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Note: Links lead to the DBLP on the Web. Charles X. Ling Shengli Sheng , Charles X. Ling, Qiang Yang : Simple Test Strategies for Cost-Sensitive Decision Trees. ECML 2005 : 365-376 Jin Huang , Charles X. Ling: Partial Ensemble Classifiers Selection for Better Ranking. ICDM 2005 : 653-656 Charles X. Ling, Shengli Sheng , Tilmann F. W. Bruckhaus , Nazim H. Madhavji : Predicting Software Escalations with Maximum ROI. ICDM 2005 : 717-720 Shengli Sheng , Charles X. Ling: Hybrid Cost-Sensitive Decision Tree. PKDD 2005 : 274-284 Jin Huang , Charles X. Ling: Rank Measures for Ordering. PKDD 2005 : 503-510 Jin Huang , Charles X. Ling: Dynamic Ensemble Re-Construction for Better Ranking. PKDD 2005 : 511-518 Dequan Li , Yan Fu , Ruixiang Sun , Charles X. Ling, Yonggang Wei , Hu Zhou , Rong Zeng , Qiang Yang , Simin He , Wen Gao : pFind: a novel database-searching software system for automated peptide and protein identification via tandem mass spectrometry. Bioinformatics 21 (13): 3049-3050 (2005) Shichao Zhang , Zhenxing Qin , Charles X. Ling, Shengli Sheng : "Missing Is Useful': Missing Values in Cost-Sensitive Decision Trees. IEEE Trans. Knowl. Data Eng. 17 (12): 1689-1693 (2005) Jin Huang , Charles X. Ling: Using AUC and Accuracy in Evaluating Learning Algorithms - Appendices. IEEE Trans. Knowl. Data Eng. 17 (3): (2005) Jin Huang , Charles X. Ling: Using AUC and Accuracy in Evaluating Learning Algorithms. IEEE Trans. Knowl. Data Eng. 17 (3): 299-310 (2005) Charles X. Ling, William Stafford Noble , Qiang Yang : Guest Editors' Introduction to the Special Issue: Machine Learning for Bioinformatics - Part 1. IEEE/ACM Trans. Comput. Biology Bioinform. 2 (2): 81-82 (2005) Charles X. Ling, William Stafford Noble , Qiang Yang : Guest Editor's Introduction to the Special Issue: Machine Learning for Bioinformatics-Part 2. IEEE/ACM Trans. Comput. Biology Bioinform. 2 (3): 177-178 (2005) Jinhua Zheng , Charles X. Ling, Zhongzhi Shi , Juan Xue , Xuyong Li : A Multi-objective Genetic Algorithm Based on Quick Sort. Canadian Conference on AI 2004 : 175-186 Jianning Wang , Charles X. Ling: Artificial Aging of Faces by Support Vector Machines. Canadian Conference on AI 2004 : 499-503 Xiaoyong Chai , Lin Deng , Qiang Yang , Charles X. Ling: Test-Cost Sensitive Naive Bayes Classification. ICDM 2004 : 51-58 Charles X. Ling, Qiang Yang , Jianning Wang , Shichao Zhang : Decision trees with minimal costs. ICML 2004 Jinhua Zheng , Zhongzhi Shi , Charles X. Ling, Yong Xie : A New Method to Construct the Non-Dominated Set in Multi-Objective Genetic Algorithms. Intelligent Information Processing 2004 : 456-470 Yan Fu , Qiang Yang , Charles X. Ling, Haipeng Wang , Dequan Li , Ruixiang Sun , Hu Zhou , Rong Zeng , Yiqiang Chen , Simin He , Wen Gao : A Kernel-Based Case Retrieval Algorithm with Application to Bioinformatics. PRICAI 2004 : 544-553 Yan Fu , Qiang Yang , Ruixiang Sun , Dequan Li , Rong Zeng , Charles X. Ling, Wen Gao : Exploiting the kernel trick to correlate fragment ions for peptide identification via tandem