Webb, Geoffrey I.

37 publications

AAAI 2025 Little Is Enough: Boosting Privacy by Sharing Only Hard Labels in Federated Semi-Supervised Learning Amr Abourayya, Jens Kleesiek, Kanishka Rao, Erman Ayday, Bharat Rao, Geoffrey I. Webb, Michael Kamp

DMLR 2025 MONSTER: Monash Scalable Time Series Evaluation Repository Angus Dempster, Navid Mohammadi Foumani, Chang Wei Tan, Lynn Miller, Amish Mishra, Mahsa Salehi, Charlotte Pelletier, Daniel F. Schmidt, Geoffrey I. Webb

MLJ 2023 A Bayesian-Inspired, Deep Learning-Based, Semi-Supervised Domain Adaptation Technique for Land Cover Mapping Benjamin Lucas, Charlotte Pelletier, Daniel F. Schmidt, Geoffrey I. Webb, François Petitjean

AAAI 2023 Computing Divergences Between Discrete Decomposable Models Loong Kuan Lee, Nico Piatkowski, François Petitjean, Geoffrey I. Webb

MLJ 2023 SETAR-Tree: A Novel and Accurate Tree Algorithm for Global Time Series Forecasting Rakshitha Godahewa, Geoffrey I. Webb, Daniel F. Schmidt, Christoph Bergmeir

NeurIPSW 2022 AIMHI: Protecting Sensitive Data Through Federated Co-Training Amr Abourayya, Michael Kamp, Erman Ayday, Jens Kleesiek, Kanishka Rao, Geoffrey I. Webb, Bharat Rao

MLJ 2018 Accurate Parameter Estimation for Bayesian Network Classifiers Using Hierarchical Dirichlet Processes François Petitjean, Wray L. Buntine, Geoffrey I. Webb, Nayyar Abbas Zaidi

MLJ 2017 Efficient Parameter Learning of Bayesian Network Classifiers Nayyar Abbas Zaidi, Geoffrey I. Webb, Mark James Carman, François Petitjean, Wray L. Buntine, Mike Hynes, Hans De Sterck

MLJ 2016 ALRn: Accelerated Higher-Order Logistic Regression Nayyar Abbas Zaidi, Geoffrey I. Webb, Mark James Carman, François Petitjean, Jesús Cerquides

JMLR 2016 Scalable Learning of Bayesian Network Classifiers Ana M. Martínez, Geoffrey I. Webb, Shenglei Chen, Nayyar A. Zaidi

MLJ 2015 Introduction: Special Issue of Selected Papers of ACML 2013 Cheng Soon Ong, Wray L. Buntine, Tu Bao Ho, Masashi Sugiyama, Geoffrey I. Webb

JMLR 2013 Alleviating Naive Bayes Attribute Independence Assumption by Attribute Weighting Nayyar A. Zaidi, Jesús Cerquides, Mark J. Carman, Geoffrey I. Webb

MLJ 2012 Learning by Extrapolation from Marginal to Full-Multivariate Probability Distributions: Decreasingly Naive Bayesian Classification Geoffrey I. Webb, Janice R. Boughton, Fei Zheng, Kai Ming Ting, Houssam Salem

MLJ 2012 Subsumption Resolution: An Efficient and Effective Technique for Semi-Naive Bayesian Learning Fei Zheng, Geoffrey I. Webb, Pramuditha Suraweera, Liguang Zhu

MLJ 2011 Feature-Subspace Aggregating: Ensembles for Stable and Unstable Learners Kai Ming Ting, Jonathan R. Wells, Swee Chuan Tan, Shyh Wei Teng, Geoffrey I. Webb

MLJ 2009 Anytime Classification for a Pool of Instances Bei Hui, Ying Yang, Geoffrey I. Webb

MLJ 2009 Discretization for Naive-Bayes Learning: Managing Discretization Bias and Variance Ying Yang, Geoffrey I. Webb

JMLR 2009 Supervised Descriptive Rule Discovery: A Unifying Survey of Contrast Set, Emerging Pattern and Subgroup Mining Petra Kralj Novak, Nada Lavrač, Geoffrey I. Webb

MLJ 2008 Discovering Significant Patterns Geoffrey I. Webb

MLJ 2008 Layered Critical Values: A Powerful Direct-Adjustment Approach to Discovering Significant Patterns Geoffrey I. Webb

MLJ 2007 Classifying Under Computational Resource Constraints: Anytime Classification Using Probabilistic Estimators Ying Yang, Geoffrey I. Webb, Kevin B. Korb, Kai Ming Ting

MLJ 2007 Discovering Significant Patterns Geoffrey I. Webb

ICML 2006 Efficient Lazy Elimination for Averaged One-Dependence Estimators Fei Zheng, Geoffrey I. Webb

ECML-PKDD 2006 To Select or to Weigh: A Comparative Study of Model Selection and Model Weighing for SPODE Ensembles Ying Yang, Geoffrey I. Webb, Jesús Cerquides, Kevin B. Korb, Janice R. Boughton, Kai Ming Ting

MLJ 2005 Not so Naive Bayes: Aggregating One-Dependence Estimators Geoffrey I. Webb, Janice R. Boughton, Zhihai Wang

MLJ 2005 On the Application of ROC Analysis to Predict Classification Performance Under Varying Class Distributions Geoffrey I. Webb, Kai Ming Ting

ICML 2002 Non-Disjoint Discretization for Naive-Bayes Classifiers Ying Yang, Geoffrey I. Webb

ECML-PKDD 2001 Proportional K-Interval Discretization for Naive-Bayes Classifiers Ying Yang, Geoffrey I. Webb

MLJ 2000 Lazy Learning of Bayesian Rules Zijian Zheng, Geoffrey I. Webb

MLJ 2000 MultiBoosting: A Technique for Combining Boosting and Wagging Geoffrey I. Webb

MLJ 1999 An Experimental Evaluation of Integrating Machine Learning with Knowledge Acquisition Geoffrey I. Webb, Jason Wells, Zijian Zheng

IJCAI 1999 Decision Tree Grafting from the All Tests but One Partition Geoffrey I. Webb

ICML 1999 Lazy Bayesian Rules: A Lazy Semi-Naive Bayesian Learning Technique Competitive to Boosting Decision Trees Zijian Zheng, Geoffrey I. Webb, Kai Ming Ting

ECML-PKDD 1998 Classification Learning Using All Rules Murlikrishna Viswanathan, Geoffrey I. Webb

IJCAI 1997 Decision Tree Grafting Geoffrey I. Webb

JAIR 1996 Further Experimental Evidence Against the Utility of Occam's Razor Geoffrey I. Webb

JAIR 1995 OPUS: An Efficient Admissible Algorithm for Unordered Search Geoffrey I. Webb