Geoffrey I. Webb
Orcid: 0000-0001-9963-5169Affiliations:
- Monash University, Melbourne, Australia
According to our database1,
Geoffrey I. Webb
authored at least 279 papers
between 1988 and 2024.
Collaborative distances:
Collaborative distances:
Awards
IEEE Fellow
IEEE Fellow 2015, "For contributions to machine learning, data mining and knowledge discovery".
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
Online presence:
-
on scopus.com
-
on orcid.org
-
on id.loc.gov
-
on dl.acm.org
On csauthors.net:
Bibliography
2024
Improving position encoding of transformers for multivariate time series classification.
Data Min. Knowl. Discov., January, 2024
Prevalidated ridge regression is a highly-efficient drop-in replacement for logistic regression for high-dimensional data.
CoRR, 2024
2023
EHR-QC: A streamlined pipeline for automated electronic health records standardisation and preprocessing to predict clinical outcomes.
J. Biomed. Informatics, November, 2023
Parameterizing the cost function of dynamic time warping with application to time series classification.
Data Min. Knowl. Discov., September, 2023
Hydra: competing convolutional kernels for fast and accurate time series classification.
Data Min. Knowl. Discov., September, 2023
Pattern Recognit., August, 2023
Mach. Learn., July, 2023
TIMER is a Siamese neural network-based framework for identifying both general and species-specific bacterial promoters.
Briefings Bioinform., July, 2023
A Bayesian-inspired, deep learning-based, semi-supervised domain adaptation technique for land cover mapping.
Mach. Learn., June, 2023
Knowl. Inf. Syst., June, 2023
Pattern Recognit., May, 2023
Ultra-fast meta-parameter optimization for time series similarity measures with application to nearest neighbour classification.
Knowl. Inf. Syst., May, 2023
PFresGO: an attention mechanism-based deep-learning approach for protein annotation by integrating gene ontology inter-relationships.
Bioinform., March, 2023
Series2Vec: Similarity-based Self-supervised Representation Learning for Time Series Classification.
CoRR, 2023
CoRR, 2023
CARLA: A Self-supervised Contrastive Representation Learning Approach for Time Series Anomaly Detection.
CoRR, 2023
A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection.
CoRR, 2023
An Approach to Multiple Comparison Benchmark Evaluations that is Stable Under Manipulation of the Comparate Set.
CoRR, 2023
Proximity Forest 2.0: A new effective and scalable similarity-based classifier for time series.
CoRR, 2023
Deep Learning for Time Series Classification and Extrinsic Regression: A Current Survey.
CoRR, 2023
Proceedings of the International Conference on Machine Learning and Applications, 2023
Computing Marginal and Conditional Divergences between Decomposable Models with Applications.
Proceedings of the IEEE International Conference on Data Mining, 2023
ShapeDBA: Generating Effective Time Series Prototypes Using ShapeDTW Barycenter Averaging.
Proceedings of the Advanced Analytics and Learning on Temporal Data, 2023
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
IEEE Trans. Knowl. Data Eng., 2022
PROST: AlphaFold2-aware Sequence-Based Predictor to Estimate Protein Stability Changes upon Missense Mutations.
J. Chem. Inf. Model., 2022
Environ. Model. Softw., 2022
MultiRocket: multiple pooling operators and transformations for fast and effective time series classification.
Data Min. Knowl. Discov., 2022
Data Min. Knowl. Discov., 2022
DEMoS: a deep learning-based ensemble approach for predicting the molecular subtypes of gastric adenocarcinomas from histopathological images.
Bioinform., 2022
Critical assessment of computational tools for prokaryotic and eukaryotic promoter prediction.
Briefings Bioinform., 2022
ASPIRER: a new computational approach for identifying non-classical secreted proteins based on deep learning.
Briefings Bioinform., 2022
Positive-unlabeled learning in bioinformatics and computational biology: a brief review.
