Michael Bain

Publication Activity (10 Years)

Years Active: 1989-2023
Publications (10 Years): 25

Top Topics

Differential Evolution Algorithm

Top Venues

Publications

Ashwin Srinivasan, Michael Bain, A. Baskar, Enrico W. Coiera
A Protocol for Intelligible Interaction Between Agents That Learn and Explain. CoRR (2023)
James Kemp, Christopher Barker, Norm Good, Michael Bain
Developing an anomaly detection framework for Medicare claims. ACSW (2023)
Manal Helal, Fanrong Kong, Sharon C. A. Chen, Michael Bain, Richard Christen, Vitali Sintchenko
Defining Reference Sequences for Nocardia Species by Similarity and Clustering Analyses of 16S rRNA Gene Sequence Data. CoRR (2023)
James Kemp, Christopher Barker, Norm Good, Michael Bain
Context Discovery and Cost Prediction for Detection of Anomalous Medical Claims, with Ontology Structure Providing Domain Knowledge. HEALTHINF (2023)
Alfred Krzywicki, Ashesh Mahidadia, Michael Bain
Discovering Periodicity in Locally Repeating Patterns. DSAA (2022)
Ashwin Srinivasan, Michael Bain, Enrico W. Coiera
One-way Explainability Isn't The Message. CoRR (2022)
Ashwin Srinivasan, Michael Bain, A. Baskar
Learning explanations for biological feedback with delays using an event calculus. Mach. Learn. 111 (7) (2022)
Yu Bai, Michael Bain
Optimizing weighted lazy learning and Naive Bayes classification using differential evolution algorithm. J. Ambient Intell. Humaniz. Comput. 13 (6) (2022)
James Kemp, Christopher Barker, Norm Good, Michael Bain
Sequential pattern detection for identifying courses of treatment and anomalous claim behaviour in medical insurance. BIBM (2022)
Hendra Suryanto, Ashesh Mahidadia, Michael Bain, Charles Guan, Ada Guan
Credit Risk Modeling Using Transfer Learning and Domain Adaptation. Frontiers Artif. Intell. 5 (2022)
Faqihza Mukhlish, John Page, Michael Bain
From Reward to Histone: Combining Temporal-Difference Learning and Epigenetic Inheritance for Swarm's Coevolving Decision Making. ICDL-EPIROB (2020)
Yu Bai, Michael Bain
Using a Semi-Evolutionary Algorithm to Optimize Deep Network Hyper-Parameters with an Application to Donor Detection. SSCI (2020)
Ashwin Srinivasan, Lovekesh Vig, Michael Bain
Logical Explanations for Deep Relational Machines Using Relevance Information. J. Mach. Learn. Res. 20 (2019)
Alfred Krzywicki, Wayne Wobcke, Michael Bain, Susanne Schmeidl, Bradford Heap
A Knowledge Acquisition Method for Event Extraction and Coding Based on Deep Patterns. PKAW (2018)
Ashwin Srinivasan, Lovekesh Vig, Michael Bain
Logical Explanations for Deep Relational Machines Using Relevance Information. CoRR (2018)
Michael Bain, Ashwin Srinivasan
Identification of biological transition systems using meta-interpreted logic programs. Mach. Learn. 107 (7) (2018)
John Page, Michael Bain, Faqihza Mukhlish
The Risks of Low Level Narrow Artificial Intelligence. ISR (2018)
Alfred Krzywicki, Bradford Heap, Michael Bain, Wayne Wobcke, Susanne Schmeidl
Using Word Embeddings with Linear Models for Short Text Classification. Australasian Conference on Artificial Intelligence (2018)
Gavin Katz, Bradford Heap, Wayne Wobcke, Michael Bain, Sandeepa Kannangara
Analysing TV Audience Engagement via Twitter: Incremental Segment-Level Opinion Mining of Second Screen Tweets. PRICAI (2018)
