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Geoffrey I. Webb Vis

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*2009
77EEKai Ming Ting, Jonathan R. Wells, Swee Chuan Tan, Shyh Wei Teng, Geoffrey I. Webb: FaSS: Ensembles for Stable Learners. MCS 2009: 364-374
76EEBin Liu, Ying Yang, Geoffrey I. Webb, Janice R. Boughton: A Comparative Study of Bandwidth Choice in Kernel Density Estimation for Naive Bayesian Classification. PAKDD 2009: 302-313
2008
75 Geoffrey I. Webb: Multi-Strategy Ensemble Learning, Ensembles of Bayesian Classifiers, and the Problem of False Discoveries. AusDM 2008: 15
74EEGeoffrey I. Webb: Discovering significant patterns. Machine Learning 71(1): 131 (2008)
73EEGeoffrey I. Webb: Layered critical values: a powerful direct-adjustment approach to discovering significant patterns. Machine Learning 71(2-3): 307-323 (2008)
2007
72EEFei Zheng, Geoffrey I. Webb: Finding the Right Family: Parent and Child Selection for Averaged One-Dependence Estimators. ECML 2007: 490-501
71EEGeoffrey I. Webb: Finding the Real Patterns. PAKDD 2007: 6
70EEGeoffrey I. Webb: Editorial. Data Min. Knowl. Discov. 15(1): 1-2 (2007)
69EEYing Yang, Geoffrey I. Webb, Jesús Cerquides, Kevin B. Korb, Janice R. Boughton, Kai Ming Ting: To Select or To Weigh: A Comparative Study of Linear Combination Schemes for SuperParent-One-Dependence Estimators. IEEE Trans. Knowl. Data Eng. 19(12): 1652-1665 (2007)
68EEGeoffrey I. Webb: Discovering Significant Patterns. Machine Learning 68(1): 1-33 (2007)
67EEYing Yang, Geoffrey I. Webb, Kevin B. Korb, Kai Ming Ting: Classifying under computational resource constraints: anytime classification using probabilistic estimators. Machine Learning 69(1): 35-53 (2007)
2006
66 Qiang Yang, Geoffrey I. Webb: PRICAI 2006: Trends in Artificial Intelligence, 9th Pacific Rim International Conference on Artificial Intelligence, Guilin, China, August 7-11, 2006, Proceedings Springer 2006
65EEJingli Lu, Ying Yang, Geoffrey I. Webb: Incremental Discretization for Naïve-Bayes Classifier. ADMA 2006: 223-238
64 Geoffrey I. Webb: Anytime learning and classification for online applications. AMT 2006: 7-12
63EEYing Yang, Geoffrey I. Webb, Jesús Cerquides, Kevin B. Korb, Janice R. Boughton, Kai Ming Ting: To Select or To Weigh: A Comparative Study of Model Selection and Model Weighing for SPODE Ensembles. ECML 2006: 533-544
62EEFei Zheng, Geoffrey I. Webb: Efficient lazy elimination for averaged one-dependence estimators. ICML 2006: 1113-1120
61EEGeoffrey I. Webb: Discovering significant rules. KDD 2006: 434-443
60EEGeoffrey I. Webb, Damien Brain: Generality Is Predictive of Prediction Accuracy. Selected Papers from AusDM 2006: 1-13
59EEShiying Huang, Geoffrey I. Webb: Efficiently Identifying Exploratory Rules' Significance. Selected Papers from AusDM 2006: 64-77
2005
58EEGeoffrey I. Webb: K-Optimal Pattern Discovery: An Efficient and Effective Approach to Exploratory Data Mining. Australian Conference on Artificial Intelligence 2005: 1-2