Briefings Bioinform., 2022
Clarion is a multi-label problem transformation method for identifying mRNA subcellular localizations.
Briefings Bioinform., 2022
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2022
Proceedings of the IEEE International Conference on Data Mining, 2022
2021
Bioinform., November, 2021
IEEE ACM Trans. Comput. Biol. Bioinform., 2021
Data Min. Knowl. Discov., 2021
CoRR, 2021
MultiRocket: Effective summary statistics for convolutional outputs in time series classification.
CoRR, 2021
Bioinform., 2021
Anthem: a user customised tool for fast and accurate prediction of binding between peptides and HLA class I molecules.
Briefings Bioinform., 2021
Assessing the performance of computational predictors for estimating protein stability changes upon missense mutations.
Briefings Bioinform., 2021
Proceedings of the 2021 SIAM International Conference on Data Mining, 2021
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021
MiniRocket: A Very Fast (Almost) Deterministic Transform for Time Series Classification.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021
Proceedings of the IEEE International Conference on Data Mining, 2021
2020
An Incremental Construction of Deep Neuro Fuzzy System for Continual Learning of Nonstationary Data Streams.
IEEE Trans. Fuzzy Syst., 2020
Knowl. Inf. Syst., 2020
J. Bioinform. Comput. Biol., 2020
Procleave: Predicting Protease-specific Substrate Cleavage Sites by Combining Sequence and Structural Information.
Genom. Proteom. Bioinform., 2020
Data Min. Knowl. Discov., 2020
Data Min. Knowl. Discov., 2020
Data Min. Knowl. Discov., 2020
ROCKET: exceptionally fast and accurate time series classification using random convolutional kernels.
Data Min. Knowl. Discov., 2020
Dagstuhl Reports, 2020
Discriminative, Generative and Self-Supervised Approaches for Target-Agnostic Learning.
CoRR, 2020
A Bayesian-inspired, deep learning, semi-supervised domain adaptation technique for land cover mapping.
CoRR, 2020
DeepCleave: a deep learning predictor for caspase and matrix metalloprotease substrates and cleavage sites.
Bioinform., 2020
PRISMOID: a comprehensive 3D structure database for post-translational modifications and mutations with functional impact.
Briefings Bioinform., 2020
Comprehensive review and assessment of computational methods for predicting RNA post-transcriptional modification sites from RNA sequences.
Briefings Bioinform., 2020
iLearn : an integrated platform and meta-learner for feature engineering, machine-learning analysis and modeling of DNA, RNA and protein sequence data.
Briefings Bioinform., 2020
IEEE Access, 2020
Unsupervised Domain Adaptation Techniques for Classification of Satellite Image Time Series.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2020
Proceedings of the 7th IEEE International Conference on Data Science and Advanced Analytics, 2020
2019
Temporal Convolutional Neural Network for the Classification of Satellite Image Time Series.
Remote. Sens., 2019
Knowl. Inf. Syst., 2019
Adaptive online extreme learning machine by regulating forgetting factor by concept drift map.
Neurocomputing, 2019
Proximity Forest: an effective and scalable distance-based classifier for time series.
Data Min. Knowl. Discov., 2019
SIMLIN: a bioinformatics tool for prediction of S-sulphenylation in the human proteome based on multi-stage ensemble-learning models.
BMC Bioinform., 2019
BMC Bioinform., 2019
Computational analysis and prediction of lysine malonylation sites by exploiting informative features in an integrative machine-learning framework.
Briefings Bioinform., 2019
Systematic analysis and prediction of type IV secreted effector proteins by machine learning approaches.
Briefings Bioinform., 2019
iProt-Sub: a comprehensive package for accurately mapping and predicting protease-specific substrates and cleavage sites.
Briefings Bioinform., 2019
Twenty years of bioinformatics research for protease-specific substrate and cleavage site prediction: a comprehensive revisit and benchmarking of existing methods.
