Learning and Searching Pseudo-Boolean Surrogate Functions from Small Samples

Authors: Swingler, Kevin

Contributors: Computing Science, orcid:0000-0002-4517-9433

Source: Evolutionary Computation. 28:317-338

Subject Terms: Pseudo-Boolean Functions, Walsh Decomposition, 0102 computer and information sciences, 02 engineering and technology, Models, Theoretical, 16. Peace & justice, Computational Intelligence and Machine Learning, Mixed Order Hyper Networks, 01 natural sciences, Statistical Machine Learning, 0202 electrical engineering, electronic engineering, information engineering, Learning, Optimisation, Computer Simulation, Fitness Function Modelling, Linkage Learning, Algorithms, Estimation of Distribution Algorithms

File Description: application/pdf

Access URL: http://dspace.stir.ac.uk/bitstream/1893/29641/1/ECJ-2018-036R2-single.pdf
https://pubmed.ncbi.nlm.nih.gov/31038355
https://www.ncbi.nlm.nih.gov/pubmed/31038355
https://www.mitpressjournals.org/doi/abs/10.1162/evco_a_00257
https://dspace.stir.ac.uk/handle/1893/29641
https://direct.mit.edu/evco/article/28/2/317/94981/Learning-and-Searching-Pseudo-Boolean-Surrogate
https://dblp.uni-trier.de/db/journals/ec/ec28.html#Swingler20
https://pubmed.ncbi.nlm.nih.gov/31038355/

Exploring the Accuracy - Energy Trade-off in Machine Learning

Authors: Brownlee, Alexander, Adair, Jason, Haraldsson, Saemundur, Jabbo, John

Contributors: Computing Science, orcid:0000-0003-2892-5059, orcid:0000-0003-0395-5884

Subject Terms: Computational Intelligence and Machine Learning, Optimisation, Search Based Software Engineering

File Description: application/pdf

Relation: Brownlee A, Adair J, Haraldsson S & Jabbo J (2021) Exploring the Accuracy - Energy Trade-off in Machine Learning. In: 2021 IEEE/ACM International Workshop on Genetic Improvement (GI). Genetic Improvement Workshop at 43rd International Conference on Software Engineering, Madrid, Spain, 30.05.2021-30.05.2021. Piscataway, NJ: IEEE. https://doi.org/10.1109/GI52543.2021.00011; http://hdl.handle.net/11667/173; http://hdl.handle.net/1893/32312; 1707726; http://dspace.stir.ac.uk/bitstream/1893/32312/1/GI2021_Machine_Learning_Energy.pdf

Availability: http://hdl.handle.net/1893/32312
https://doi.org/10.1109/GI52543.2021.00011
http://dspace.stir.ac.uk/bitstream/1893/32312/1/GI2021_Machine_Learning_Energy.pdf

Structure Discovery in Mixed Order Hyper Networks

Authors: Swingler, Kevin

Contributors: Computing Science, orcid:0000-0002-4517-9433

Subject Terms: High order neural networks, Structure discovery, Linkage learning, Computational Intelligence and Machine Learning, Optimisation

File Description: application/pdf

Relation: Swingler K (2016) Structure Discovery in Mixed Order Hyper Networks. Big Data Analytics, 1 (1), Art. No.: 8. https://doi.org/10.1186/s41044-016-0009-x; http://hdl.handle.net/1893/23415; 564023; http://dspace.stir.ac.uk/bitstream/1893/23415/1/Swingler_BigDataAnalytics_2016.pdf

Availability: http://hdl.handle.net/1893/23415
https://doi.org/10.1186/s41044-016-0009-x
http://dspace.stir.ac.uk/bitstream/1893/23415/1/Swingler_BigDataAnalytics_2016.pdf

A Semi-supervised Corpus Annotation for Saudi Sentiment Analysis Using Twitter

Authors: Alqarafi, Abdulrahman, Adeel, Ahsan, Hawalah, Ahmed, Swingler, Kevin, Hussain, Amir

Contributors: Hussain, A, Zhao, H, Ren, J, Zheng, J, Liu, C-L, Luo, B, Zhao, X, Computing Science, Taibah University, orcid:0000-0002-4517-9433, orcid:0000-0002-8080-082X

Subject Terms: Sentiment analysis, Saudi dialect, Word embedding, Computational Intelligence and Machine Learning

File Description: application/pdf

Relation: Alqarafi A, Adeel A, Hawalah A, Swingler K & Hussain A (2018) A Semi-supervised Corpus Annotation for Saudi Sentiment Analysis Using Twitter. In: Hussain A, Zhao H, Ren J, Zheng J, Liu C, Luo B & Zhao X (eds.) Advances in Brain Inspired Cognitive Systems. Lecture Notes in Computer Science, 10989. BICS 2018: 9th International Conference on Brain Inspired Cognitive Systems, Xi'an, China, 07.07.2018-08.07.2018. Cham, Switzerland: Springer International Publishing, pp. 589-596. https://doi.org/10.1007/978-3-030-00563-4_57; Lecture Notes in Computer Science, 10989; http://hdl.handle.net/1893/29408; 1046609

Availability: http://hdl.handle.net/1893/29408
https://doi.org/10.1007/978-3-030-00563-4_57
http://dspace.stir.ac.uk/bitstream/1893/29408/1/Camera%20Ready%20Paper-Bics%20Abdulrahman%20Alqarafi.pdf

A novel brain-inspired compression-based optimised multimodal fusion for emotion recognition

Authors: Gogate, Mandar, Adeel, Ahsan, Hussain, Amir

Contributors: Engineering and Physical Sciences Research Council, Computing Science, orcid:0000-0003-1712-9014, orcid:0000-0002-8080-082X

Subject Terms: Acoustics, Convolution, Emotion recognition, Feature extraction, Kernel, Videos, Visualization, Compression, Deep Convolutional Neural Network, Multimodal Fusion, Optimisation, Artificial Intelligence, Computational Intelligence and Machine Learning, Computer Science, Speech and Natural Language Processing

File Description: application/pdf

Relation: Gogate M, Adeel A & Hussain A (2017) A novel brain-inspired compression-based optimised multimodal fusion for emotion recognition. In: 2017 IEEE Symposium Series on Computational Intelligence (SSCI). 2017 IEEE Symposium Series on Computational Intelligence (SSCI). Piscataway, NJ, USA: IEEE. https://doi.org/10.1109/SSCI.2017.8285377; Towards visually-driven speech enhancement for cognitively-inspired multi-modal hearing-aid devices; EP/M026981/1; http://hdl.handle.net/1893/26943; 497086; http://dspace.stir.ac.uk/bitstream/1893/26943/1/08285377.pdf

Availability: http://hdl.handle.net/1893/26943
https://doi.org/10.1109/SSCI.2017.8285377
http://dspace.stir.ac.uk/bitstream/1893/26943/1/08285377.pdf