An Experimental Comparison of Human and Machine Learning Formalisms. - Stephen H. Muggleton; Michael Bain 001; Jean Hayes Michie; Donald Michie (ML, 1989)

Machines That Learn and Machines That Teach. - Donald Michie; Michael Bain 001 (SCAI, 1989)

Experiments in Non-Monotonic Learning. - Michael Bain 001 (ML, 1991)

Compression, Significance, and Accuracy. - Stephen H. Muggleton; Ashwin Srinivasan 001; Michael Bain 001 (ML, 1992)

Learning optimal chess strategies. - Michael Bain 001; Stephen H. Muggleton (Machine Intelligence 13, 1992)

The Justification of Logical Theories based on Data Compression. - Ashwin Srinivasan 001; Stephen H. Muggleton; Michael Bain 001 (Machine Intelligence 13, 1992)

Inductive Logic Programming With Large-Scale Unstructured Data. - Michael Bain 001; Ashwin Srinivasan 001 (Machine Intelligence 14, 1993)

Chess (King-Rook vs. King). - Michael Bain 001; Arthur Hoff (UCI Machine Learning Repository, 1994)

A Framework for Behavioural Cloning. - Michael Bain 001; Claude Sammut (Machine Intelligence 15, 1995)

Analogical Prediction. - Stephen H. Muggleton; Michael Bain 001 (ILP, 1999)

Motor Skill as Dynamic Constraint Satisfaction. - Ken Ueno; Koichi Furukawa; Michael Bain 001 (Electron. Trans. Artif. Intell., 2000)

Structured Features from Concept Lattices for Unsupervised Learning and Classification. - Michael Bain 001 (Australian Joint Conference on Artificial Intelligence, 2002)

Inductive Construction of Ontologies from Formal Concept Analysis. - Michael Bain 001 (Australian Conference on Artificial Intelligence, 2003)

An Empirical Study of the Use of Relevance Information in Inductive Logic Programming. - Ashwin Srinivasan 001; Ross D. King; Michael Bain 001 (J. Mach. Learn. Res., 2003)

Predicate Invention and the Revision of First-Order Concept Lattices. - Michael Bain 001 (ICFCA, 2004)

Virtual Apparatus Framework Approach to Constructing Adaptive Tutorials. - Dror Ben-Naim; Nadine Marcus; Michael Bain 001 (CSREA EEE, 2007)

iHMMune-align: hidden Markov model-based alignment and identification of germline genes in rearranged immunoglobulin gene sequences. - Bruno A. Gaëta; Harald R. Malming; Katherine J. L. Jackson; Michael E. Bain; Patrick Wilson; Andrew M. Collins (Bioinform., 2007)

Mining Minimal Constrained Flow Cycles from Complex Transaction Data. - Meng Xu; Michael Bain 001 (AusDM, 2009)

A User-Driven and Data-Driven Approach for Supporting Teachers in Reflection and Adaptation of Adaptive Tutorials. - Dror Ben-Naim; Michael Bain 001; Nadine Marcus (EDM, 2009)

Collaborative Filtering for People to People Recommendation in Social Networks. - Xiongcai Cai; Michael Bain 001; Alfred Krzywicki; Wayne Wobcke; Yang Sok Kim; Paul Compton; Ashesh Mahidadia (Australasian Conference on Artificial Intelligence, 2010)

Automated Recommendation Rule Acquisition for Two-Way Interaction-based Social Network Web Sites. - Yang Sok Kim; Ashesh Mahidadia; Paul Compton; Alfred Krzywicki; Wayne Wobcke; Michael Bain 001; Xiongcai Cai (EKAW (Posters and Demos), 2010)

Learning Collaborative Filtering and Its Application to People to People Recommendation in Social Networks. - Xiongcai Cai; Michael Bain 001; Alfred Krzywicki; Wayne Wobcke; Yang Sok Kim; Paul Compton; Ashesh Mahidadia (ICDM, 2010)