Xinqi Zhu, Michael Bain
B-CNN: Branch Convolutional Neural Network for Hierarchical Classification. CoRR (2017)
Ashwin Srinivasan, Michael Bain
An empirical study of on-line models for relational data streams. Mach. Learn. 106 (2) (2017)
Lovekesh Vig, Ashwin Srinivasan, Michael Bain, Ankit Verma
An Investigation into the Role of Domain-Knowledge on the Use of Embeddings. ILP (2017)
Bradford Heap, Michael Bain, Wayne Wobcke, Alfred Krzywicki, Susanne Schmeidl
Word Vector Enrichment of Low Frequency Words in the Bag-of-Words Model for Short Text Multi-class Classification Problems. CoRR (2017)
Bradford Heap, Alfred Krzywicki, Susanne Schmeidl, Wayne Wobcke, Michael Bain
A Joint Human/Machine Process for Coding Events and Conflict Drivers. ADMA (2017)
Alfred Krzywicki, Wayne Wobcke, Michael Bain, John Calvo Martinez, Paul Compton
Data mining for building knowledge bases: techniques, architectures and applications. Knowl. Eng. Rev. 31 (2) (2016)
Ashwin Srinivasan, Michael Bain, Deepika Vatsa, Sumeet Agarwal
Identification of Transition Models of Biological Systems in the Presence of Transition Noise. ILP (2015)
Alfred Krzywicki, Wayne Wobcke, Yang Sok Kim, Xiongcai Cai, Michael Bain, Ashesh Mahidadia, Paul Compton
Collaborative Filtering for people-to-people recommendation in online dating: Data analysis and user trial. Int. J. Hum. Comput. Stud. 76 (2015)
Wayne Wobcke, Alfred Krzywicki, Yang Sok Kim, Xiongcai Cai, Michael Bain, Paul Compton, Ashesh Mahidadia
A Deployed People-to-People Recommender System in Online Dating. AI Mag. 36 (3) (2015)
Alfred Krzywicki, Wayne Wobcke, Yang Sok Kim, Xiongcai Cai, Michael Bain, Paul Compton, Ashesh Mahidadia
Evaluation and Deployment of a People-to-People Recommender in Online Dating. AAAI (2014)
Ammar Alanazi, Michael Bain
A people-to-people content-based reciprocal recommender using hidden markov models. RecSys (2013)
Xiongcai Cai, Michael Bain, Alfred Krzywicki, Wayne Wobcke, Yang Sok Kim, Paul Compton, Ashesh Mahidadia
ProCF: Probabilistic Collaborative Filtering for Reciprocal Recommendation. PAKDD (2) (2013)
Alfred Krzywicki, Wayne Wobcke, Xiongcai Cai, Michael Bain, Ashesh Mahidadia, Paul Compton, Yang Sok Kim
Using a Critic to Promote Less Popular Candidates in a People-to-People Recommender System. IAAI (2012)
Yang Sok Kim, Ashesh Mahidadia, Paul Compton, Alfred Krzywicki, Wayne Wobcke, Xiongcai Cai, Michael Bain
People-to-People Recommendation Using Multiple Compatible Subgroups. Australasian Conference on Artificial Intelligence (2012)
Yang Sok Kim, Alfred Krzywicki, Wayne Wobcke, Ashesh Mahidadia, Paul Compton, Xiongcai Cai, Michael Bain
Hybrid Techniques to Address Cold Start Problems for People to People Recommendation in Social Networks. PRICAI (2012)
Xiongcai Cai, Michael Bain, Alfred Krzywicki, Wayne Wobcke, Yang Sok Kim, Paul Compton, Ashesh Mahidadia
Reciprocal and Heterogeneous Link Prediction in Social Networks. PAKDD (2) (2012)
Xiongcai Cai, Michael Bain, Alfred Krzywicki, Wayne Wobcke, Yang Sok Kim, Paul Compton, Ashesh Mahidadia
Learning to Make Social Recommendations: A Model-Based Approach. ADMA (2) (2011)
Ashwin Srinivasan, Michael Bain
Knowledge-Guided Identification of Petri Net Models of Large Biological Systems. ILP (2011)