mass spectrometry. Bioinformatics 20 (12): 1948-1954 (2004) Charles X. Ling, Jin Huang , Harry Zhang : AUC: A Better Measure than Accuracy in Comparing Learning Algorithms. Canadian Conference on AI 2003 : 329-341 Harry Zhang , Charles X. Ling: A Fundamental Issue of Naive Bayes. Canadian Conference on AI 2003 : 591-595 Jin Huang , Jingjing Lu , Charles X. Ling: Comparing Naive Bayes, Decision Trees, and SVM with AUC and Accuracy. ICDM 2003 : 553-556 Qiang Yang , Jie Yin , Charles X. Ling, Tielin Chen : Postprocessing Decision Trees to Extract Actionable Knowledge. ICDM 2003 : 685-688 Charles X. Ling, Robert J. Yan : Decision Tree with Better Ranking. ICML 2003 : 480-487 Charles X. Ling, Jin Huang , Harry Zhang : AUC: a Statistically Consistent and more Discriminating Measure than Accuracy. IJCAI 2003 : 519-526 Yiqiang Chen , Wen Gao , Lijuan Duan , Xiang Chen , Charles X. Ling: Intelligent Protein 3D Structure Retrieval System. ISMIS 2003 : 108-115 Harry Zhang , Charles X. Ling: Numeric Mapping and Learnability of Naive Bayes. Applied Artificial Intelligence 17 (5-6): 507-518 (2003) Charles X. Ling, Tielin Chen , Qiang Yang , Jie Cheng : Mining Optimal Actions for Profitable CRM. ICDM 2002 : 767-770 Huajie Zhang , Charles X. Ling: Representational Upper Bounds of Bayesian Networks. ICML 2002 : 674-681 Charles X. Ling, Huajie Zhang : Toward Bayesian Classifiers with Accurate Probabilities. PAKDD 2002 : 123-134 Charles X. Ling, Jianfeng Gao , Huajie Zhang , Weining Qian , HongJiang Zhang : Improving Encarta Search Engine Performance by Mining User Logs. IJPRAI 16 (8): 1101-1116 (2002) Charles X. Ling, Nick Cercone : Editorial Notes. Int. J. Found. Comput. Sci. 13 (4): 473-475 (2002) Yiqiang Chen , Wen Gao , Tingshao Zhu , Charles X. Ling: Learning Prosodic Patterns for Mandarin Speech Synthesis. J. Intell. Inf. Syst. 19 (1): 95-109 (2002) Charles X. Ling, Huajie Zhang : The Representational Power of Discrete Bayesian Networks. Journal of Machine Learning Research 3 : 709-721 (2002) Wai Lam , Chi-Kin Keung , Charles X. Ling: Learning good prototypes for classification using filtering and abstraction of instances. Pattern Recognition 35 (7): 1491-1506 (2002) Huajie Zhang , Charles X. Ling: Geometric Properties of Naive Bayes in Nominal Domains. ECML 2001 : 588-599 Charles X. Ling, Jianfeng Gao , Huajie Zhang , Weining Qian , HongJiang Zhang : Mining Generalized Query Patterns from Web Logs. HICSS 2001 Huajie Zhang , Charles X. Ling: Learnability of Augmented Naive Bayes in Nonimal Domains. ICML 2001 : 617-623 Huajie Zhang , Charles X. Ling: An Improved Learning Algorithm for Augmented Naive Bayes. PAKDD 2001 : 581-586 Huajie Zhang , Charles X. Ling, Zhiduo Zhao : The Learnability of Naive Bayes. Canadian Conference on AI 2000 : 432-441 Charles X. Ling, Bei Zhang : Grapheme Generation in Learning to Read English Words. Canadian Conference on AI 1998 : 184-195 Charles X. Ling, Chenghui Li : Data Mining for Direct Marketing: Problems and Solutions. KDD 1998 : 73-79 Ron Sun , Charles X. Ling: Computational Cognitive Modeling, the Source