57EEYing Yang, Kevin B. Korb, Kai Ming Ting, Geoffrey I. Webb: Ensemble Selection for SuperParent-One-Dependence Estimators. Australian Conference on Artificial Intelligence 2005: 102-112
56EEShiying Huang, Geoffrey I. Webb: Pruning Derivative Partial Rules During Impact Rule Discovery. PAKDD 2005: 71-80
55 Shiying Huang, Geoffrey I. Webb: Discarding Insignificant Rules during Impact Rule Discovery in Large, Dense Databases. SDM 2005
54 Ying Yang, Geoffrey I. Webb, Xindong Wu: Discretization Methods. The Data Mining and Knowledge Discovery Handbook 2005: 113-130
53EEGeoffrey I. Webb, Songmao Zhang: K-Optimal Rule Discovery. Data Min. Knowl. Discov. 10(1): 39-79 (2005)
52EEGeoffrey I. Webb, Kai Ming Ting: On the Application of ROC Analysis to Predict Classification Performance Under Varying Class Distributions. Machine Learning 58(1): 25-32 (2005)
51EEGeoffrey I. Webb, Janice R. Boughton, Zhihai Wang: Not So Naive Bayes: Aggregating One-Dependence Estimators. Machine Learning 58(1): 5-24 (2005)
2004
50 Geoffrey I. Webb, Xinghuo Yu: AI 2004: Advances in Artificial Intelligence, 17th Australian Joint Conference on Artificial Intelligence, Cairns, Australia, December 4-6, 2004, Proceedings Springer 2004
49EEDhananjay R. Thiruvady, Geoffrey I. Webb: Mining Negative Rules Using GRD. PAKDD 2004: 161-165
48EEZhihai Wang, Geoffrey I. Webb, Fei Zheng: Selective Augmented Bayesian Network Classifiers Based on Rough Set Theory. PAKDD 2004: 319-328
47EEGeoffrey I. Webb, Zijian Zheng: Multistrategy Ensemble Learning: Reducing Error by Combining Ensemble Learning Techniques. IEEE Trans. Knowl. Data Eng. 16(8): 980-991 (2004)
46EEHonghua Dai, Geoffrey I. Webb: Guest Editors' Introduction. International Journal of Software Engineering and Knowledge Engineering 14(4): 365-368 (2004)
2003
45EEYing Yang, Geoffrey I. Webb: On Why Discretization Works for Naive-Bayes Classifiers. Australian Conference on Artificial Intelligence 2003: 440-452
44EEZhihai Wang, Geoffrey I. Webb, Fei Zheng: Adjusting Dependence Relations for Semi-Lazy TAN Classifiers. Australian Conference on Artificial Intelligence 2003: 453-465
43EEShane M. Butler, Geoffrey I. Webb, Rob A. Lewis: A Case Study in Feature Invention for Breast Cancer Diagnosis Using X-Ray Scatter Images. Australian Conference on Artificial Intelligence 2003: 677-685
42EEGeoffrey I. Webb, Shane M. Butler, Douglas A. Newlands: On detecting differences between groups. KDD 2003: 256-265
41EEHongbo Shi, Zhihai Wang, Geoffrey I. Webb, Houkuan Huang: A New Restricted Bayesian Network Classifier. PAKDD 2003: 265-270
40EEYing Yang, Geoffrey I. Webb: Weighted Proportional k-Interval Discretization for Naive-Bayes Classifiers. PAKDD 2003: 501-512
39 Chengqi Zhang, Shichao Zhang, Geoffrey I. Webb: Identifying Approximate Itemsets of Interest in Large Databases. Appl. Intell. 18(1): 91-104 (2003)
2002
38EEYakov Frayman, Bernard F. Rolfe, Geoffrey I. Webb: Solving Regression Problems Using Competitive Ensemble Models. Australian Joint Conference on Artificial Intelligence 2002: 511-522
37EEZhihai Wang, Geoffrey I. Webb: Comparison of Lazy Bayesian Rule and Tree-Augmented Bayesian Learning. ICDM 2002: 490-497