Adaptive Tutorials for Virtual Microscopy: A Design Paradigm to Promote Pedagogical Ownership. - Dror Ben-Naim; Gary Velan; Nadine Marcus; Michael Bain 001 (Intelligent Tutoring Systems (2), 2010)

People Recommendation Based on Aggregated Bidirectional Intentions in Social Network Site. - Yang Sok Kim; Ashesh Mahidadia; Paul Compton; Xiongcai Cai; Michael Bain 001; Alfred Krzywicki; Wayne Wobcke (PKAW, 2010)

Interaction-Based Collaborative Filtering Methods for Recommendation in Online Dating. - Alfred Krzywicki; Wayne Wobcke; Xiongcai Cai; Ashesh Mahidadia; Michael Bain 001; Paul Compton; Yang Sok Kim (WISE, 2010)

Learning with Gene Ontology Annotation Using Feature Selection and Construction. - Elma Akand; Michael Bain 001; Mark D. Temple (Appl. Artif. Intell., 2010)

Structured Induction. - Michael Bain 001 (Encyclopedia of Machine Learning, 2010)

Learning to Make Social Recommendations: A Model-Based Approach. - Xiongcai Cai; Michael Bain 001; Alfred Krzywicki; Wayne Wobcke; Yang Sok Kim; Paul Compton; Ashesh Mahidadia (ADMA (2), 2011)

Knowledge-Guided Identification of Petri Net Models of Large Biological Systems. - Ashwin Srinivasan 001; Michael Bain 001 (ILP, 2011)

Instructional Support for Teachers and Guided Feedback for Students in an Adaptive eLearning Environment. - Nadine Marcus; Dror Ben-Naim; Michael Bain 001 (ITNG, 2011)

People-to-People Recommendation Using Multiple Compatible Subgroups. - Yang Sok Kim; Ashesh Mahidadia; Paul Compton; Alfred Krzywicki; Wayne Wobcke; Xiongcai Cai; Michael Bain 001 (Australasian Conference on Artificial Intelligence, 2012)

Using a Critic to Promote Less Popular Candidates in a People-to-People Recommender System. - Alfred Krzywicki; Wayne Wobcke; Xiongcai Cai; Michael Bain 001; Ashesh Mahidadia; Paul Compton; Yang Sok Kim (IAAI, 2012)

Reciprocal and Heterogeneous Link Prediction in Social Networks. - Xiongcai Cai; Michael Bain 001; Alfred Krzywicki; Wayne Wobcke; Yang Sok Kim; Paul Compton; Ashesh Mahidadia (PAKDD (2), 2012)

Hybrid Techniques to Address Cold Start Problems for People to People Recommendation in Social Networks. - Yang Sok Kim; Alfred Krzywicki; Wayne Wobcke; Ashesh Mahidadia; Paul Compton; Xiongcai Cai; Michael Bain 001 (PRICAI, 2012)

ProCF: Probabilistic Collaborative Filtering for Reciprocal Recommendation. - Xiongcai Cai; Michael Bain 001; Alfred Krzywicki; Wayne Wobcke; Yang Sok Kim; Paul Compton; Ashesh Mahidadia (PAKDD (2), 2013)

A people-to-people content-based reciprocal recommender using hidden markov models. - Ammar S. Alanazi; Michael Bain 001 (RecSys, 2013)

Evaluation and Deployment of a People-to-People Recommender in Online Dating. - Alfred Krzywicki; Wayne Wobcke; Yang Sok Kim; Xiongcai Cai; Michael Bain 001; Paul Compton; Ashesh Mahidadia (AAAI, 2014)

Combining Career Progression and Profile Matching in a Job Recommender System. - Bradford Heap; Alfred Krzywicki; Wayne Wobcke; Michael Bain 001; Paul Compton (PRICAI, 2014)

