Charles Elkan

	2012
71		Charles Elkan, Yehuda Koren: Guest Editorial for Special Issue KDD'10. TKDD 5(4): 18 (2012)
	2011
70		Aditya Krishna Menon, Charles Elkan: Link Prediction via Matrix Factorization. ECML/PKDD (2) 2011: 437-452
69		Charles Elkan: Reinforcement Learning with a Bilinear Q Function. EWRL 2011: 78-88
68		Wenkai Li, Qinghua Guo, Charles Elkan: A Positive and Unlabeled Learning Algorithm for One-Class Classification of Remote-Sensing Data. IEEE T. Geoscience and Remote Sensing 49(2): 717-725 (2011)
67		Aditya Kumar Sehgal, Sanmay Das, Keith Noto, Milton H. Saier Jr., Charles Elkan: Identifying Relevant Data for a Biological Database: Handcrafted Rules versus Machine Learning. IEEE/ACM Trans. Comput. Biology Bioinform. 8(3): 851-857 (2011)
66		Aditya Krishna Menon, Charles Elkan: Fast Algorithms for Approximating the Singular Value Decomposition. TKDD 5(2): 13 (2011)
	2010
65		Nikolaos Trogkanis, Charles Elkan: Conditional Random Fields for Word Hyphenation. ACL 2010: 366-374
64		Aditya Krishna Menon, Charles Elkan: A Log-Linear Model with Latent Features for Dyadic Prediction. ICDM 2010: 364-373
63		Charles Elkan: Preserving Privacy in Data Mining via Importance Weighting. PSDML 2010: 15-21
62		Luigi Cerulo, Charles Elkan, Michele Ceccarelli: Learning gene regulatory networks from only positive and unlabeled data. BMC Bioinformatics 11: 228 (2010)
61		Aditya Krishna Menon, Charles Elkan: Dyadic Prediction Using a Latent Feature Log-Linear Model CoRR abs/1006.2156: (2010)
60		Padhraic Smyth, Charles Elkan: Technical perspective - Creativity helps influence prediction precision. Commun. ACM 53(4): 88 (2010)
59		Aditya Krishna Menon, Charles Elkan: Predicting labels for dyadic data. Data Min. Knowl. Discov. 21(2): 327-343 (2010)
58		Irene Rodriguez-Lujan, Ramón Huerta, Charles Elkan, Carlos Santa Cruz: Quadratic Programming Feature Selection. Journal of Machine Learning Research 11: 1491-1516 (2010)
57		Avinash Atreya, Charles Elkan: Latent semantic indexing (LSI) fails for TREC collections. SIGKDD Explorations 12(2): 5-10 (2010)
	2009
56		Gabriel Doyle, Charles Elkan: Accounting for burstiness in topic models. ICML 2009: 36
55		Milton H. Saier Jr., Ming Ren Yen, Keith Noto, Dorjee G. Tamang, Charles Elkan: The Transporter Classification Database: recent advances. Nucleic Acids Research 37(Database-Issue): 274-278 (2009)
	2008
54		Keith Noto, Milton H. Saier Jr., Charles Elkan: Learning to Find Relevant Biological Articles without Negative Training Examples. Australasian Conference on Artificial Intelligence 2008: 202-213
53		Guilherme Hoefel, Charles Elkan: Learning a two-stage SVM/CRF sequence classifier. CIKM 2008: 271-278
52		Charles Elkan, Keith Noto: Learning classifiers from only positive and unlabeled data. KDD 2008: 213-220
	2007
51		Andrew T. Smith, Charles Elkan: Making generative classifiers robust to selection bias. KDD 2007: 657-666
50		Sanmay Das, Milton H. Saier Jr., Charles Elkan: Finding Transport Proteins in a General Protein Database. PKDD 2007: 54-66
49		James Bennett, Charles Elkan, Bing Liu, Padhraic Smyth, Domonkos Tikk: KDD Cup and workshop 2007. SIGKDD Explorations 9(2): 51-52 (2007)
	2006
48		Charles Elkan: Clustering documents with an exponential-family approximation of the Dirichlet compound multinomial distribution. ICML 2006: 289-296
	2005
47		Rasmus Elsborg Madsen, David Kauchak, Charles Elkan: Modeling word burstiness using the Dirichlet distribution. ICML 2005: 545-552
46		Charles Elkan: Deriving TF-IDF as a Fisher Kernel. SPIRE 2005: 295-300
45		Douglas Turnbull, Charles Elkan: Fast Recognition of Musical Genres Using RBF Networks. IEEE Trans. Knowl. Data Eng. 17(4): 580-584 (2005)
	2004
44		Andrew T. Smith, Charles Elkan: A Bayesian network framework for reject inference. KDD 2004: 286-295
43		David Kauchak, Joseph Smarr, Charles Elkan: Sources of Success for Boosted Wrapper Induction. Journal of Machine Learning Research 5: 499-527 (2004)
	2003
42		David Kauchak, Charles Elkan: Learning Rules to Improve a Machine Translation System. ECML 2003: 205-216
41		Charles Elkan: Using the Triangle Inequality to Accelerate k-Means. ICML 2003: 147-153
40		Eric Wiewiora, Garrison W. Cottrell, Charles Elkan: Principled Methods for Advising Reinforcement Learning Agents. ICML 2003: 792-799
39		Greg Hamerly, Charles Elkan: Learning the k in k-means. NIPS 2003
	2002
38		Greg Hamerly, Charles Elkan: Alternatives to the k-means algorithm that find better clusterings. CIKM 2002: 600-607
37		Bianca Zadrozny, Charles Elkan: Transforming classifier scores into accurate multiclass probability estimates. KDD 2002: 694-699
	2001
