By Dr Michael Bain

Book Chapters

Kemp J; Barker C; Good N; Bain M, 2024, 'Graphical Association Analysis for Identifying Variation in Provider Claims for Joint Replacement Surgery', in , pp. 805 - 809, http://dx.doi.org/10.3233/SHTI231076

Bain M, 2017, 'Structured Induction', in Encyclopedia of Machine Learning and Data Mining, Springer US, pp. 1201 - 1205, http://dx.doi.org/10.1007/978-1-4899-7687-1_796

Heap B; Krzywicki A; Wobcke W; Bain M; Compton P, 2014, 'Combining Career Progression and Profile Matching in a Job Recommender System', in Lecture Notes in Computer Science, Springer International Publishing, pp. 396 - 408, http://dx.doi.org/10.1007/978-3-319-13560-1_32

Ma DKG; Stolte C; Kaur S; Bain M; O Donoghue SI, 2014, 'Visual analytics of signalling pathways using time profiles', in Sun C; Bednarz T; Pham TD; Vallotton P; Wang D (ed.), Signal and Image Analysis for Biomedical and Life Sciences, pp. 3 - 22

Wearing MJ, 2011, 'Preface', in Wearing M (ed.), Social Identity, Nova Science Publishers, 2011, pp. vii - xvii, http://dx.doi.org/10.1109/ICDMW.2011.192

Bain M, 2011, 'Structured Induction', in Sammut C; Webb GI (ed.), Encyclopedia of Machine Learning, Springer US, pp. 930 - 933, http://dx.doi.org/10.1007/978-0-387-30164-8_796

Ben-Naim D; Velan GM; Marcus N; Bain M, 2010, 'Adaptive Tutorials for Virtual Microscopy: A Design Paradigm to Promote Pedagogical Ownership.', in Aleven V; Kay J; Mostow J (ed.), Intelligent Tutoring Systems 10th International Conference, ITS 2010, Pittsburgh, PA, USA, June 14-18, 2010, Proceedings, Springer Science & Business Media, pp. 266 - 268, http://dx.doi.org/10.1007/978-3-642-13437-1_40

Journal articles

Guan C; Suryanto H; Mahidadia A; Bain M; Compton P, 2023, 'Responsible Credit Risk Assessment with Machine Learning and Knowledge Acquisition', Human-Centric Intelligent Systems, 3, pp. 232 - 243, http://dx.doi.org/10.1007/s44230-023-00035-1

Bain M; McCay A, 2023, 'The neural democratisation of AI', AI and Society, http://dx.doi.org/10.1007/s00146-023-01706-0

Srinivasan A; Bain M; Baskar A, 2022, 'Learning explanations for biological feedback with delays using an event calculus', Machine Learning, 111, pp. 2435 - 2487, http://dx.doi.org/10.1007/s10994-021-06038-y

Bai Y; Bain M, 2022, 'Optimizing weighted lazy learning and Naive Bayes classification using differential evolution algorithm', Journal of Ambient Intelligence and Humanized Computing, 13, pp. 3005 - 3024, http://dx.doi.org/10.1007/s12652-021-03135-7

Suryanto H; Mahidadia A; Bain M; Guan C; Guan A, 2022, 'Credit Risk Modeling Using Transfer Learning and Domain Adaptation', Frontiers in Artificial Intelligence, 5, http://dx.doi.org/10.3389/frai.2022.868232

Page J; Mukhlish F; Bain M, 2022, 'Ensuring the Alignment of Genetic/Epigenetic Designed Swarms.', Mathematical Machines and Systems. 2022 #1, 1, pp. 3 - 11, http://dx.doi.org/10.34121/1028-9763-2022-1-3-11

Lock O; Bain M; Pettit C, 2021, 'Towards the collaborative development of machine learning techniques in planning support systems – a Sydney example', Environment and Planning B: Urban Analytics and City Science, 48, pp. 484 - 502, http://dx.doi.org/10.1177/2399808320939974

Mukhlish F; Page J; Bain M, 2020, 'Reward-based epigenetic learning algorithm for a decentralised multi-agent system', International Journal of Intelligent Unmanned Systems, 8, pp. 201 - 224, http://dx.doi.org/10.1108/IJIUS-12-2018-0036

Srinivasan A; Vig L; Bain M, 2019, 'Logical explanations for deep relational machines using relevance information', Journal of Machine Learning Research, 20

Mukhlish F; Page J; Bain M, 2019, 'TEKNOLOGI ROBOT KAWANAN (SWARM ROBOTICS) UNTUK MISI PENCARIAN DAN PERTOLONGAN DI INDONESIA', Seminar Nasional Kontrol Instrumentasi dan Otomasi (SNIKO) 2015, http://dx.doi.org/10.5614/sniko.2018.47

Mukhlish F; Page J; Bain M, 2018, 'Evolutionary-learning framework: improving automatic swarm robotics design', International Journal of Intelligent Unmanned Systems, 6, pp. 197 - 215, http://dx.doi.org/10.1108/IJIUS-06-2018-0016