Identification of Transition Models of Biological Systems in the Presence of Transition Noise. - Ashwin Srinivasan 001; Michael Bain 001; Deepika Vatsa; Sumeet Agarwal (ILP, 2015)

A Deployed People-to-People Recommender System in Online Dating. - Wayne Wobcke; Alfred Krzywicki; Yang Sok Kim; Xiongcai Cai; Michael Bain 001; Paul Compton; Ashesh Mahidadia (AI Mag., 2015)

Collaborative Filtering for people-to-people recommendation in online dating: Data analysis and user trial. - Alfred Krzywicki; Wayne Wobcke; Yang Sok Kim; Xiongcai Cai; Michael Bain 001; Ashesh Mahidadia; Paul Compton (Int. J. Hum. Comput. Stud., 2015)

Data mining for building knowledge bases: techniques, architectures and applications. - Alfred Krzywicki; Wayne Wobcke; Michael Bain 001; John Calvo Martinez; Paul Compton (Knowl. Eng. Rev., 2016)

A Joint Human/Machine Process for Coding Events and Conflict Drivers. - Bradford Heap; Alfred Krzywicki; Susanne Schmeidl; Wayne Wobcke; Michael Bain 001 (ADMA, 2017)

An Investigation into the Role of Domain-Knowledge on the Use of Embeddings. - Lovekesh Vig; Ashwin Srinivasan 001; Michael Bain 001; Ankit Verma (ILP, 2017)

Word Vector Enrichment of Low Frequency Words in the Bag-of-Words Model for Short Text Multi-class Classification Problems. - Bradford Heap; Michael Bain 001; Wayne Wobcke; Alfred Krzywicki; Susanne Schmeidl (CoRR, 2017)

B-CNN: Branch Convolutional Neural Network for Hierarchical Classification. - Xinqi Zhu; Michael Bain 001 (CoRR, 2017)

An empirical study of on-line models for relational data streams. - Ashwin Srinivasan 001; Michael Bain 001 (Mach. Learn., 2017)

Structured Induction. - Michael Bain 001 (Encyclopedia of Machine Learning and Data Mining, 2017)

Using Word Embeddings with Linear Models for Short Text Classification. - Alfred Krzywicki; Bradford Heap; Michael Bain 001; Wayne Wobcke; Susanne Schmeidl (Australasian Conference on Artificial Intelligence, 2018)

The Risks of Low Level Narrow Artificial Intelligence. - John Page; Michael Bain 001; Faqihza Mukhlish (ISR, 2018)

A Knowledge Acquisition Method for Event Extraction and Coding Based on Deep Patterns. - Alfred Krzywicki; Wayne Wobcke; Michael Bain 001; Susanne Schmeidl; Bradford Heap (PKAW, 2018)

Analysing TV Audience Engagement via Twitter: Incremental Segment-Level Opinion Mining of Second Screen Tweets. - Gavin Katz; Bradford Heap; Wayne Wobcke; Michael Bain 001; Sandeepa Kannangara (PRICAI, 2018)

Identification of biological transition systems using meta-interpreted logic programs. - Michael Bain 001; Ashwin Srinivasan 001 (Mach. Learn., 2018)

Logical Explanations for Deep Relational Machines Using Relevance Information. - Ashwin Srinivasan 001; Lovekesh Vig; Michael Bain 001 (J. Mach. Learn. Res., 2019)

From Reward to Histone: Combining Temporal-Difference Learning and Epigenetic Inheritance for Swarm's Coevolving Decision Making. - Faqihza Mukhlish; John Page; Michael Bain 001 (ICDL-EPIROB, 2020)

Using a Semi-Evolutionary Algorithm to Optimize Deep Network Hyper-Parameters with an Application to Donor Detection. - Yu Bai 019; Michael Bain 001 (SSCI, 2020)

Sequential pattern detection for identifying courses of treatment and anomalous claim behaviour in medical insurance. - James Kemp; Christopher Barker; Norm Good; Michael Bain 001 (BIBM, 2022)