Nadine Marcus, Dror Ben-Naim, Michael Bain
Instructional Support for Teachers and Guided Feedback for Students in an Adaptive eLearning Environment. ITNG (2011)
Elma Akand, Michael Bain, Mark D. Temple
Learning with Gene Ontology Annotation Using Feature Selection and Construction. Appl. Artif. Intell. 24 (1&2) (2010)
Alfred Krzywicki, Wayne Wobcke, Xiongcai Cai, Ashesh Mahidadia, Michael Bain, Paul Compton, Yang Sok Kim
Interaction-Based Collaborative Filtering Methods for Recommendation in Online Dating. WISE (2010)
Dror Ben-Naim, Gary Velan, Nadine Marcus, Michael Bain
Adaptive Tutorials for Virtual Microscopy: A Design Paradigm to Promote Pedagogical Ownership. Intelligent Tutoring Systems (2) (2010)
Xiongcai Cai, Michael Bain, Alfred Krzywicki, Wayne Wobcke, Yang Sok Kim, Paul Compton, Ashesh Mahidadia
Collaborative Filtering for People to People Recommendation in Social Networks. Australasian Conference on Artificial Intelligence (2010)
Xiongcai Cai, Michael Bain, Alfred Krzywicki, Wayne Wobcke, Yang Sok Kim, Paul Compton, Ashesh Mahidadia
Learning Collaborative Filtering and Its Application to People to People Recommendation in Social Networks. ICDM (2010)
Dror Ben-Naim, Michael Bain, Nadine Marcus
A User-Driven and Data-Driven Approach for Supporting Teachers in Reflection and Adaptation of Adaptive Tutorials. EDM (2009)
Meng Xu, Michael Bain
Mining Minimal Constrained Flow Cycles from Complex Transaction Data. AusDM (2009)
Dror Ben-Naim, Nadine Marcus, Michael Bain
Virtual Apparatus Framework Approach to Constructing Adaptive Tutorials. CSREA EEE (2007)
Michael Bain
Predicate Invention and the Revision of First-Order Concept Lattices. ICFCA (2004)
Michael Bain
Inductive Construction of Ontologies from Formal Concept Analysis. Australian Conference on Artificial Intelligence (2003)
Ashwin Srinivasan, Ross D. King, Michael Bain
An Empirical Study of the Use of Relevance Information in Inductive Logic Programming. J. Mach. Learn. Res. 4 (2003)
Michael Bain
Structured Features from Concept Lattices for Unsupervised Learning and Classification. Australian Joint Conference on Artificial Intelligence (2002)
Ken Ueno, Koichi Furukawa, Michael Bain
Motor Skill as Dynamic Constraint Satisfaction. Electron. Trans. Artif. Intell. 4 (B) (2000)
Stephen Muggleton, Michael Bain
Analogical Prediction. ILP (1999)
Michael Bain, Claude Sammut
A Framework for Behavioural Cloning. Machine Intelligence 15 (1995)
Michael Bain, Ashwin Srinivasan
Inductive Logic Programming With Large-Scale Unstructured Data. Machine Intelligence 14 (1993)
Ashwin Srinivasan, Stephen Muggleton, Michael Bain
The Justification of Logical Theories based on Data Compression. Machine Intelligence 13 (1992)
Stephen Muggleton, Ashwin Srinivasan, Michael Bain
Compression, Significance, and Accuracy. ML (1992)
Michael Bain, Stephen Muggleton
Learning optimal chess strategies. Machine Intelligence 13 (1992)
Michael Bain
Experiments in Non-Monotonic Learning. ML (1991)
Donald Michie, Michael Bain
Machines That Learn and Machines That Teach. SCAI (1989)
Stephen Muggleton, Michael Bain, Jean Hayes Michie, Donald Michie
An Experimental Comparison of Human and Machine Learning Formalisms. ML (1989)