Michael Fairbank

David Barragan-Alcantar

Shuhui Li

Neural Networks, 2025

2023

A Minimal "Functionally Sentient" Organism Trained With Backpropagation Through Time.

[BibT_eX]

[DOI]

Mahrad Pisheh Var

Adapt. Behav., December, 2023

Demand management in time-slotted last-mile delivery via dynamic routing with forecast orders.

[BibT_eX]

[DOI]

Eur. J. Oper. Res., September, 2023

2022

Deep Learning in Target Space.

[BibT_eX]

[DOI]

Luca Citi

J. Mach. Learn. Res., 2022

An Iterative Optimization and Learning-Based IoT System for Energy Management of Connected Buildings.

[BibT_eX]

[DOI]

IEEE Internet Things J., 2022

Grokking-like effects in counterfactual inference.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

IEEE Trans. Circuits Syst. I Regul. Pap., 2021

A Comparison of Deep-Learning Methods for Analysing and Predicting Business Processes.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

IEEE Trans. Cybern., 2020

Deep Learning in Target Space.

[BibT_eX]

[DOI]

CoRR, 2020

Baseline win rates for neural-network based trading algorithms.

[BibT_eX]

[DOI]

Andreas Krause

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Practical Game Design Tool: State Explorer.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Games, 2020

2019

Mek: Mechanics Prototyping Tool for 2D Tile-Based Turn-Based Deterministic Games.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Games, 2019

Extracting Learning Curves From Puzzle Games.

[BibT_eX]

[DOI]

Proceedings of the 11th Computer Science and Electronic Engineering Conference, 2019

2017

Convolutional-Match Networks for Question Answering.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Diversity maintenance using a population of repelling random-mutation hill climbers.

[BibT_eX]

[DOI]

Rokas Volkovas

Diego Perez Liebana

Proceedings of the 2017 9th Computer Science and Electronic Engineering Conference, 2017

Convolutional neural networks applied to high-frequency market microstructure forecasting.

[BibT_eX]

[DOI]

Jonathan Doering

Sheri Markose

Proceedings of the 2017 9th Computer Science and Electronic Engineering Conference, 2017

2016

Optimal resampling for the noisy OneMax problem.

[BibT_eX]

[DOI]

CoRR, 2016

Match memory recurrent networks.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., 2015

Back to optimality: a formal framework to express the dynamics of learning optimal behavior.

[BibT_eX]

[DOI]

Esther Mondragón

Adapt. Behav., 2015

Control of Three-Phase Grid-Connected Microgrids using Artificial Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 7th International Joint Conference on Computational Intelligence (IJCCI 2015), 2015

2014

Value-gradient learning.

[BibT_eX]

[DOI]

PhD thesis, 2014

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

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., 2014

Clipping in Neurocontrol by Adaptive Dynamic Programming.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Neural Networks, 2014

2013

An Equivalence Between Adaptive Dynamic Programming With a Critic and Backpropagation Through Time.

[BibT_eX]

[DOI]

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

[BibT_eX]

[DOI]

CoRR, 2013

Emergent and Adaptive Systems of Systems.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Systems, 2013

Nested-loop neural network vector control of permanent magnet synchronous motors.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., 2012

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

[BibT_eX]

[DOI]

Neural Comput., 2012

Vector control of a grid-connected rectifier/inverter using an artificial neural network.

[BibT_eX]

[DOI]

Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

The divergence of reinforcement learning algorithms with value-iteration and function approximation.

[BibT_eX]

[DOI]

Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

Value-gradient learning.

[BibT_eX]

[DOI]

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).

[BibT_eX]

[DOI]

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

[BibT_eX]

[DOI]

CoRR, 2011

2008

Reinforcement Learning by Value Gradients

[BibT_eX]

[DOI]

CoRR, 2008

1999

A Curvature Primal Sketch Neural Network Recognition System.

[BibT_eX]

[DOI]