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Items where Author is "Fairbank, Michael"

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Number of items: 18.

Article

Abdollahi, Mohammad and Yang, Xinan and Fairbank, Michael and Nasri, moncef (2023) Demand Management in Time-slotted Last-mile Delivery via Dynamic Routing with Forecast Orders. European Journal of Operational Research, 309 (2). pp. 704-718. DOI https://doi.org/10.1016/j.ejor.2023.01.023

Pisheh Var, Mahrad and Fairbank, Michael and Samothrakis, Spyros (2023) A Minimal “Functionally Sentient” Organism Trained with Backpropagation Through Time. Adaptive Behavior, 31 (6). pp. 531-544. DOI https://doi.org/10.1177/10597123231166416

Gao, Yixiang and Li, Shuhui and Xiao, Yang and Dong, Weizhen and Fairbank, Michael and Lu, Bing (2022) An Iterative Optimization and Learning-based IoT System for Energy Management of Connected Buildings. IEEE Internet of Things Journal, 9 (21). p. 1. DOI https://doi.org/10.1109/jiot.2022.3176306

Fairbank, Michael and Samothrakis, Spyridon and Citi, Luca (2022) Deep Learning in Target Space. Journal of Machine Learning Research, 23. pp. 1-46.

Dong, Weizhen and Li, Shuhui and Fu, Xingang and Li, Zhongwen and Fairbank, Michael and Gao, Yixiang (2021) Control of a Buck DC/DC Converter Using Approximate Dynamic Programming and Artificial Neural Networks. IEEE Transactions on Circuits and Systems Part 1: Regular Papers, 68 (4). pp. 1760-1768. DOI https://doi.org/10.1109/tcsi.2021.3053468

Li, Shuhui and Won, Hoyun and Fu, Xingang and Fairbank, Michael and Wunsch, Donald C and Alonso, Eduardo (2020) Neural-Network Vector Controller for Permanent-Magnet Synchronous Motor Drives: Simulated and Hardware-Validated Results. IEEE Transactions on Cybernetics, 50 (7). pp. 3218-3230. DOI https://doi.org/10.1109/tcyb.2019.2897653

Fu, Xingang and Li, Shuhui and Fairbank, Michael and Wunsch, Donald C and Alonso, Eduardo (2015) Training Recurrent Neural Networks With the Levenberg-Marquardt Algorithm for Optimal Control of a Grid-Connected Converter. IEEE Transactions on Neural Networks and Learning Systems, 26 (9). pp. 1900-1912. DOI https://doi.org/10.1109/TNNLS.2014.2361267

Fairbank, Michael and Prokhorov, Danil and Alonso, Eduardo (2014) Clipping in Neurocontrol by Adaptive Dynamic Programming. IEEE Transactions on Neural Networks and Learning Systems, 25 (10). pp. 1909-1920. DOI https://doi.org/10.1109/TNNLS.2014.2297991

Fairbank, Michael and Li, Shuhui and Fu, Xingang and Alonso, Eduardo and Wunsch, Donald (2014) An adaptive recurrent neural-network controller using a stabilization matrix and predictive inputs to solve a tracking problem under disturbances. Neural Networks, 49. pp. 74-86. DOI https://doi.org/10.1016/j.neunet.2013.09.010

Fairbank, Michael and Alonso, Eduardo and Prokhorov, Danil (2012) Simple and fast calculation of the second-order gradients for globalized dual heuristic dynamic programming in neural networks. IEEE Transactions on Neural Networks and Learning Systems, 23 (10). pp. 1671-1676. DOI https://doi.org/10.1109/tnnls.2012.2205268

Fairbank, Michael and Alonso, Eduardo (2012) Efficient calculation of the Gauss-Newton approximation of the Hessian matrix in neural networks. Neural Computation, 24 (3). pp. 607-610. DOI https://doi.org/10.1162/neco_a_00248

Monograph

Fairbank, Michael and Samothrakis, Spyridon and Citi, Luca (2021) Deep Learning in Target Space. Working Paper. arXiv. (Unpublished)

Conference or Workshop Item

Pisheh Var, Mahrad and Fairbank, Michael and Samothrakis, Spyridon (2023) Finding Eulerian tours in mazes using amemory-augmented fixed policy function. In: Computing Conference, 2023-06-22 - 2023-06-23, London.

Samothrakis, Spyridon and Matran-Fernandez, Ana and Abdullahi, Umar and Fairbank, Michael and Fasli, Maria (2022) Grokking-like effects in counterfactual inference. In: 2022 International Joint Conference on Neural Networks (IJCNN), 2022-07-18 - 2022-07-23, Padua, Italy.

Venugopal, Ishwar and Tollich, Jessica and Fairbank, Michael and Scherp, Ansgar (2021) A Comparison of Deep-Learning Methods forAnalysing and Predicting Business Processes. In: International Joint Conference on Neural Networks, IJCNN, 2021, 2021-07-18 - 2021-07-22, Shenzhen. (In Press)

Volkovas, Rokas and Fairbank, Michael and Woodward, John R and Lucas, Simon (2020) Practical Game Design Tool: State Explorer. In: IEEE Conference on Games (CoG) 2020, 2020-08-24 - 2020-08-27, Osaka, Japan.

Krause, Andreas and Fairbank, Michael (2020) Baseline win rates for neural-network based trading algorithms. In: 2020 International Joint Conference on Neural Networks (IJCNN 2020), 2020-07-19 - 2020-07-24, Glasgow. (In Press)

Fairbank, Michael and Alonso, Eduardo (2012) Value-gradient learning. In: The 2012 International Joint Conference on Neural Networks (IJCNN), 2012-06-10 - 2012-06-15, Brisbane, QLD, Australia.

This list was generated on Thu May 30 10:55:55 2024 BST.