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2020 – today
- 2023
[j14]Mahrad Pisheh Var
, Michael Fairbank, Spyridon Samothrakis:
A Minimal "Functionally Sentient" Organism Trained With Backpropagation Through Time. Adapt. Behav. 31(6): 531-544 (2023)- [j13]Mohammad Abdollahi, Xinan Yang, Moncef Ilies Nasri, Michael Fairbank:
Demand management in time-slotted last-mile delivery via dynamic routing with forecast orders. Eur. J. Oper. Res. 309(2): 704-718 (2023) - 2022
- [j12]Yixiang Gao, Shuhui Li, Yang Xiao, Weizhen Dong, Michael Fairbank, Bing Lu:
An Iterative Optimization and Learning-Based IoT System for Energy Management of Connected Buildings. IEEE Internet Things J. 9(21): 21246-21259 (2022) - [j11]Michael Fairbank, Spyridon Samothrakis, Luca Citi:
Deep Learning in Target Space. J. Mach. Learn. Res. 23: 8:1-8:46 (2022) - [c18]Spyridon Samothrakis, Ana Matran-Fernandez, Umar I. Abdullahi, Michael Fairbank, Maria Fasli:
Grokking-like effects in counterfactual inference. IJCNN 2022: 1-8 - 2021
- [j10]Weizhen Dong, Shuhui Li, Xingang Fu, Zhongwen Li, Michael Fairbank, Yixiang Gao:
Control of a Buck DC/DC Converter Using Approximate Dynamic Programming and Artificial Neural Networks. IEEE Trans. Circuits Syst. I Regul. Pap. 68(4): 1760-1768 (2021) - [c17]Ishwar Venugopal, Jessica Töllich, Michael Fairbank, Ansgar Scherp:
A Comparison of Deep-Learning Methods for Analysing and Predicting Business Processes. IJCNN 2021: 1-8 - 2020
- [j9]Shuhui Li, Hoyun Won, Xingang Fu, Michael Fairbank, Donald C. Wunsch, Eduardo Alonso:
Neural-Network Vector Controller for Permanent-Magnet Synchronous Motor Drives: Simulated and Hardware-Validated Results. IEEE Trans. Cybern. 50(7): 3218-3230 (2020) - [c16]Rokas Volkovas, Michael Fairbank, John R. Woodward, Simon Lucas:
Practical Game Design Tool: State Explorer. CoG 2020: 439-446 - [c15]Andreas Krause, Michael Fairbank:
Baseline win rates for neural-network based trading algorithms. IJCNN 2020: 1-6 - [i7]Michael Fairbank, Spyridon Samothrakis:
Deep Learning in Target Space. CoRR abs/2006.01578 (2020)
2010 – 2019
- 2019
- [c14]Rokas Volkovas, Michael Fairbank, John R. Woodward, Simon M. Lucas:
Extracting Learning Curves From Puzzle Games. CEEC 2019: 150-155 - [c13]Rokas Volkovas, Michael Fairbank, John R. Woodward, Simon M. Lucas:
Mek: Mechanics Prototyping Tool for 2D Tile-Based Turn-Based Deterministic Games. CoG 2019: 1-8 - [i6]Rokas Volkovas, Michael Fairbank, John R. Woodward, Simon M. Lucas:
Mek: Mechanics Prototyping Tool for 2D Tile-Based Turn-Based Deterministic Games. CoRR abs/1904.03540 (2019) - 2017
- [c12]Jonathan Doering, Michael Fairbank, Sheri Markose:
Convolutional neural networks applied to high-frequency market microstructure forecasting. CEEC 2017: 31-36 - [c11]Rokas Volkovas, Michael Fairbank, Diego Perez Liebana:
Diversity maintenance using a population of repelling random-mutation hill climbers. CEEC 2017: 37-42 - [c10]Spyridon Samothrakis, Tom Vodopivec, Michael Fairbank, Maria Fasli:
Convolutional-Match Networks for Question Answering. IJCAI 2017: 2686-2692 - 2016
- [c9]Spyridon Samothrakis, Tom Vodopivec, Maria Fasli, Michael Fairbank:
Match memory recurrent networks. IJCNN 2016: 1339-1346 - [i5]Jialin Liu, Michael Fairbank, Diego Perez Liebana, Simon M. Lucas:
Optimal resampling for the noisy OneMax problem. CoRR abs/1607.06641 (2016) - 2015
- [j8]Eduardo Alonso, Michael Fairbank, Esther Mondragón:
Back to optimality: a formal framework to express the dynamics of learning optimal behavior. Adapt. Behav. 23(4): 206-215 (2015) - [j7]Xingang Fu, Shuhui Li, Michael Fairbank, Donald C. Wunsch, Eduardo Alonso:
