Blar i AURA på forfatter "Granmo, Ole-Christoffer"
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Combining unsupervised, supervised and rule-based learning: the case of detecting patient allergies in electronic health records
Berge, Geir Thore; Granmo, Ole-Christoffer; Tveit, Tor Oddbjørn; Ruthjersen, Anna Linda; Sharma, Jivitesh (Peer reviewed; Journal article, 2023)Background Data mining of electronic health records (EHRs) has a huge potential for improving clinical decision support and to help healthcare deliver precision medicine. Unfortunately, the rule-based and machine learning-based ... -
A Conclusive Analysis of the Finite-Time Behavior of the Discretized Pursuit Learning Automaton
Zhang, Xuan; Jiao, Lei; Oommen, John; Granmo, Ole-Christoffer (Journal article; Peer reviewed, 2019)This paper deals with the finite-time analysis (FTA) of learning automata (LA), which is a topic for which very little work has been reported in the literature. This is as opposed to the asymptotic steady-state analysis ... -
Convolutional Tsetlin Machine-based Training and Inference Accelerator for 2-D Pattern Classification
Tunheim, Svein Anders; Lei, Jiao; Shafik, Rishad Ahmed; Yakovlev, Alexandre; Granmo, Ole-Christoffer (Peer reviewed; Journal article, 2023)The Tsetlin Machine (TM) is a machine learning algorithm based on an ensemble of Tsetlin Automata (TAs) that learns propositional logic expressions from Boolean input features. In this paper, the design and implementation ... -
Cyclostationary Random Number Sequences for the Tsetlin Machine
Tunheim, Svein Anders; Yadav, Rohan Kumar; Lei, Jiao; Shafik, Rishad; Granmo, Ole-Christoffer (Peer reviewed; Journal article, 2022)The Tsetlin Machine (TM) constitutes an emerging machine learning algorithm that has shown competitive performance on several benchmarks. The underlying concept of the TM is propositional logic determined by a group of ... -
Deep Q-Learning With Q-Matrix Transfer Learning for Novel Fire Evacuation Environment
Sharma, Jivitesh; Andersen, Per-Arne; Granmo, Ole-Christoffer; Goodwin, Morten (Journal article; Peer reviewed, 2020) -
Deep Reinforcement Learning using Capsules in Advanced Game Environments
Andersen, Per-Arne; Goodwin, Morten; Granmo, Ole-Christoffer (Master thesis, 2018)Reinforcement Learning (RL) is a research area that has blossomed tremendously in recent years and has shown remarkable potential for artificial intelligence based opponents in computer games. This success is primarily due ... -
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 ... -
Environment Sound Classification using Multiple Feature Channels and Attention based Deep Convolutional Neural Network
Sharma, Jivitesh; Granmo, Ole-Christoffer; Goodwin, Morten (Peer reviewed; Journal article, 2020)In this paper, we propose a model for the Environment Sound Classification Task (ESC) that consists of multiple feature channels given as input to a Deep Convolutional Neural Network (CNN) with Attention mechanism. The ... -
Escape planning in realistic fire scenarios with Ant Colony Optimisation
Goodwin, Morten; Granmo, Ole-Christoffer; Radianti, Jaziar (Journal article; Peer reviewed, 2014)An emergency requiring evacuation is a chaotic event, filled with uncertainties both for the people affected and rescuers. The evacuees are often left to themselves for navigation to the escape area. The chaotic situation ... -
Explainable Tsetlin Machine Framework for Fake News Detection with Credibility Score Assessment
Bhattarai, Bimal; Granmo, Ole-Christoffer; Lei, Jiao (Chapter, 2022)The proliferation of fake news, i.e., news intentionally spread for misinformation, poses a threat to individuals and society. Despite various fact-checking websites such as PolitiFact, robust detection techniques are ... -
Explainable Tsetlin Machine Framework for Fake News Detection with Credibility Score Assessment
Granmo, Ole-Christoffer; Jiao, Lei (Journal article, 2022)The proliferation of fake news, i.e., news intentionally spread for misinformation, poses a threat to individuals and society. Despite various fact-checking websites such as PolitiFact, robust detection techniques are ... -
Extending the Tsetlin Machine With Integer-Weighted Clauses for Increased Interpretability
Abeyrathna, Kuruge Darshana; Granmo, Ole-Christoffer; Goodwin, Morten (Peer reviewed; Journal article, 2021) -
FlashRL: A Reinforcement Learning Platform for Flash Games
Andersen, Per-Arne; Goodwin, Morten; Granmo, Ole-Christoffer (Journal article; Peer reviewed, 2017) -
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, ... -
Increasing sample efficiency in deep reinforcement learning using generative environment modelling
Andersen, Per-Arne; Goodwin, Morten; Granmo, Ole-Christoffer (Journal article; Peer reviewed, 2020) -
Indoor Space Classification Using Cascaded LSTM
Yadav, Rohan Kumar; Bhattarai, Bimal; Lei, Jiao; Goodwin, Morten; Granmo, Ole-Christoffer (Journal article; Peer reviewed, 2020)Indoor space classification is an important part of localization that helps in precise location extraction, which has been extensively utilized in industrial and domestic domain. There are various approaches that employ ... -
An Interpretable Knowledge Representation Framework for Natural Language Processing with Cross-Domain Application
Bhattarai, Bimal; Granmo, Ole-Christoffer; Lei, Jiao (Lecture Notes in Computer Science;13980, Chapter; Peer reviewed, 2023)Data representation plays a crucial role in natural language processing (NLP), forming the foundation for most NLP tasks. Indeed, NLP performance highly depends upon the effectiveness of the preprocessing pipeline that ... -
Language Detection and Tracking in Multilingual Documents Using Weak Estimators
Stensby, Aleksander; Oommen, B. John; Granmo, Ole-Christoffer (Chapter; Peer reviewed, 2010)This paper deals with the extremely complicated problem of language detection and tracking in real-life electronic (for example, in Word-of-Mouth (WoM)) applications, where various segments of the text are written in ... -
Learning automata based energy-efficient AI hardware design for IoT applications: Learning Automata based AI Hardware
Wheeldon, Adrian; Shafik, Rishad; Rahman, Tousif; Lei, Jie; Yakovlev, Alex; Granmo, Ole-Christoffer (Peer reviewed; Journal article, 2020) -
A Learning Automata Based Solution to Service Selection in Stochastic Environments
Yazidi, Anis; Granmo, Ole-Christoffer; Oommen, B. John (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 ...