36EEJames E. Pearce, Geoffrey I. Webb, Robin N. Shaw, Brian Garner: Experimentation and Self Learning in Continuous Database Marketing. ICDM 2002: 775-778
35 Ying Yang, Geoffrey I. Webb: Non-Disjoint Discretization for Naive-Bayes Classifiers. ICML 2002: 666-673
34EEDamien Brain, Geoffrey I. Webb: The Need for Low Bias Algorithms in Classification Learning from Large Data Sets. PKDD 2002: 62-73
2001
33EEGeoffrey I. Webb: Candidate Elimination Criteria for Lazy Bayesian Rules. Australian Joint Conference on Artificial Intelligence 2001: 545-556
32EESongmao Zhang, Geoffrey I. Webb: Further Pruning for Efficient Association Rule Discovery. Australian Joint Conference on Artificial Intelligence 2001: 605-618
31EEYing Yang, Geoffrey I. Webb: Proportional k-Interval Discretization for Naive-Bayes Classifiers. ECML 2001: 564-575
30EEGeoffrey I. Webb: Discovering associations with numeric variables. KDD 2001: 383-388
29EEGeoffrey I. Webb, Michael J. Pazzani, Daniel Billsus: Machine Learning for User Modeling. User Model. User-Adapt. Interact. 11(1-2): 19-29 (2001)
2000
28EEGeoffrey I. Webb: Efficient search for association rules. KDD 2000: 99-107
27 Geoffrey I. Webb: MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning 40(2): 159-196 (2000)
26 Zijian Zheng, Geoffrey I. Webb: Lazy Learning of Bayesian Rules. Machine Learning 41(1): 53-84 (2000)
1999
25 Zijian Zheng, Geoffrey I. Webb, Kai Ming Ting: Lazy Bayesian Rules: A Lazy Semi-Naive Bayesian Learning Technique Competitive to Boosting Decision Trees. ICML 1999: 493-502
24 Geoffrey I. Webb: Decision Tree Grafting From the All Tests But One Partition. IJCAI 1999: 702-707
23EEZijian Zheng, Geoffrey I. Webb: Stochastic Attribute Selection Committees with Aultiple Boosting: Learning More Accurate and More Stable Classifer Committees. PAKDD 1999: 123-132
22EEDouglas A. Newlands, Geoffrey I. Webb: Convex Hulls in Concept Induction. PAKDD 1999: 306-316
21 Geoffrey I. Webb, Jason Wells, Zijian Zheng: An Experimental Evaluation of Integrating Machine Learning with Knowledge Acquisition. Machine Learning 35(1): 5-23 (1999)
1998
20EEGeoffrey I. Webb: The Problem of Missing Values in Decision Tree Grafting. Australian Joint Conference on Artificial Intelligence 1998: 273-283
19EEGeoffrey I. Webb, Michael J. Pazzani: Adjusted Probability Naive Bayesian Induction. Australian Joint Conference on Artificial Intelligence 1998: 285-295
18EEZijian Zheng, Geoffrey I. Webb: Stochastic Attribute Selection Committees. Australian Joint Conference on Artificial Intelligence 1998: 321-332
17EEMurlikrishna Viswanathan, Geoffrey I. Webb: Classification Learning Using All Rules. ECML 1998: 149-159
16EEGeoffrey I. Webb, Mark Kuzmycz: Evaluation of Data Aging: A Technique for Discounting Old Data During Student Modeling. Intelligent Tutoring Systems 1998: 384-393
15EEGeoffrey I. Webb: Preface to UMUAI Special Issue on Machine Learning for User Modeling. User Model. User-Adapt. Interact. 8(1-2): 1-3 (1998)