Training Recurrent Neural Networks With the Levenberg-Marquardt Algorithm for Optimal Control of a Grid-Connected Converter. IEEE Trans. Neural Networks Learn. Syst. 26(9): 1900-1912 (2015) - [c8]Shuhui Li, Xingang Fu, Ishan Jaithwa, Eduardo Alonso, Michael Fairbank, Donald C. Wunsch II:
Control of Three-Phase Grid-Connected Microgrids using Artificial Neural Networks. IJCCI (NCTA) 2015: 58-69 - 2014
- [b1]Michael Fairbank:
Value-gradient learning. City University London, UK, 2014 - [j6]Michael Fairbank, Shuhui Li, Xingang Fu, Eduardo Alonso, Donald C. Wunsch II:
An adaptive recurrent neural-network controller using a stabilization matrix and predictive inputs to solve a tracking problem under disturbances. Neural Networks 49: 74-86 (2014) - [j5]Shuhui Li, Michael Fairbank, Cameron Johnson, Donald C. Wunsch, Eduardo Alonso, Julio L. Proao:
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. 25(4): 738-750 (2014) - [j4]Michael Fairbank, Danil V. Prokhorov, Eduardo Alonso:
Clipping in Neurocontrol by Adaptive Dynamic Programming. IEEE Trans. Neural Networks Learn. Syst. 25(10): 1909-1920 (2014) - 2013
- [j3]Michael Fairbank, Eduardo Alonso, Danil V. Prokhorov:
An Equivalence Between Adaptive Dynamic Programming With a Critic and Backpropagation Through Time. IEEE Trans. Neural Networks Learn. Syst. 24(12): 2088-2100 (2013) - [c7]Shuhui Li, Michael Fairbank, Xingang Fu, Donald C. Wunsch, Eduardo Alonso:
Nested-loop neural network vector control of permanent magnet synchronous motors. IJCNN 2013: 1-8 - [c6]Eduardo Alonso, Michael Fairbank:
Emergent and Adaptive Systems of Systems. SMC 2013: 1721-1725 - [i4]Michael Fairbank:
The Importance of Clipping in Neurocontrol by Direct Gradient Descent on the Cost-to-Go Function and in Adaptive Dynamic Programming. CoRR abs/1302.5565 (2013) - 2012
- [j2]Michael Fairbank, Eduardo Alonso:
Efficient Calculation of the Gauss-Newton Approximation of the Hessian Matrix in Neural Networks. Neural Comput. 24(3): 607-610 (2012) - [j1]Michael Fairbank, Eduardo Alonso, Danil V. Prokhorov:
Simple and Fast Calculation of the Second-Order Gradients for Globalized Dual Heuristic Dynamic Programming in Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 23(10): 1671-1676 (2012) - [c5]Michael Fairbank, Eduardo Alonso:
A comparison of learning speed and ability to cope without exploration between DHP and TD(0). IJCNN 2012: 1-8 - [c4]Michael Fairbank, Eduardo Alonso:
Value-gradient learning. IJCNN 2012: 1-8 - [c3]Michael Fairbank, Eduardo Alonso:
The divergence of reinforcement learning algorithms with value-iteration and function approximation. IJCNN 2012: 1-8 - [c2]Shuhui Li, Donald C. Wunsch, Michael Fairbank, Eduardo Alonso:
Vector control of a grid-connected rectifier/inverter using an artificial neural network. IJCNN 2012: 1-7 - 2011
- [i3]Michael Fairbank, Eduardo Alonso:
The Local Optimality of Reinforcement Learning by Value Gradients, and its Relationship to Policy Gradient Learning. CoRR abs/1101.0428 (2011) - [i2]Michael Fairbank, Eduardo Alonso:
The Divergence of Reinforcement Learning Algorithms with Value-Iteration and Function Approximation. CoRR abs/1107.4606 (2011)
2000 – 2009
- 2008
- [i1]Michael Fairbank:
Reinforcement Learning by Value Gradients. CoRR abs/0803.3539 (2008)
1990 – 1999
- 1999
- [c1]Michael Fairbank, Andrew Tuson:
A Curvature Primal Sketch Neural Network Recognition System. ICANNGA 1999: 46-51
Coauthor Index
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