Universitetet Agder

∙ Kristiansand , Norway ∙ 0 followers

003222 The University of Agder, formerly known as Agder College and Agder University College, is a public university with campuses in Kristiansand and Grimstad, Norway.

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

Tsetlin Machines (TMs) capture patterns using conjunctive clauses in pro...
07/27/2020 ∙ by Christian D. Blakely, et al. ∙ 16 ∙ share

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The Dreaming Variational Autoencoder for Reinforcement Learning Environments

Reinforcement learning has shown great potential in generalizing over ra...
10/02/2018 ∙ by Per-Arne Andersen, et al. ∙ 10 ∙ share

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Environment Sound Classification using Multiple Feature Channels and Deep Convolutional Neural Networks

In this paper, we propose a model for the Environment Sound Classificati...
08/28/2019 ∙ by Jivitesh Sharma, et al. ∙ 8 ∙ share

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Deep RTS: A Game Environment for Deep Reinforcement Learning in Real-Time Strategy Games

Reinforcement learning (RL) is an area of research that has blossomed tr...
08/15/2018 ∙ by Per-Arne Andersen, et al. ∙ 2 ∙ share

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Inference of Spatio-Temporal Functions over Graphs via Multi-Kernel Kriged Kalman Filtering

Inference of space-time varying signals on graphs emerges naturally in a...
11/25/2017 ∙ by Vassilis N. Ioannidis, et al. ∙ 0 ∙ share

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Thompson Sampling Guided Stochastic Searching on the Line for Deceptive Environments with Applications to Root-Finding Problems

The multi-armed bandit problem forms the foundation for solving a wide r...
08/05/2017 ∙ by Sondre Glimsdal, et al. ∙ 0 ∙ share

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

A number of intriguing decision scenarios revolve around partitioning a ...
07/11/2017 ∙ by Sondre Glimsdal, et al. ∙ 0 ∙ share

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Bayesian Unification of Gradient and Bandit-based Learning for Accelerated Global Optimisation

Bandit based optimisation has a remarkable advantage over gradient based...
05/28/2017 ∙ by Ole-Christoffer Granmo, et al. ∙ 0 ∙ share

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Adaptive Task Assignment in Online Learning Environments

With the increasing popularity of online learning, intelligent tutoring ...
06/23/2016 ∙ by Per-Arne Andersen, et al. ∙ 0 ∙ share

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Learning Power Spectrum Maps from Quantized Power Measurements

Power spectral density (PSD) maps providing the distribution of RF power...
06/07/2016 ∙ by Daniel Romero, et al. ∙ 0 ∙ share

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

Although simple individually, artificial neurons provide state-of-the-ar...
04/04/2018 ∙ by Ole-Christoffer Granmo, et al. ∙ 0 ∙ share

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Concurrent Computing with Shared Replicated Memory

The behavioural theory of concurrent systems states that any concurrent ...
02/13/2019 ∙ by Klaus-Dieter Schewe, et al. ∙ 0 ∙ share

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A Scheme for Continuous Input to the Tsetlin Machine with Applications to Forecasting Disease Outbreaks

In this paper, we apply a new promising tool for pattern classification,...
05/10/2019 ∙ by K. Darshana Abeyrathna, et al. ∙ 0 ∙ share

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Deep Q-Learning with Q-Matrix Transfer Learning for Novel Fire Evacuation Environment

We focus on the important problem of emergency evacuation, which clearly...
05/23/2019 ∙ by Jivitesh Sharma, et al. ∙ 0 ∙ share

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Towards Model-based Reinforcement Learning for Industry-near Environments

Deep reinforcement learning has over the past few years shown great pote...
07/27/2019 ∙ by Per-Arne Andersen, et al. ∙ 0 ∙ share

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Performance Evaluation of the LoRa Protocol in the context of Smart Meter

In recent years, the use of Low Power Wide Area Network (LPWAN) is incre...
07/04/2019 ∙ by Muhammad Nouman Rafi, et al. ∙ 0 ∙ share

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A Tsetlin Machine with Multigranular Clauses

The recently introduced Tsetlin Machine (TM) has provided competitive pa...
09/16/2019 ∙ by Saeed Rahimi Gorji, et al. ∙ 0 ∙ share

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Accurate Graph Filtering in Wireless Sensor Networks

Wireless sensor networks (WSNs) are considered as a major technology ena...
04/24/2020 ∙ by Leila Ben Saad, et al. ∙ 0 ∙ share

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Extending the Tsetlin Machine With Integer-Weighted Clauses for Increased Interpretability

Despite significant effort, building models that are both interpretable ...
05/11/2020 ∙ by K. Darshana Abeyrathna, et al. ∙ 0 ∙ share

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An Exploratory Study of COVID-19 Misinformation on Twitter

Although a lot of correct and useful information is shared through chann...
05/12/2020 ∙ by Gautam Kishore Shahi, et al. ∙ 0 ∙ share

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A Novel Multi-Step Finite-State Automaton for Arbitrarily Deterministic Tsetlin Machine Learning

Due to the high energy consumption and scalability challenges of deep le...
07/04/2020 ∙ by K. Darshana Abeyrathna, et al. ∙ 0 ∙ share

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Universitetet Agder

Featured Researchers

Ole-Christoffer Granmo

Morten Goodwin

Per-Arne Andersen

Baltasar Beferull-Lozano

K. Darshana Abeyrathna

Daniel Romero

Sondre Glimsdal

Jivitesh Sharma

Saeed Rahimi Gorji

Leila Ben Saad

Andreas Prinz

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

The Dreaming Variational Autoencoder for Reinforcement Learning Environments

Environment Sound Classification using Multiple Feature Channels and Deep Convolutional Neural Networks

Deep RTS: A Game Environment for Deep Reinforcement Learning in Real-Time Strategy Games

Inference of Spatio-Temporal Functions over Graphs via Multi-Kernel Kriged Kalman Filtering

Thompson Sampling Guided Stochastic Searching on the Line for Deceptive Environments with Applications to Root-Finding Problems

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

Bayesian Unification of Gradient and Bandit-based Learning for Accelerated Global Optimisation

Adaptive Task Assignment in Online Learning Environments

Learning Power Spectrum Maps from Quantized Power Measurements

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

Concurrent Computing with Shared Replicated Memory

A Scheme for Continuous Input to the Tsetlin Machine with Applications to Forecasting Disease Outbreaks

Deep Q-Learning with Q-Matrix Transfer Learning for Novel Fire Evacuation Environment

Towards Model-based Reinforcement Learning for Industry-near Environments

Performance Evaluation of the LoRa Protocol in the context of Smart Meter

A Tsetlin Machine with Multigranular Clauses

Accurate Graph Filtering in Wireless Sensor Networks

Extending the Tsetlin Machine With Integer-Weighted Clauses for Increased Interpretability

An Exploratory Study of COVID-19 Misinformation on Twitter

A Novel Multi-Step Finite-State Automaton for Arbitrarily Deterministic Tsetlin Machine Learning