Michael Mayo - RankMe

75 papers A 1B 17C 2Misc 6Journal 20Unranked 29

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	Feature extractor stacking for cross-domain few-shot learning. Mach. Learn. Hongyu Wang, Eibe Frank, Bernhard Pfahringer, Michael Mayo, Geoff Holmes
2023	B	`conf`	Keep It Simple: Fault Tolerance Evaluation of Federated Learning with Unreliable Clients. CLOUD Victoria Huang, Shaleeza Sohail, Michael Mayo, Tania Lorido-Botran, Mark Rodrigues, Chris Anderson, Melanie Ooi
2023	J	`jnl`	Keep It Simple: Fault Tolerance Evaluation of Federated Learning with Unreliable Clients. CoRR Victoria Huang, Shaleeza Sohail, Michael Mayo, Tania Lorido-Botran, Mark Rodrigues, Chris Anderson, Melanie Ooi
2023	J	`jnl`	Rural AI: Serverless-Powered Federated Learning for Remote Applications. IEEE Internet Comput. Panos Patros, Melanie Ooi, Victoria Huang, Michael Mayo, Chris Anderson, Stephen Burroughs, Matt Baughman, Osama Almurshed, Omer F. Rana, Ryan Chard, Kyle Chard, Ian T. Foster
2022	—	`conf`	Adaptive Edge-Cloud Environments for Rural AI. SCC Osama Almurshed, Panos Patros, Victoria Huang, Michael Mayo, Melanie Ooi, Ryan Chard, Kyle Chard, Omer F. Rana, Harshaan Nagra, Matt Baughman, Ian T. Foster
2022	B	`conf`	Alzheimer's Disease Detection via a Surrogate Brain Age Prediction Task using 3D Convolutional Neural Networks. IJCNN Chen Zheng, Bernhard Pfahringer, Michael Mayo
2022	—	`conf`	Assessing Vulnerability from Its Description. UbiSec Zijing Zhang, Vimal Kumar, Michael Mayo, Albert Bifet
2022	—	`conf`	Clinically-relevant Summarisation of Cataract Surgery Videos Using Deep Learning. ACIIDS (Companion) Jesse Whitten, James McKelvie, Michael Mayo
2022	J	`jnl`	Cross-domain Few-shot Meta-learning Using Stacking. CoRR Hongyu Wang, Eibe Frank, Bernhard Pfahringer, Michael Mayo, Geoffrey Holmes
2022	—	`conf`	Domain Generalisation for Glaucoma Detection in Retinal Images from Unseen Fundus Cameras. ACIIDS (2) Hansi Gunasinghe, James McKelvie, Abigail M. Y. Koay, Michael Mayo
2022	Misc	`conf`	Evaluation of Deep Learning Techniques on a Novel Hierarchical Surgical Tool Dataset. AI Mark Rodrigues, Michael Mayo, Panos Patros
2022	—	`conf`	Experiments in Cross-domain Few-shot Learning for Image Classification: Extended Abstract. Meta-Knowledge Transfer @ ECML/PKDD Hongyu Wang, Huon Fraser, Henry Gouk, Eibe Frank, Bernhard Pfahringer, Michael Mayo, Geoff Holmes
2022	J	`jnl`	Predicting glucose level with an adapted branch predictor. Comput. Biol. Medicine Tomas Koutny, Michael Mayo
2022	—	`conf`	Prevalence of sociodemographic factors in a cohort of diabetes mellitus: a retrospective study. ICMHI Madurapperumage A. Erandathi, William Yu Chung Wang, Michael Mayo, Ibrahim Shafiu
2022	J	`jnl`	Surgical Tool Datasets for Machine Learning Research: A Survey. Int. J. Comput. Vis. Mark Rodrigues, Michael Mayo, Panos Patros
2021	—	`conf`	A Systematic Review on Extracting Predictors for Forecasting Complications of Diabetes Mellitus. ICMHI Anuradha Madurapperumage, William Yu Chung Wang, Michael Mayo