Bain M; Srinivasan A, 2018, 'Identification of biological transition systems using meta-interpreted logic programs', Machine Learning, 107, pp. 1171 - 1206, http://dx.doi.org/10.1007/s10994-018-5709-1

Heap B; Bain M; Wobcke W; Krzywicki A; Schmeidl S, 2017, 'Word Vector Enrichment of Low Frequency Words in the Bag-of-Words Model for Short Text Multi-class Classification Problems.', CoRR, abs/1709.05778

Krzywicki A; Wobcke W; Bain M; Calvo Martinez J; Compton P, 2016, 'Data mining for building knowledge bases: Techniques, architectures and applications', Knowledge Engineering Review, 31, pp. 97 - 123, http://dx.doi.org/10.1017/S0269888916000047

wobcke W; Krzywicki A; Kim Y; Cai X; Bain M; Compton P; Mahidadia A, 2015, 'A Deployed People-to-People Recommender System in Online Dating', AI Magazine, 36, http://dx.doi.org/10.1609/aimag.v36i3.2599

Masson B; Bain M; Page J, 2015, 'Large Aircraft Engine-Out Takeoff Path Optimization', Journal of Aerospace Operations

Krzywicki A; Wobcke W; Kim YS; Cai X; Bain M; Mahidadia A; Compton P, 2015, 'Collaborative Filtering for people-to-people recommendation in online dating: Data analysis and user trial', International Journal of Human-Computer Studies, 76, pp. 50 - 66, http://dx.doi.org/10.1016/j.ijhcs.2014.12.003

Akand E; Bain M; Temple M, 2010, 'Learning with gene ontology annotation using feature selection and construction', Applied Artificial Intelligence, 24, pp. 5 - 38, http://dx.doi.org/10.1080/08839510903448627

Kadupitige ; Leung KC; Sellmeier J; Sivieng J; Catchpoole DR; Bain ME; Gaeta BA, 2009, 'MINER: exploratory analysis of gene interaction networks by machine learning from expression data', BMC Genomics, 10 Suppl 3, pp. S17, http://dx.doi.org/10.1186/1471-2164-10-S3-S17

Gaeta BA; Malming H; Jackson KJ; Bain ME; Wilson PD; Collins AM, 2007, 'iHMMune-align: hidden Markov model-based alignment and identification of germline genes in rearranged immunoglobulin gene sequences', Bioinformatics, 23, pp. 1580 - 1587

Lee CE; Gaeta BA; Malming H; Bain ME; Sewell WA; Collins AM, 2006, 'Reconsidering the human immunoglobulin heavy-chain locus: 1. An evaluation of the expressed human IGHD gene repertoire', Immunogenetics, 57, pp. 917 - 925

Srinivasan A; King R; Bain ME, 2003, 'An Empirical Study of the use of Relevance Information in Inductive Logic Programming', Journal of Machine Learning Research, 4, pp. 369 - 383

Bain ME; Furukawa K; Ueno K, 2001, 'Motor Skill as Dynamic Constraint Satisfaction', Electronic Transactions on Artificial Intelligence, pp. 79 - 92

Conference Papers

Kemp J; Barker C; Good N; Bain M, 2023, 'Context Discovery and Cost Prediction for Detection of Anomalous Medical Claims, with Ontology Structure Providing Domain Knowledge', in Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies, SCITEPRESS - Science and Technology Publications, presented at 16th International Conference on Health Informatics, 16 February 2023 - 18 February 2023, http://dx.doi.org/10.5220/0011611000003414

Kemp J; Barker C; Good N; Bain M, 2023, 'Developing an anomaly detection framework for Medicare claims', in ACM International Conference Proceeding Series, ACM, pp. 234 - 237, presented at ACSW 2023: 2023 Australasian Computer Science Week, http://dx.doi.org/10.1145/3579375.3579410

Krzywicki A; Mahidadia A; Bain M, 2022, 'Discovering Periodicity in Locally Repeating Patterns', in Proceedings - 2022 IEEE 9th International Conference on Data Science and Advanced Analytics, DSAA 2022, http://dx.doi.org/10.1109/DSAA54385.2022.10032435

Kemp J; Barker C; Good N; Bain M, 2022, 'Sequential pattern detection for identifying courses of treatment and anomalous claim behaviour in medical insurance', in Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022, pp. 3039 - 3046, http://dx.doi.org/10.1109/BIBM55620.2022.9995541

Page J; Mukhlish F; Bain M, 2021, 'Towards Motion Capture Using a Swarms of Drones', in Tan Tien N (ed.), Proceedings of 17th International Conference on Intelligent Unmanned Systems, International Society of Intelligent Unmanned Systems, Ho Ci Minh City, Viet Nam, presented at 17th International Conference on Intelligent Unmanned System, Ho Ci Minh City, Viet Nam, 25 August 2021 - 27 August 2021

Bai Y; Bain M, 2020, 'Using a Semi-Evolutionary Algorithm to Optimize Deep Network Hyper-Parameters with an Application to Donor Detection', in 2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020, pp. 2655 - 2662, http://dx.doi.org/10.1109/SSCI47803.2020.9308351