14EEBark Cheung Chiu, Geoffrey I. Webb: Using Decision Trees for Agent Modeling: Improving Prediction Performance. User Model. User-Adapt. Interact. 8(1-2): 131-152 (1998)
1997
13EEBark Cheung Chiu, Geoffrey I. Webb, Zijian Zheng: Using Decision Trees for Agent Modelling: A Study on Resolving Confliction Predictions. Australian Joint Conference on Artificial Intelligence 1997: 349-358
12 Geoffrey I. Webb: Decision Tree Grafting. IJCAI (2) 1997: 846-851
1996
11EEGeoffrey I. Webb: Cost-Sensitive Specialization. PRICAI 1996: 23-34
10EEGeoffrey I. Webb: Further Experimental Evidence against the Utility of Occam's Razor CoRR cs.AI/9605101: (1996)
9 Geoffrey I. Webb: Further Experimental Evidence against the Utility of Occam's Razor. J. Artif. Intell. Res. (JAIR) 4: 397-417 (1996)
8EEGeoffrey I. Webb: Integrating machine learning with knowledge acquisition through direct interaction with domain experts. Knowl.-Based Syst. 9(4): 253-266 (1996)
1995
7 Philip A. Smith, Geoffrey I. Webb: Transparency Debugging with Explanations for Novice Programmers. AADEBUG 1995: 105-118
6EEDouglas A. Newlands, Geoffrey I. Webb: Polygonal Inductive Generalisation System. IEA/AIE 1995: 587-592
5 Geoffrey I. Webb: OPUS: An Efficient Admissible Algorithm for Unordered Search. J. Artif. Intell. Res. (JAIR) 3: 431-465 (1995)
4 Geoffrey I. Webb, Mark Kuzmycz: Feature Based Modelling: A Methodology for Producing Coherent, Consistent, Dynamically Changing Models of Agents' Competencies. User Model. User-Adapt. Interact. 5(2): 117-150 (1995)
1992
3 Mark Kuzmycz, Geoffrey I. Webb: Evaluation of Feature Based Modelling in Subtraction. Intelligent Tutoring Systems 1992: 269-276
1988
2EEGeoffrey I. Webb: Techniques for Efficient Empirical Induction. Australian Joint Conference on Artificial Intelligence 1988: 225-239
1 Geoffrey I. Webb: A Knowledge-Based Approach to Computer-Aided Learning. International Journal of Man-Machine Studies 29(3): 257-285 (1988)

Coauthor Index

1Daniel Billsus [29]
2Janice R. Boughton [51] [63] [69] [76]
3Damien Brain [34] [60]
4Shane M. Butler [42] [43]
5Jesús Cerquides [63] [69]
6Bark Cheung Chiu [13] [14]
7Honghua Dai [46]
8Yakov Frayman [38]
9Brian Garner [36]
10Houkuan Huang [41]
11Shiying Huang [55] [56] [59]
12Kevin B. Korb [57] [63] [67] [69]
13Mark Kuzmycz [3] [4] [16]
14Rob A. Lewis [43]
15Bin Liu [76]
16Jingli Lu [65]
17Douglas A. Newlands [6] [22] [42]
18Michael J. Pazzani [19] [29]
19James E. Pearce [36]
20Bernard F. Rolfe [38]
21Robin N. Shaw [36]
22Hongbo Shi [41]
23Philip A. Smith [7]
24Swee Chuan Tan [77]
25Shyh Wei Teng [77]
26Dhananjay R. Thiruvady [49]
27Kai Ming Ting [25] [52] [57] [63] [67] [69] [77]
28Murlikrishna Viswanathan [17]
29Zhihai Wang [37] [41] [44] [48] [51]
30Jason Wells [21]
31Jonathan R. Wells [77]
32Xindong Wu [54]
33Qiang Yang [66]
34Ying Yang [31] [35] [40] [45] [54] [57] [63] [65] [67] [69] [76]
35Xinghuo Yu [50]
36Chengqi Zhang [39]
37Shichao Zhang [39]
38Songmao Zhang [32] [53]
39Fei Zheng [44] [48] [62] [72]
40Zijian Zheng [13] [18] [21] [23] [25] [26] [47]

Colors in the list of coauthors

Copyright © Tue Nov 3 08:52:44 2009 by Michael Ley (ley@uni-trier.de)