2021	—	`conf`	Comparison Of Pretrained Feature Extractors For Glaucoma Detection. ISBI Hansi Gunasinghe, James McKelvie, Abigail M. Y. Koay, Michael Mayo
2021	—	`conf`	Interpretable Deep Learning for Surgical Tool Management. iMIMIC/TDA4MedicalData@MICCAI Mark Rodrigues, Michael Mayo, Panos Patros
2021	J	`jnl`	Metaheuristic Optimization of Insulin Infusion Protocols Using Historical Data with Validation Using a Patient Simulator. Vietnam. J. Comput. Sci. Hongyu Wang, Lynne Chepulis, Ryan G. Paul, Michael Mayo
2020	—	`conf`	A Comparison of Machine Learning Methods for Cross-Domain Few-Shot Learning. Australasian Conference on Artificial Intelligence Hongyu Wang, Henry Gouk, Eibe Frank, Bernhard Pfahringer, Michael Mayo
2020	J	`jnl`	A review of Automatic end-to-end De-Identification: Is High Accuracy the Only Metric? Appl. Artif. Intell. Vithya Yogarajan, Bernhard Pfahringer, Michael Mayo
2020	—	`conf`	Comparing High Dimensional Word Embeddings Trained on Medical Text to Bag-of-Words for Predicting Medical Codes. ACIIDS (1) Vithya Yogarajan, Henry Gouk, Tony Smith, Michael Mayo, Bernhard Pfahringer
2020	J	`jnl`	Improving Naive Bayes for Regression with Optimized Artificial Surrogate Data. Appl. Artif. Intell. Michael Mayo, Eibe Frank
2020	—	`conf`	In Silico Comparison of Continuous Glucose Monitor Failure Mode Strategies for an Artificial Pancreas. KDH@ECAI Yunjie Lisa Lu, Abigail M. Y. Koay, Michael Mayo
2020	B	`conf`	Interpretable Machine Learning with Bitonic Generalized Additive Models and Automatic Feature Construction. DS Noëlie Cherrier, Michael Mayo, Jean-Philippe Poli, Maxime Defurne, Franck Sabatié
2020	—	`conf`	Metaheuristics for Discovering Favourable Continuous Intravenous Insulin Rate Protocols from Historical Patient Data. ACIIDS (1) Hongyu Wang, Lynne Chepulis, Ryan G. Paul, Michael Mayo
2020	—	`conf`	Neural Multi-class Classification Approach to Blood Glucose Level Forecasting with Prediction Uncertainty Visualisation. KDH@ECAI Michael Mayo, Tomas Koutny
2020	—	`conf`	Predicting Diabetes Mellitus and its Complications through a Graph-Based Risk Scoring System. ICMHI Madurapperumage A. Erandathi, William Y. C. Wang, Michael Mayo
2019	—	`conf`	A Nearest Neighbour-Based Analysis to Identify Patients from Continuous Glucose Monitor Data. ACIIDS (2) Michael Mayo, Vithya Yogarajan
2019	J	`jnl`	A survey of neural network-based cancer prediction models from microarray data. Artif. Intell. Medicine Maisa Daoud, Michael Mayo
2019	J	`jnl`	Automatic end-to-end De-identification: Is high accuracy the only metric? CoRR Vithya Yogarajan, Bernhard Pfahringer, Michael Mayo
2019	B	`conf`	Data Normalisation using Differential Evolution and Aggregated Logistic Functions. CEC Michael Mayo, Maisa Daoud
2019	—	`conf`	Improving the Robustness of the Glycemic Variability Percentage Metric to Sensor Dropouts in Continuous Glucose Monitor Data. ACIIDS (2) Michael Mayo
2019	—	`conf`	Maintaining SLOs of Cloud-Native Applications Via Self-Adaptive Resource Sharing. SASO Vladimir Podolskiy, Michael Mayo, Abigail M. Y. Koay, Michael Gerndt, Panos Patros