Mukhlish F; Page J; Bain M, 2020, 'From Reward to Histone: Combining Temporal-Difference Learning and Epigenetic Inheritance for Swarm’s Coevolving Decision Making', in 2020 Joint IEEE 10th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob), Institute of Electrical and Electronics Engineers (IEEE), Valparaíso, Chile, pp. 1 - 6, presented at 2020 Joint IEEE 10th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob), Valparaíso, Chile, 26 October 2020 - 30 October 2020

Page J; Bain M; Mukhlish F, 2019, 'Intern Training of Artificial Intelligence Systems', in Juliastuti E (ed.), 2019 International Conference on Instrimentation, Control and Automation, IEEE, Bandung, Indoneasia, pp. 117 - 120, presented at 6th ICA 2019, Bandung, Indoneasia, 31 July 2019 - 02 August 2019

Mukhlish F; Page J; Bain M, 2019, 'Reward-based Evolutionary Swarm UAVs on Search and Rescue Mission', in AEROSPACE - 18th Australian International Aerospace Congress, Engineers Australia, Royal Aeronautical Society, Melbourne, Australia, pp. 348 - 353, presented at AIAC 2018: 18th Australian International Aerospace Congress, Melbourne, Australia, 24 February 2019 - 26 February 2019

Krzywicki A; Heap B; Bain M; Wobcke W; Schmeidl S, 2018, 'Using word embeddings with linear models for short text classification', in Mitrovic T; Xue B; Li X (eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer, Cham, Victoria University of Wellington, New Zealand, pp. 819 - 827, presented at AI 2018 - The 31st Australasian Joint Conference on Artificial Intelligence, Victoria University of Wellington, New Zealand, 11 December 2018 - 14 December 2018, http://dx.doi.org/10.1007/978-3-030-03991-2_74

Bain M, 2018, 'An investigation into the role of domain-knowledge on the use of embeddings', in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Ferrara, Italy, pp. 169 - 183, presented at International Conference on Inductive Logic Programming, Ferrara, Italy, 02 September 2018 - 04 September 2018, http://dx.doi.org/10.1007/978-3-319-78090-0_12

Katz G; Heap B; Wobcke W; Bain M; Kannangara S, 2018, 'Analysing TV audience engagement via twitter: Incremental segment-level opinion mining of second screen tweets', in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Nanjing, China, pp. 300 - 308, presented at Pacific Rim International Conference on Artificial Intelligence, Nanjing, China, 28 August 2018 - 31 August 2018, http://dx.doi.org/10.1007/978-3-319-97310-4_34

Krzywicki A; Wobcke W; Bain M; Schmeidl S; Heap B, 2018, 'A knowledge acquisition method for event extraction and coding based on deep patterns', in Yoshida K; Lee M (ed.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer Nature, Nanjing, China, pp. 16 - 31, presented at Pacific Rim Knowledge Acquisition Workshop, Nanjing, China, 27 August 2018 - 28 August 2018, http://dx.doi.org/10.1007/978-3-319-97289-3_2

Heap B; Krzywicki A; Schmeidl S; Wobcke W; Bain M, 2017, 'A joint human/machine process for coding events and conflict drivers', in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Singapore, pp. 639 - 654, presented at 13th International Conference, ADMA 2017, Singapore, 05 November 2017 - 06 November 2017, http://dx.doi.org/10.1007/978-3-319-69179-4_45

Alanazi AS; Bain ME, 2016, 'A Scalable People-to-People Hybrid Reciprocal Recommender Using Hidden Markov Models', in 2nd International Workshop on Machine Learning Methods for Recommender Systems, Miami, Florida, USA, presented at International Workshop on Machine Learning Methods for Recommender Systems, Miami, Florida, USA, 05 May 2016 - 07 May 2016, http://dx.doi.org/10.26190/unsworks/27046

Srinivasan A; Bain M; Vatsa D; Agarwal S, 2016, 'Identification of transition models of biological systems in the presence of transition noise', in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 200 - 214, http://dx.doi.org/10.1007/978-3-319-40566-7_14

Masson B; Page J, 2015, 'Runway and Terrain Classification and effect on Engine Out Takeoff Paths', in Runway and Terrain Classification and effect on Engine Out Takeoff Paths, APISAT 2015, Cairns, presented at APISAT 2015, Cairns, 25 November 2015 - 27 November 2015

Masson B; Bain M; Page J, 2015, 'Is Engine Failure on the Runway at Takeoff the most limiting case?', in AIAC16, Melbourne, Vic, presented at Australian International Aerospace Conference, Melbourne, Vic, 23 February 2015 - 25 February 2015, http://search.informit.org/documentSummary;dn=254530517802743;res=IELENG;subject=Law

Masson B; Bain M; Page J, 2015, 'Diverging Engine Failure Paths on Standard Instrument Departures', Kissimmee, Florida, USA, presented at AIAA SciTech Conference, Kissimmee, Florida, USA, 05 January 2015 - 09 January 2015

Masson B; Bain M; Page J, 2015, 'Diverging engine failure paths on standard instrument departures', in AIAA Guidance, Navigation, and Control Conference, 2013

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