Michael Fairbank

Orcid: 0000-0003-3833-7875

According to our database1, Michael Fairbank authored at least 38 papers between 1999 and 2023.

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

Timeline

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Bibliography

2023
A Minimal "Functionally Sentient" Organism Trained With Backpropagation Through Time.
Adapt. Behav., December, 2023

Demand management in time-slotted last-mile delivery via dynamic routing with forecast orders.
Eur. J. Oper. Res., September, 2023

2022
Deep Learning in Target Space.
J. Mach. Learn. Res., 2022

An Iterative Optimization and Learning-Based IoT System for Energy Management of Connected Buildings.
IEEE Internet Things J., 2022

Grokking-like effects in counterfactual inference.
Proceedings of the International Joint Conference on Neural Networks, 2022

2021
Control of a Buck DC/DC Converter Using Approximate Dynamic Programming and Artificial Neural Networks.
IEEE Trans. Circuits Syst. I Regul. Pap., 2021

A Comparison of Deep-Learning Methods for Analysing and Predicting Business Processes.
Proceedings of the International Joint Conference on Neural Networks, 2021

2020
Neural-Network Vector Controller for Permanent-Magnet Synchronous Motor Drives: Simulated and Hardware-Validated Results.
IEEE Trans. Cybern., 2020

Deep Learning in Target Space.
CoRR, 2020

Baseline win rates for neural-network based trading algorithms.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Practical Game Design Tool: State Explorer.
Proceedings of the IEEE Conference on Games, 2020

2019
Mek: Mechanics Prototyping Tool for 2D Tile-Based Turn-Based Deterministic Games.
Proceedings of the IEEE Conference on Games, 2019

Extracting Learning Curves From Puzzle Games.
Proceedings of the 11th Computer Science and Electronic Engineering Conference, 2019

2017
Convolutional-Match Networks for Question Answering.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Diversity maintenance using a population of repelling random-mutation hill climbers.
Proceedings of the 2017 9th Computer Science and Electronic Engineering Conference, 2017

Convolutional neural networks applied to high-frequency market microstructure forecasting.
Proceedings of the 2017 9th Computer Science and Electronic Engineering Conference, 2017

2016
Optimal resampling for the noisy OneMax problem.
CoRR, 2016

Match memory recurrent networks.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

2015
Training Recurrent Neural Networks With the Levenberg-Marquardt Algorithm for Optimal Control of a Grid-Connected Converter.
IEEE Trans. Neural Networks Learn. Syst., 2015

Back to optimality: a formal framework to express the dynamics of learning optimal behavior.
Adapt. Behav., 2015

Control of Three-Phase Grid-Connected Microgrids using Artificial Neural Networks.
Proceedings of the 7th International Joint Conference on Computational Intelligence (IJCCI 2015), 2015

2014
Value-gradient learning.
PhD thesis, 2014

Artificial Neural Networks for Control of a Grid-Connected Rectifier/Inverter Under Disturbance, Dynamic and Power Converter Switching Conditions.
IEEE Trans. Neural Networks Learn. Syst., 2014

Clipping in Neurocontrol by Adaptive Dynamic Programming.
IEEE Trans. Neural Networks Learn. Syst., 2014

An adaptive recurrent neural-network controller using a stabilization matrix and predictive inputs to solve a tracking problem under disturbances.
Neural Networks, 2014

2013
An Equivalence Between Adaptive Dynamic Programming With a Critic and Backpropagation Through Time.
IEEE Trans. Neural Networks Learn. Syst., 2013

The Importance of Clipping in Neurocontrol by Direct Gradient Descent on the Cost-to-Go Function and in Adaptive Dynamic Programming
CoRR, 2013

Emergent and Adaptive Systems of Systems.
Proceedings of the IEEE International Conference on Systems, 2013

Nested-loop neural network vector control of permanent magnet synchronous motors.
Proceedings of the 2013 International Joint Conference on Neural Networks, 2013

2012
Simple and Fast Calculation of the Second-Order Gradients for Globalized Dual Heuristic Dynamic Programming in Neural Networks.
IEEE Trans. Neural Networks Learn. Syst., 2012

Efficient Calculation of the Gauss-Newton Approximation of the Hessian Matrix in Neural Networks.
Neural Comput., 2012

Vector control of a grid-connected rectifier/inverter using an artificial neural network.
Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

The divergence of reinforcement learning algorithms with value-iteration and function approximation.
Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

Value-gradient learning.
Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

A comparison of learning speed and ability to cope without exploration between DHP and TD(0).
Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

2011
The Local Optimality of Reinforcement Learning by Value Gradients, and its Relationship to Policy Gradient Learning
CoRR, 2011

2008
Reinforcement Learning by Value Gradients
CoRR, 2008

1999
A Curvature Primal Sketch Neural Network Recognition System.
Proceedings of the International Conference on Artificial Neural Nets and Genetic Algorithms, 1999


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