2019	B	`conf`	RBFA: Radial Basis Function Autoencoders. CEC Maisa Daoud, Michael Mayo, Sally Jo Cunningham
2018	—	`conf`	A Novel Synthetic Over-Sampling Technique for Imbalanced Classification of Gene Expressions Using Autoencoders and Swarm Optimization. Australasian Conference on Artificial Intelligence Maisa Daoud, Michael Mayo
2018	J	`jnl`	A survey of automatic de-identification of longitudinal clinical narratives. CoRR Vithya Yogarajan, Michael Mayo, Bernhard Pfahringer
2018	—	`conf`	Neural Networks for Predicting the Output of wind flow Simulations Over Complex Topographies. ICBK Michael Mayo, Sarah Wakes, Chris Anderson
2018	A	`conf`	Shock Absorbing Exoskeleton for Vertical Mobility System: Concept and Feasibility Study. IROS Jun Ueda, Melih Turkseven, Euisun Kim, Quincy Lowery, Courtland Bivens, Michael Mayo
2018	J	`jnl`	Using Swarm Optimization To Enhance Autoencoders Images. CoRR Maisa Daoud, Michael Mayo
2017	J	`jnl`	Aesthetic Local Search of Wind Farm Layouts. Inf. Michael Mayo, Maisa Daoud
2017	J	`jnl`	Aesthetic local search of wind farm layouts. PeerJ Prepr. Michael Mayo, Maisa Daoud
2017	B	`conf`	Constructing Document Vectors Using Kernel Density Estimates. MDAI Michael Mayo, Sean Goltz
2017	J	`jnl`	Improving Naive Bayes for Regression with Optimised Artificial Surrogate Data. CoRR Michael Mayo, Eibe Frank
2017	—	`conf`	Surrogate modeling a computational fluid dynamics-based wind turbine wake simulation using machine learning. SSCI Brett Wilson, Sarah Wakes, Michael Mayo
2016	B	`conf`	BlockCopy-based operators for evolving efficient wind farm layouts. CEC Michael Mayo, Chen Zheng
2016	Misc	`conf`	Deferral classification of evolving temporal dependent data streams. SAC Michael Mayo, Albert Bifet
2016	C	`conf`	Proceedings in Adaptation, Learning and Optimization. IES Michael Mayo, Maisa Daoud, Chen Zheng
2016	—	`conf`	Towards a New Evolutionary Subsampling Technique for Heuristic Optimisation of Load Disaggregators. PAKDD Workshops Michael Mayo, Sara Omranian
2015	Misc	`conf`	Alternating model trees. SAC Eibe Frank, Michael Mayo, Stefan Kramer
2015	B	`conf`	An Adaptive Model-Based Mutation Operator for the Wind Farm Layout Optimisation Problem. SMC Michael Mayo, Maisa Daoud
2014	B	`conf`	Evolving artificial datasets to improve interpretable classifiers. IEEE Congress on Evolutionary Computation Michael Mayo, Quan Sun
2014	Misc	`ed.`	Proceedings of the 29th International Conference on Image and Vision Computing New Zealand, IVCNZ 2014, Hamilton, New Zealand, November 19-21, 2014 IVCNZ Michael J. Cree, Lee V. Streeter, John A. Perrone, Michael Mayo, Anthony M. Blake
2013	B	`conf`	Identifying Market Price Levels Using Differential Evolution. EvoApplications Michael Mayo
2013	B	`conf`	Predicting Regression Test Failures Using Genetic Algorithm-Selected Dynamic Performance Analysis Metrics. SSBSE Michael Mayo, Simon A. Spacey
2013	—	`conf`	Towards a Framework for Designing Full Model Selection and Optimization Systems. MCS Quan Sun, Bernhard Pfahringer, Michael Mayo