Briefings Bioinform., 2019
Large-scale comparative assessment of computational predictors for lysine post-translational modification sites.
Briefings Bioinform., 2019
Proceedings of the 2019 SIAM International Conference on Data Mining, 2019
Proceedings of the 10th International Workshop on the Analysis of Multitemporal Remote Sensing Images, 2019
Exploring Data Quantity Requirements for Domain Adaptation in the Classification of Satellite Image Time Series.
Proceedings of the 10th International Workshop on the Analysis of Multitemporal Remote Sensing Images, 2019
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019
2018
Accurate parameter estimation for Bayesian network classifiers using hierarchical Dirichlet processes.
Mach. Learn., 2018
Int. J. Geogr. Inf. Sci., 2018
CoRR, 2018
An Incremental Construction of Deep Neuro Fuzzy System for Continual Learning of Non-stationary Data Streams.
CoRR, 2018
On the Inter-relationships among Drift rate, Forgetting rate, Bias/variance profile and Error.
CoRR, 2018
PROSPERous: high-throughput prediction of substrate cleavage sites for 90 proteases with improved accuracy.
Bioinform., 2018
iFeature: a Python package and web server for features extraction and selection from protein and peptide sequences.
Bioinform., 2018
Comprehensive assessment and performance improvement of effector protein predictors for bacterial secretion systems III, IV and VI.
Briefings Bioinform., 2018
Efficient and Effective Accelerated Hierarchical Higher-Order Logistic Regression for Large Data Quantities.
Proceedings of the 2018 SIAM International Conference on Data Mining, 2018
Proceedings of the 2018 SIAM International Conference on Data Mining, 2018
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018
2017
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017
IEEE Trans. Knowl. Data Eng., 2017
Knowl. Inf. Syst., 2017
SimUSF: an efficient and effective similarity measure that is invariant to violations of the interval scale assumption.
Data Min. Knowl. Discov., 2017
POSSUM: a bioinformatics toolkit for generating numerical sequence feature descriptors based on PSSM profiles.
Bioinform., 2017
Critical evaluation of bioinformatics tools for the prediction of protein crystallization propensity.
Briefings Bioinform., 2017
Proceedings of the 2017 SIAM International Conference on Data Mining, 2017
Proceedings of the 2017 SIAM International Conference on Data Mining, 2017
Specious rules: an efficient and effective unifying method for removing misleading and uninformative patterns in association rule mining.
Proceedings of the 2017 SIAM International Conference on Data Mining, 2017
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017
2016
Faster and more accurate classification of time series by exploiting a novel dynamic time warping averaging algorithm.
Knowl. Inf. Syst., 2016
Data Min. Knowl. Discov., 2016
Data Min. Knowl. Discov., 2016
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2016
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016
2015
GlycoMine: a machine learning-based approach for predicting N-, C- and O-linked glycosylation in the human proteome.
Bioinform., 2015
Proceedings of the 2015 SIAM International Conference on Data Mining, Vancouver, BC, Canada, April 30, 2015
2014
Proceedings of the 1st ECML/PKDD Workshop on Statistically Sound Data Mining, 2014
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2014
Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014
Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014
Proceedings of the 2014 IEEE International Conference on Data Mining, 2014
Contrary to Popular Belief Incremental Discretization can be Sound, Computationally Efficient and Extremely Useful for Streaming Data.
Proceedings of the 2014 IEEE International Conference on Data Mining, 2014
Dynamic Time Warping Averaging of Time Series Allows Faster and More Accurate Classification.
Proceedings of the 2014 IEEE International Conference on Data Mining, 2014
A Statistically Efficient and Scalable Method for Log-Linear Analysis of High-Dimensional Data.
Proceedings of the 2014 IEEE International Conference on Data Mining, 2014
2013
ACM Trans. Knowl. Discov. Data, 2013
J. Mach. Learn. Res., 2013
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2013
Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013
Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013
2012
Subsumption resolution: an efficient and effective technique for semi-naive Bayesian learning.