36		Charles Elkan: Shared challenges in data mining and computational biology (abstract of invited talk). BIOKDD 2001: 44
35		Greg Hamerly, Charles Elkan: Bayesian approaches to failure prediction for disk drives. ICML 2001: 202-209
34		Bianca Zadrozny, Charles Elkan: Obtaining calibrated probability estimates from decision trees and naive Bayesian classifiers. ICML 2001: 609-616
33		Charles Elkan: The Foundations of Cost-Sensitive Learning. IJCAI 2001: 973-978
32		Bianca Zadrozny, Charles Elkan: Learning and making decisions when costs and probabilities are both unknown. KDD 2001: 204-213
31		Charles Elkan: Magical thinking in data mining: lessons from CoIL challenge 2000. KDD 2001: 426-431
30		Charles Elkan: Paradoxes of fuzzy logic, revisited. Int. J. Approx. Reasoning 26(2): 153-155 (2001)
	2000
29		Charles Elkan: Results of the KDD'99 Classifier Learning. SIGKDD Explorations 1(2): 63-64 (2000)
28		Charles Elkan: KDD'99 Knowledge Discovery Contest. SIGKDD Explorations 1(2): 78 (2000)
27		Fredrik Farnstrom, James Lewis, Charles Elkan: Scalability for Clustering Algorithms Revisited. SIGKDD Explorations 2(1): 51-57 (2000)
	1999
26		Timothy L. Bailey, Michael E. Baker, Charles Elkan, William Noble Grundy: MEME, MAST, and Meta-MEME: New Tools for Motif Discovery in Protein Sequences. Pattern Discovery in Biomolecular Data 1999: 30-54
	1997
25		Alvaro E. Monge, Charles Elkan: An Efficient Domain-Independent Algorithm for Detecting Approximately Duplicate Database Records. DMKD 1997: 0-
24		William Noble Grundy, Timothy L. Bailey, Charles Elkan, Michael E. Baker: Meta-MEME: motif-based hidden Markov models of protein families. Computer Applications in the Biosciences 13(4): 397-406 (1997)
	1996
23		Karan Bhatia, Charles Elkan: LPMEME: A Statistical Method for Inductive Logic Programming. Canadian Conference on AI 1996: 227-239
22		Charles Elkan: Reasoning about Unknown, Counterfactual, and Nondeterministic Actions in First-Order Logic. Canadian Conference on AI 1996: 54-68
21		Alvaro E. Monge, Charles Elkan: The Field Matching Problem: Algorithms and Applications. KDD 1996: 267-270
20		Alberto Maria Segre, Geoffrey J. Gordon, Charles Elkan: Exploratory Analysis of Speedup Learning Data Using Epectation Maximization. Artif. Intell. 85(1-2): 301-319 (1996)
19		William Noble Grundy, Timothy L. Bailey, Charles Elkan: ParaMEME: a parallel implementation and a web interface for a DNA and protein motif discovery tool. Computer Applications in the Biosciences 12(4): 303-310 (1996)
	1995
18		Timothy L. Bailey, Charles Elkan: The Value of Prior Knowledge in Discovering Motifs with MEME. ISMB 1995: 21-29
17		Timothy L. Bailey, Charles Elkan: Unsupervised Learning of Multiple Motifs in Biopolymers Using Expectation Maximization. Machine Learning 21(1-2): 51-80 (1995)
	1994
16		Timothy L. Bailey, Charles Elkan: Fitting a Mixture Model By Expectation Maximization To Discover Motifs In Biopolymer. ISMB 1994: 28-36
15		Alberto Maria Segre, Charles Elkan: A High-Performance Explanation-Based Learning Algorithm. Artif. Intell. 69(1-2): 1-50 (1994)
14		Charles Elkan: The Paradoxical Success of Fuzzy Logic. IEEE Expert 9(4): 3-8 (1994)
13		Charles Elkan: Elkan's Reply: The Paradoxical Controversy over Fuzzy Logic. IEEE Expert 9(4): 47-49 (1994)
	1993
12		Charles Elkan: The Paradoxical Success of Fuzzy Logic. AAAI 1993: 698-703
11		Timothy L. Bailey, Charles Elkan: Estimating the Accuracy of Learned Concepts. IJCAI 1993: 895-901
10		Charles Elkan, Russell Greiner: D. B. Lenat and R. V. Guha, Building Large Knowledge-Based Systems: Representation and Inference in the Cyc Project. Artif. Intell. 61(1): 41-52 (1993)
	1991
9		Russell Greiner, Charles Elkan: Measuring and Improving the Effectiveness of Representations. IJCAI 1991: 518-524
8		Alberto Maria Segre, Charles Elkan, Alexander Russell: A Critical Look at Experimental Evaluations of EBL. Machine Learning 6: 183-195 (1991)
	1990
7		Charles Elkan: Incremental, Approximate Planning. AAAI 1990: 145-150
6		Charles Elkan: Independence of Logic Database Queries and Updates. PODS 1990: 154-160
5		Charles Elkan: A Rational Reconstruction of Nonmonotonic Truth Maintenance Systems. Artif. Intell. 43(2): 219-234 (1990)
	1989
4		Charles Elkan: Conspiracy Numbers and Caching for Searching And/Or Trees and Theorem-Proving. IJCAI 1989: 341-348
3		Charles Elkan: Logical Characterizations of Nonmonotonic TMSs. MFCS 1989: 218-224
2		Charles Elkan: A Decision Procedure for Conjunctive Query Disjointness. PODS 1989: 134-139
	1988
1		Charles Elkan, David A. McAllester: Automated Inductive Reasoning about Logic Programs. ICLP/SLP 1988: 876-892

