Dennis F. Kibler

	2005
36		Bob Y. Chan, Dennis F. Kibler: Using hexamers to predict cis-regulatory motifs in Drosophila. BMC Bioinformatics 6: 262 (2005)
	2002
35		Steven Hampson, Dennis F. Kibler, Pierre Baldi: Distribution patterns of over-represented k-mers in non-coding yeast DNA. Bioinformatics 18(4): 513-528 (2002)
	2000
34		Steven Hampson, Pierre Baldi, Dennis F. Kibler, Suzanne B. Sandmeyer: Analysis of Yeast's ORF Upstream Regions by Parallel Processing, Microarrays, and Computational Methods. ISMB 2000: 190-201
33		Yuh-Jyh Hu, Suzanne B. Sandmeyer, Calvin McLaughlin, Dennis F. Kibler: Combinatorial motif analysis and hypothesis generation on a genomic scale. Bioinformatics 16(3): 222-232 (2000)
32		Stephen D. Bay, Dennis F. Kibler, Michael J. Pazzani, Padhraic Smyth: The UCI KDD Archive of Large Data Sets for Data Mining Research and Experimentation. SIGKDD Explorations 2(2): 81-85 (2000)
	1999
31		Yuh-Jyh Hu, Suzanne B. Sandmeyer, Dennis F. Kibler: Detecting Motifs from Sequences. ICML 1999: 181-190
30		Dennis F. Kibler: Paul R. Cohen's Empirical Methods for Artificial Intelligence. Artif. Intell. 113(1-2): 281-284 (1999)
29		Steven Hampson, Dennis F. Kibler: Minimum Generalization Via Reflection: A Fast Linear Threshold Learner. Machine Learning 37(1): 51-73 (1999)
	1998
28		Dennis F. Kibler: A Review of Machine Learning. AI Magazine 19(1): 136 (1998)
	1997
27		Piew Datta, Dennis F. Kibler: Symbolic Nearest Mean Classifiers. AAAI/IAAI 1997: 82-87
26		Piew Datta, Dennis F. Kibler: Learning Symbolic Prototypes. ICML 1997: 75-82
	1996
25		Yuh-Jyh Hu, Dennis F. Kibler: Generation of Attributes for Learning Algorithms. AAAI/IAAI, Vol. 1 1996: 806-811
	1995
24		Piew Datta, Dennis F. Kibler: Learning Prototypical Concept Descriptions. ICML 1995: 158-166
	1993
23		Piew Datta, Dennis F. Kibler: Concept Sharing: A Means to Improve Multi-Concept Learning. ICML 1993: 89-96
22		David Ruby, Dennis F. Kibler: Learning Steppingstones for Problem Solving. IJPRAI 7(3): 527-540 (1993)
	1992
21		David Ruby, Dennis F. Kibler: Learning Episodes for Optimization. ML 1992: 379-384
20		Michael J. Pazzani, Dennis F. Kibler: The Utility of Knowledge in Inductive Learning. Machine Learning 9: 57-94 (1992)
	1991
19		David Ruby, Dennis F. Kibler: SteppingStone: An Empirical and Analytical Evaluation. AAAI 1991: 527-532
18		David W. Aha, Dennis F. Kibler, Marc K. Albert: Instance-Based Learning Algorithms. Machine Learning 6: 37-66 (1991)
	1989
17		David Ruby, Dennis F. Kibler: Learning Subgoal Sequences for Planning. IJCAI 1989: 609-614
16		David W. Aha, Dennis F. Kibler: Noise-Tolerant Instance-Based Learning Algorithms. IJCAI 1989: 794-799
15		David Rudy, Dennis F. Kibler: Learning to Plan in Complex Domains. ML 1989: 180-182
14		Dennis F. Kibler, David W. Aha, Marc K. Albert: Instance-based prediction of real-valued attributes. Computational Intelligence 5: 51-57 (1989)
	1988
13		Dennis F. Kibler, David W. Aha: Comparing Instance-Averaging with Instance-Filtering Learning Algorithms. EWSL 1988: 63-79
12		Dennis F. Kibler, Pat Langley: Machine Learning as an Experimental Science. EWSL 1988: 81-92
	1987
11		Dennis F. Kibler: The Qualitative Character of Intelligence. ICDE 1987: 289-290
	1986
10		Bruce W. Porter, Dennis F. Kibler: Experimental Goal Regression: A Method for Learning Problem-Solving Heuristics. Machine Learning 1(3): 249-286 (1986)
	1985
9		Dennis F. Kibler, John S. Conery: Parallelism in AI Programs. IJCAI 1985: 53-56
8		Bruce W. Porter, Dennis F. Kibler: A Comparison of Analytic and Experimental Goal Regression for Machine Learning. IJCAI 1985: 555-559
7		Rogers P. Hall, Dennis F. Kibler: Differing Methodological Perspectives in Artificial Intelligence. AI Magazine 6(3): 166-178 (1985)
6		John S. Conery, Dennis F. Kibler: AND Parallelism and Nondeterminism in Logic Programs. New Generation Comput. 3(1): 43-70 (1985)
	1984
5		Bruce W. Porter, Dennis F. Kibler: Learning Operator Transformations. AAAI 1984: 278-282
	1983
4		Dennis F. Kibler, Bruce W. Porter: Episodic Learning. AAAI 1983: 191-196
3		Dennis F. Kibler, Bruce W. Porter: Perturbation: A Means for Guiding Generalization. IJCAI 1983: 415-418
2		John S. Conery, Dennis F. Kibler: AND Parallelism in Logic Programs. IJCAI 1983: 539-543
	1981
1		Dennis F. Kibler, Paul Morris: Don't Be Stupid. IJCAI 1981: 345-347

Coauthor Index

1	David W. Aha	[13] [14] [16] [18]
2	Marc K. Albert	[14] [18]
3	Pierre Baldi	[34] [35]
4	Stephen D. Bay	[32]
5	Bob Y. Chan	[36]
6	John S. Conery	[2] [6] [9]
7	Piew Datta	[23] [24] [26] [27]
8	Rogers P. Hall	[7]
9	Steven E. Hampson (Steven Hampson)	[29] [34] [35]
10	Yuh-Jyh Hu	[25] [31] [33]
11	Pat Langley	[12]
12	Calvin McLaughlin	[33]
13	Paul Morris	[1]
14	Michael J. Pazzani	[20] [32]
15	Bruce W. Porter	[3] [4] [5] [8] [10]
16	David Ruby	[17] [19] [21] [22]
17	David Rudy	[15]
18	Suzanne B. Sandmeyer	[31] [33] [34]
19	Padhraic Smyth	[32]

Colors in the list of coauthors

Last update Sun Feb 12 22:50:56 2012 CET by the DBLP Team — Data released under the ODC-BY 1.0 license — See also our legal information page