Mach. Learn., 2012
Learning by extrapolation from marginal to full-multivariate probability distributions: decreasingly naive Bayesian classification.
Mach. Learn., 2012
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2012
Proceedings of the Hybrid Artificial Intelligent Systems - 7th International Conference, 2012
Proceedings of the Twenty-Third Australasian Database Conference, 2012
2011
Mach. Learn., 2011
J. Bioinform. Comput. Biol., 2011
2010
Proceedings of the Encyclopedia of Machine Learning, 2010
Proceedings of the Encyclopedia of Machine Learning, 2010
Proceedings of the Encyclopedia of Machine Learning, 2010
Proceedings of the Encyclopedia of Machine Learning, 2010
Proceedings of the Encyclopedia of Machine Learning, 2010
Proceedings of the Data Mining and Knowledge Discovery Handbook, 2nd ed., 2010
Self-sufficient itemsets: An approach to screening potentially interesting associations between items.
ACM Trans. Knowl. Discov. Data, 2010
Bioinform., 2010
EGM: encapsulated gene-by-gene matching to identify gene orthologs and homologous segments in genomes.
Bioinform., 2010
2009
Mach. Learn., 2009
Supervised Descriptive Rule Discovery: A Unifying Survey of Contrast Set, Emerging Pattern and Subgroup Mining.
J. Mach. Learn. Res., 2009
A Comparative Study of Bandwidth Choice in Kernel Density Estimation for Naive Bayesian Classification.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2009
Proceedings of the Multiple Classifier Systems, 8th International Workshop, 2009
2008
Layered critical values: a powerful direct-adjustment approach to discovering significant patterns.
Mach. Learn., 2008
Multi-Strategy Ensemble Learning, Ensembles of Bayesian Classifiers, and the Problem of False Discoveries.
Proceedings of the Data Mining and Analytics 2008, 2008
2007
To Select or To Weigh: A Comparative Study of Linear Combination Schemes for SuperParent-One-Dependence Estimators.
IEEE Trans. Knowl. Data Eng., 2007
Classifying under computational resource constraints: anytime classification using probabilistic estimators.
Mach. Learn., 2007
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2007
Finding the Right Family: Parent and Child Selection for Averaged One-Dependence Estimators.
Proceedings of the Machine Learning: ECML 2007, 2007
2006
Proceedings of the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2006
Proceedings of the Machine Learning, 2006
To Select or To Weigh: A Comparative Study of Model Selection and Model Weighing for SPODE Ensembles.
Proceedings of the Machine Learning: ECML 2006, 2006
Proceedings of the Data Mining - Theory, Methodology, Techniques, and Applications, 2006
Proceedings of the Data Mining - Theory, Methodology, Techniques, and Applications, 2006
Proceedings of the Advances in Intelligent IT, 2006
Proceedings of the Advanced Data Mining and Applications, Second International Conference, 2006
2005
On the Application of ROC Analysis to Predict Classification Performance Under Varying Class Distributions.
Mach. Learn., 2005
Discarding Insignificant Rules during Impact Rule Discovery in Large, Dense Databases.
Proceedings of the 2005 SIAM International Conference on Data Mining, 2005
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2005
Proceedings of the AI 2005: Advances in Artificial Intelligence, 2005
K-Optimal Pattern Discovery: An Efficient and Effective Approach to Exploratory Data Mining.
Proceedings of the AI 2005: Advances in Artificial Intelligence, 2005
Discretization Methods.
Proceedings of the Data Mining and Knowledge Discovery Handbook., 2005
2004
Multistrategy Ensemble Learning: Reducing Error by Combining Ensemble Learning Techniques.
IEEE Trans. Knowl. Data Eng., 2004
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2004
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2004
2003
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2003
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2003
Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 24, 2003
Proceedings of the AI 2003: Advances in Artificial Intelligence, 2003
Proceedings of the AI 2003: Advances in Artificial Intelligence, 2003
A Case Study in Feature Invention for Breast Cancer Diagnosis Using X-Ray Scatter Images.