of Power, and Other Related Issues. AI Magazine 19 (2): 113-120 (1998) Charles X. Ling, Handong Wang : Alignment Algorithms for Learning to Read Aloud. IJCAI (2) 1997 : 874-879 Charles X. Ling, Hangdong Wang : Computing Optimal Attribute Weight Settings for Nearest Neighbor Algorithms. Artif. Intell. Rev. 11 (1-5): 255-272 (1997) Charles X. Ling, John J. Parry , Hangdong Wang : Setting Attribute Weights for Nearest Neighour Learning Algorithms Using C4.5. IJPRAI 11 (3): 405-415 (1997) Charles X. Ling, Handong Wang : Learning Classifications from Multiple Sources of Unsupervised Data. Canadian Conference on AI 1996 : 284-295 William C. Schmidt , Charles X. Ling: A Decision-Tree Model of Balance Scale Development. Machine Learning 24 (3): 203-230 (1996) Charles X. Ling: Overfitting and generalization in learning discrete patterns. Neurocomputing 8 (3): 341-347 (1995) David W. Aha , Stephane Lapointe , Charles X. Ling, Stan Matwin : Inverting Implication with Small Training Sets. ECML 1994 : 31-48 David W. Aha , Stephane Lapointe , Charles X. Ling, Stan Matwin : Learning Recursive Relations with Randomly Selected Small Training Sets. ICML 1994 : 12-18 Charles X. Ling: Learning the Past Tense of English Verbs: The Symbolic Pattern Associator vs. Connectionist Models CoRR cs.AI/9402101 : (1994) Charles X. Ling, Marin Marinov : A Symbolic Model of the Nonconscious Acquisition of Information. Cognitive Science 18 (4): 595-621 (1994) Charles X. Ling: Learning the Past Tense of English Verbs: The Symbolic Pattern Associator vs. Connectionist Models. J. Artif. Intell. Res. (JAIR) 1 : 209-229 (1994) Charles X. Ling, Ralph Buchal : Learning to Control Dynamic Systems with Automatic Quantization. ECML 1993 : 372-377 Stephane Lapointe , Charles X. Ling, Stan Matwin : Constructive Inductive Logic Programming. IJCAI 1993 : 1030-1036 Charles X. Ling, Steven Cherwenka , Marin Marinov : A Symbolic Model for Learning the Past-Tenses of English Verbs. IJCAI 1993 : 1143-1149 Charles X. Ling: Inductive Learning from Good Examples. IJCAI 1991 : 751-756 1 [ 8 ] [ 9 ] 2 [ 56 ] 3 [ 4 ] 4 [ 27 ] 5 [ 44 ] 6 [ 31 ] [ 36 ] 7 [ 33 ] 8 [ 26 ] [ 33 ] [ 41 ] 9 [ 31 ] 10 [ 2 ] 11 [ 44 ] 12 [ 33 ] 13 [ 40 ] [ 41 ] [ 52 ] 14 [ 22 ] [ 28 ] 15 [ 26 ] [ 33 ] [ 40 ] [ 41 ] [ 52 ] 16 [ 41 ] [ 52 ] 17 [ 34 ] [ 37 ] [ 39 ] [ 49 ] [ 50 ] [ 53 ] [ 54 ] [ 57 ] 18 [ 24 ] 19 [ 24 ] 20 [ 3 ] [ 8 ] [ 9 ] 21 [ 17 ] 22 [ 40 ] [ 41 ] [ 52 ] 23 [ 46 ] 24 [ 37 ] 25 [ 56 ] 26 [ 2 ] [ 6 ] 27 [ 3 ] [ 8 ] [ 9 ] 28 [ 47 ] [ 48 ] 29 [ 13 ] 30 [ 22 ] [ 28 ] 31 [ 51 ] 32 [ 11 ] 33 [ 51 ] [ 55 ] [ 56 ] [ 58 ] 34 [ 42 ] [ 46 ] 35 [ 16 ] 36 [ 40 ] [ 41 ] [ 52 ] 37 [ 41 ] 38 [ 12 ] [ 15 ] 39 [ 13 ] [ 14 ] 40 [ 43 ] [ 45 ] 41 [ 52 ] 42 [ 42 ] 43 [ 46 ] 44 [ 35 ] 45 [ 31 ] [ 36 ] [ 40 ] [ 41 ] [ 43 ] [ 44 ] [ 47 ] [ 48 ] [ 52 ] [ 58 ] 46 [ 36 ] 47 [ 40 ] [ 41 ] [ 52 ] 48 [ 18 ] 49 [ 32 ] [ 34 ] [ 38 ] [ 39 ] 50 [ 22 ] [ 28 ] 51 [ 19 ] [ 20 ] [ 21 ] [ 22 ] [ 23 ] [ 25 ] [ 28 ] [ 29 ] [ 30 ] 52 [ 43 ] [ 51 ] 53 [ 19 ] 54 [ 42 ] [ 46 ] 55 [ 41 ] [ 52 ] 56 [ 26 ]  ©2006 Association for Computing Machinery |