Coauthor Index

1	Avinash Atreya	[57]
2	Timothy L. Bailey	[11] [16] [17] [18] [19] [24] [26]
3	Michael E. Baker	[24] [26]
4	James Bennett	[49]
5	Karan Bhatia	[23]
6	Michele Ceccarelli	[62]
7	Luigi Cerulo	[62]
8	Garrison W. Cottrell	[40]
9	Carlos Santa Cruz	[58]
10	Sanmay Das	[50] [67]
11	Gabriel Doyle	[56]
12	Fredrik Farnstrom	[27]
13	Geoffrey J. Gordon	[20]
14	Russell Greiner	[9] [10]
15	William Noble Grundy	[19] [24] [26]
16	Qinghua Guo	[68]
17	Greg Hamerly	[35] [38] [39]
18	Guilherme Hoefel	[53]
19	Ramón Huerta	[58]
20	David Kauchak	[42] [43] [47]
21	Yehuda Koren	[71]
22	James Lewis	[27]
23	Wenkai Li	[68]
24	Bing Liu	[49]
25	Rasmus Elsborg Madsen	[47]
26	David A. McAllester	[1]
27	Aditya Krishna Menon	[59] [61] [64] [66] [70]
28	Alvaro E. Monge	[21] [25]
29	Keith Noto	[52] [54] [55] [67]
30	Irene Rodriguez-Lujan	[58]
31	Alexander Russell	[8]
32	Milton H. Saier Jr.	[50] [54] [55] [67]
33	Alberto Maria Segre	[8] [15] [20]
34	Aditya Kumar Sehgal	[67]
35	Joseph Smarr	[43]
36	Andrew T. Smith	[44] [51]
37	Padhraic Smyth	[49] [60]
38	Dorjee G. Tamang	[55]
39	Domonkos Tikk	[49]
40	Nikolaos Trogkanis	[65]
41	Douglas Turnbull	[45]
42	Eric Wiewiora	[40]
43	Ming Ren Yen	[55]
44	Bianca Zadrozny	[32] [34] [37]

Colors in the list of coauthors

Last update Tue May 29 20:41:18 2012 CET by the DBLP Team — Data released under the ODC-BY 1.0 license — See also our legal information page