Proceedings of the AI 2003: Advances in Artificial Intelligence, 2003
2002
Proceedings of the Principles of Data Mining and Knowledge Discovery, 2002
Non-Disjoint Discretization for Naive-Bayes Classifiers.
Proceedings of the Machine Learning, 2002
Proceedings of the 2002 IEEE International Conference on Data Mining (ICDM 2002), 2002
Proceedings of the 2002 IEEE International Conference on Data Mining (ICDM 2002), 2002
Averaged One-Dependence Estimators: Preliminary Results.
Proceedings of the 15th Australian Joint Conference on Artificial Intelligence 2002, 2002
A Heuristic Lazy Bayesian Rule Algorithm.
Proceedings of the 15th Australian Joint Conference on Artificial Intelligence 2002, 2002
Proceedings of the AI 2002: Advances in Artificial Intelligence, 2002
2001
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining, 2001
Proceedings of the Machine Learning: EMCL 2001, 2001
Proceedings of the AI 2001: Advances in Artificial Intelligence, 2001
Proceedings of the AI 2001: Advances in Artificial Intelligence, 2001
2000
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining, 2000
1999
An Experimental Evaluation of Integrating Machine Learning with Knowledge Acquisition.
Mach. Learn., 1999
Stochastic Attribute Selection Committees with Aultiple Boosting: Learning More Accurate and More Stable Classifer Committees.
Proceedings of the Methodologies for Knowledge Discovery and Data Mining, 1999
Proceedings of the Methodologies for Knowledge Discovery and Data Mining, 1999
Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, 1999
Lazy Bayesian Rules: A Lazy Semi-Naive Bayesian Learning Technique Competitive to Boosting Decision Trees.
Proceedings of the Sixteenth International Conference on Machine Learning (ICML 1999), Bled, Slovenia, June 27, 1999
1998
User Model. User Adapt. Interact., 1998
User Model. User Adapt. Interact., 1998
Evaluation of Data Aging: A Technique for Discounting Old Data During Student Modeling.
Proceedings of the Intelligent Tutoring Systems, 4th International Conference, 1998
Integrating boosting and stochastic attribute selection committees for further improving the performance of decision tree learning.
Proceedings of the Tenth IEEE International Conference on Tools with Artificial Intelligence, 1998
Proceedings of the Machine Learning: ECML-98, 1998
Proceedings of the Advanced Topics in Artificial Intelligence, 1998
Proceedings of the Advanced Topics in Artificial Intelligence, 1998
Proceedings of the Advanced Topics in Artificial Intelligence, 1998
1997
Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, 1997
Using Decision Trees for Agent Modelling: A Study on Resolving Confliction Predictions.
Proceedings of the Advanced Topics in Artificial Intelligence, 1997
1996
Integrating machine learning with knowledge acquisition through direct interaction with domain experts.
Knowl. Based Syst., 1996
J. Artif. Intell. Res., 1996
Proceedings of the PRICAI'96: Topics in Artificial Intelligence, 1996
1995
Feature Based Modelling: A Methodology for Producing Coherent, Consistent, Dynamically Changing Models of Agents' Competencies.
User Model. User Adapt. Interact., 1995
J. Artif. Intell. Res., 1995
Proceedings of the Eighth International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, 1995
Transparency Debugging with Explanations for Novice Programmers.
Proceedings of the Second International Workshop on Automated Debugging, 1995
1992
Inducing diagnostic rules for glomerular disease with the DLG machine learning algorithm.
Artif. Intell. Medicine, 1992
Proceedings of the Intelligent Tutoring Systems, Second International Conference, 1992
1990
J. Exp. Theor. Artif. Intell., 1990
1988
Proceedings of the AI '88: 2nd Australian Joint Artificial Intelligence Conference, 1988