Discovering Periodicity in Locally Repeating Patterns. - Alfred Krzywicki; Ashesh Mahidadia; Michael Bain 001 (DSAA, 2022)

A Program-Synthesis Challenge for ARC-Like Tasks. - Aditya Challa; Ashwin Srinivasan 001; Michael Bain 001; Gautam Shroff (ILP, 2022)

One-way Explainability Isn't The Message. - Ashwin Srinivasan 001; Michael Bain 001; Enrico W. Coiera (CoRR, 2022)

Credit Risk Modeling Using Transfer Learning and Domain Adaptation. - Hendra Suryanto; Ashesh Mahidadia; Michael Bain 001; Charles Guan; Ada Guan (Frontiers Artif. Intell., 2022)

Optimizing weighted lazy learning and Naive Bayes classification using differential evolution algorithm. - Yu Bai 019; Michael Bain 001 (J. Ambient Intell. Humaniz. Comput., 2022)

Learning explanations for biological feedback with delays using an event calculus. - Ashwin Srinivasan 001; Michael Bain 001; A. Baskar (Mach. Learn., 2022)

Developing an anomaly detection framework for Medicare claims. - James Kemp; Christopher Barker; Norm Good; Michael Bain 001 (ACSW, 2023)

Context Discovery and Cost Prediction for Detection of Anomalous Medical Claims, with Ontology Structure Providing Domain Knowledge. - James Kemp; Christopher Barker; Norm Good; Michael Bain 001 (HEALTHINF, 2023)

Graphical Association Analysis for Identifying Variation in Provider Claims for Joint Replacement Surgery. - James Kemp; Christopher Barker; Norm Good; Michael Bain 001 (MedInfo, 2023)

A Protocol for Intelligible Interaction Between Agents That Learn and Explain. - Ashwin Srinivasan 001; Michael Bain 001; A. Baskar; Enrico W. Coiera (CoRR, 2023)

Defining Reference Sequences for Nocardia Species by Similarity and Clustering Analyses of 16S rRNA Gene Sequence Data. - Manal Helal; Fanrong Kong; Sharon C. A. Chen; Michael Bain 001; Richard Christen; Vitali Sintchenko (CoRR, 2023)

Responsible Credit Risk Assessment with Machine Learning and Knowledge Acquisition. - Charles Guan; Hendra Suryanto; Ashesh Mahidadia; Michael Bain 001; Paul Compton (Hum. Centric Intell. Syst., 2023)

Charting a Fair Path: FaGGM Fairness-Aware Generative Graphical Models. - Vivian Wei Jiang; Gustavo Batista; Michael Bain 001 (AI (1), 2024)

Towards Responsible Decisions with Limited Training Data Using Human-in-the-Loop. - Ashesh Mahidadia; Michael Bain 001; Hendra Suryanto; Byeong Kang 001; Charles Guan; Paul Compton (PKAW, 2024)

Retina Vision Transformer (RetinaViT): Introducing Scaled Patches into Vision Transformers. - Yuyang Shu; Michael E. Bain (CoRR, 2024)

The neural democratisation of AI. - Michael Bain 001; Allan McCay (AI Soc., 2024)

Editorial: Natural language processing for recommender systems. - Alfred Krzywicki; Michael Bain 001; Wayne Wobcke (Frontiers Big Data, 2025)

A comprehensive survey on integrating large language models with knowledge-based methods. - Wenli Yang; Lilian Some; Michael Bain 001; Byeong Ho Kang 001 (Knowl. Based Syst., 2025)

A model for intelligible interaction between agents that predict and explain. - A. Baskar; Ashwin Srinivasan 001; Michael Bain 001; Enrico W. Coiera (Mach. Learn., 2025)

Structured Program Synthesis using LLMs: Results and Insights from the IPARC Challenge. - Shraddha Surana; Ashwin Srinivasan; Michael Bain 001 (CoRR, 2025)