-search based SAT Solvers with Learning Capability.
Proceedings of the ICAART 2010 - Proceedings of the International Conference on Agents and Artificial Intelligence, Volume 1, 2010

2009
Learning Automata-Based Solutions to Stochastic Nonlinear Resource Allocation Problems.
Proceedings of the Natural Intelligence for Scheduling, Planning and Packing Problems, 2009

A Hierarchy of Twofold Resource Allocation Automata Supporting Optimal Sampling.
Proceedings of the Next-Generation Applied Intelligence, 2009

2008
A Solution to the Stochastic Point Location Problem in Metalevel Nonstationary Environments.
IEEE Trans. Syst. Man Cybern. Part B, 2008

The Bayesian Learning Automaton - Empirical Evaluation with Two-Armed Bernoulli Bandit Problems.
Proceedings of the Research and Development in Intelligent Systems XXV, 2008

A Hierarchy of Twofold Resource Allocation Automata Supporting Optimal Web Polling.
Proceedings of the New Frontiers in Applied Artificial Intelligence, 2008

A Bayesian Learning Automaton for Solving Two-Armed Bernoulli Bandit Problems.
Proceedings of the Seventh International Conference on Machine Learning and Applications, 2008

Solving Graph Coloring Problems Using Learning Automata.
Proceedings of the Evolutionary Computation in Combinatorial Optimization, 2008

2007
Learning Automata-Based Solutions to the Nonlinear Fractional Knapsack Problem With Applications to Optimal Resource Allocation.
IEEE Trans. Syst. Man Cybern. Part B, 2007

Routing Bandwidth-Guaranteed Paths in MPLS Traffic Engineering: A Multiple Race Track Learning Approach.
IEEE Trans. Computers, 2007

Solving the Satisfiability Problem Using Finite Learning Automata.
Int. J. Comput. Sci. Appl., 2007

Stochastic Point Location in Non-stationary Environments and Its Applications.
Proceedings of the New Trends in Applied Artificial Intelligence, 2007

Using Stochastic AI Techniques to Achieve Unbounded Resolution in Finite Player Goore Games and its Applications.
Proceedings of the 2007 IEEE Symposium on Computational Intelligence and Games, 2007

On Using a Hierarchy of Twofold Resource Allocation Automata to Solve Stochastic Nonlinear Resource Allocation Problems.
Proceedings of the AI 2007: Advances in Artificial Intelligence, 2007

2006
Real-time video content analysis: QoS-aware application composition and parallel processing.
ACM Trans. Multim. Comput. Commun. Appl., 2006

A Stochastic Random-Races Algorithm for Routing in MPLS Traffic Engineering.
Proceedings of the INFOCOM 2006. 25th IEEE International Conference on Computer Communications, 2006

On Allocating Limited Sampling Resources Using a Learning Automata-based Solution to the Fractional Knapsack Problem.
Proceedings of the Intelligent Information Processing and Web Mining, 2006

Empirical Verification of a Strategy for Unbounded Resolution in Finite Player Goore Games.
Proceedings of the AI 2006: Advances in Artificial Intelligence, 2006

2004
Parallel hypothesis driven video content analysis.
Proceedings of the 2004 ACM Symposium on Applied Computing (SAC), 2004

2003
Techniques for Parallel Execution of the Particle Filter.
Proceedings of the Image Analysis, 13th Scandinavian Conference, 2003

Supporting timeliness and accuracy in distributed real-time content-based video analysis.
Proceedings of the Eleventh ACM International Conference on Multimedia, 2003

Towards a Probabilistic Framework for Analogous Multi-Modal Human-Computer Interaction.
Proceedings of the Human-Computer Interaction: Universal Access in HCI: Inclusive Design in the Information Society, 2003

2002
Automatic Resource-aware Construction of Media Indexing Applications for Distributed Processing Environments.
Proceedings of the Pattern Recognition in Information Systems, 2002

Real-time Hypothesis Driven Feature Extraction on Parallel Processing Architectures.
Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications, 2002

Scalable Independent Multi-level Distribution in Multimedia Content Analysis.
Proceedings of the Protocols and Systems for Interactive Distributed Multimedia, 2002

Real-Time Processing of Media Streams: A Case for Event-Based Interaction.
Proceedings of the 22nd International Conference on Distributed Computing Systems, 2002


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