2012	Misc	`conf`	Cartesian Genetic Programming for Trading: A Preliminary Investigation. AusDM Michael Mayo
2012	B	`conf`	Evolutionary Data Selection for Enhancing Models of Intraday Forex Time Series. EvoApplications Michael Mayo
2012	—	`conf`	Full model selection in the space of data mining operators. GECCO (Companion) Quan Sun, Bernhard Pfahringer, Michael Mayo
2011	B	`conf`	Hybridizing Data Stream Mining and Technical Indicators in Automated Trading Systems. MDAI Michael Mayo
2011	J	`jnl`	Modelling epistasis in genetic disease using Petri nets, evolutionary computation and frequent itemset mining. Expert Syst. Appl. Michael Mayo, Lorenzo Beretta
2010	—	`conf`	Evolving Concurrent Petri Net Models of Epistasis. ACIIDS (2) Michael Mayo, Lorenzo Beretta
2010	J	`jnl`	Genomic analysis of a rare human tumor. BMC Bioinform. Steven J. M. Jones, Janessa Laskin, Yvonne Y. Li, Obi L. Griffith, Jianghong An, Mikhail Bilenky, Yaron S. N. Butterfield, Timothee Cezard, Eric Chuah, Richard Corbett, Anthony P. Fejes, Malachi Griffith, John Yee, Montgomery Martin, Michael Mayo, Nataliya Melnyk, Ryan D. Morin, Trevor J. Pugh, Tesa Severson, Sohrab P. Shah, Margaret Sutcliffe, Angela Tam, Jefferson Terry, Nina Thiessen, Thomas Thomson, Richard Varhol, Thomas Zeng, Yongjun Zhao, Richard A. Moore, David G. Huntsman, Inanç Birol, Martin Hirst, Robert A. Holt, Marco A. Marra
2009	B	`conf`	3D Face Recognition Using Multiview Keypoint Matching. AVSS Michael Mayo, Edmond Zhang
2009	Misc	`conf`	SIFTing the Relevant from the Irrelevant: Automatically Detecting Objects in Training Images. DICTA Edmond Zhang, Michael Mayo
2007	J	`jnl`	Automatic species identification of live moths. Knowl. Based Syst. Michael Mayo, Anna T. Watson
2007	—	`conf`	Random Convolution Ensembles. PCM Michael Mayo
2006	—	`conf`	Automatic Species Identification of Live Moths. SGAI Conf. (Applications) Michael Mayo, Anna T. Watson
2005	B	`conf`	Bayesian Sequence Learning for Predicting Protein Cleavage Points. PAKDD Michael Mayo
2004	—	`conf`	Using 2D and 3D Landmarks to Solve the Correspondence Problem in Cognitive Robot Mapping. Spatial Cognition Margaret E. Jefferies, Michael J. Cree, Michael Mayo, Jesse T. Baker
2004	B	`conf`	Using Context to Solve the Correspondence Problem in Simultaneous Localisation and Mapping. PRICAI Margaret E. Jefferies, Wenrong Weng, Jesse T. Baker, Michael Mayo
2002	J	`jnl`	Using Evaluation to Shape ITS Design: Results and Experiences with SQL-Tutor. User Model. User Adapt. Interact. Antonija Mitrovic, Brent Martin, Michael Mayo
2001	C	`conf`	Constraint-Based Tutors: A Success Story. IEA/AIE Antonija Mitrovic, Michael Mayo, Pramuditha Suraweera, Brent Martin
2000	B	`conf`	Using a Probabilistic Student Model to Control Problem Difficulty. Intelligent Tutoring Systems Michael Mayo, Antonija Mitrovic
1999	—	`conf`	Estimating Problem Value in an Intelligent Tutoring System Using Bayesian Networks. Australian Joint Conference on Artificial Intelligence Michael Mayo, Antonija Mitrovic