Rich Caruana

2008
44	EE	Engin Ipek, Sally A. McKee, Karan Singh, Rich Caruana, Bronis R. de Supinski, Martin Schulz: Efficient architectural design space exploration via predictive modeling. TACO 4(4): (2008)
2007
43		Pavel Berkhin, Rich Caruana, Xindong Wu: Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Jose, California, USA, August 12-15, 2007 ACM 2007
42	EE	David B. Skalak, Alexandru Niculescu-Mizil, Rich Caruana: Classifier Loss Under Metric Uncertainty. ECML 2007: 310-322
41	EE	Daria Sorokina, Rich Caruana, Mirek Riedewald: Additive Groves of Regression Trees. ECML 2007: 323-334
40	EE	Nam Nguyen, Rich Caruana: Consensus Clusterings. ICDM 2007: 607-612
39	EE	Karan Singh, Engin Ipek, Sally A. McKee, Bronis R. de Supinski, Martin Schulz, Rich Caruana: Predicting parallel application performance via machine learning approaches. Concurrency and Computation: Practice and Experience 19(17): 2219-2235 (2007)
2006
38	EE	Engin Ipek, Sally A. McKee, Rich Caruana, Bronis R. de Supinski, Martin Schulz: Efficiently exploring architectural design spaces via predictive modeling. ASPLOS 2006: 195-206
37	EE	Rich Caruana, Mohamed Farid Elhawary, Nam Nguyen, Casey Smith: Meta Clustering. ICDM 2006: 107-118
36	EE	Rich Caruana, Art Munson, Alexandru Niculescu-Mizil: Getting the Most Out of Ensemble Selection. ICDM 2006: 828-833
35	EE	Rich Caruana, Alexandru Niculescu-Mizil: An empirical comparison of supervised learning algorithms. ICML 2006: 161-168
34	EE	Cristian Bucila, Rich Caruana, Alexandru Niculescu-Mizil: Model compression. KDD 2006: 535-541
33	EE	Rich Caruana, Mohamed Farid Elhawary, Art Munson, Mirek Riedewald, Daria Sorokina, Daniel Fink, Wesley M. Hochachka, Steve Kelling: Mining citizen science data to predict orevalence of wild bird species. KDD 2006: 909-915
2005
32	EE	Art Munson, Claire Cardie, Rich Caruana: Optimizing to Arbitrary NLP Metrics using Ensemble Selection. HLT/EMNLP 2005
31	EE	Alexandru Niculescu-Mizil, Rich Caruana: Predicting good probabilities with supervised learning. ICML 2005: 625-632
30	EE	Alexandru Niculescu-Mizil, Rich Caruana: Obtaining Calibrated Probabilities from Boosting. UAI 2005: 413-
29	EE	Gregory F. Cooper, Vijoy Abraham, Constantin F. Aliferis, John M. Aronis, Bruce G. Buchanan, Rich Caruana, Michael J. Fine, Janine E. Janosky, Gary Livingston, Tom M. Mitchell: Predicting dire outcomes of patients with community acquired pneumonia. Journal of Biomedical Informatics 38(5): 347-366 (2005)
2004
28	EE	Rich Caruana, Alexandru Niculescu-Mizil, Geoff Crew, Alex Ksikes: Ensemble selection from libraries of models. ICML 2004
27	EE	Rich Caruana, Alexandru Niculescu-Mizil: Data mining in metric space: an empirical analysis of supervised learning performance criteria. KDD 2004: 69-78
26		Rich Caruana, Alexandru Niculescu-Mizil: An Empirical Evaluation of Supervised Learning for ROC Area. ROCAI 2004: 1-8
25		Rich Caruana, Alexandru Niculescu-Mizil: Data Mining in Metric Space: An Empirical Analysis of Supervised Learning Performance Criteria. ROCAI 2004: 9-18
24	EE	Rich Caruana, Thorsten Joachims, Lars Backstrom: KDD-Cup 2004: results and analysis. SIGKDD Explorations 6(2): 95-108 (2004)
2003
23	EE	Rich Caruana, Virginia R. de Sa: Benefitting from the Variables that Variable Selection Discards. Journal of Machine Learning Research 3: 1245-1264 (2003)
2001
22	EE	John Langford, Rich Caruana: (Not) Bounding the True Error. NIPS 2001: 809-816
2000
21		Joseph O'Sullivan, John Langford, Rich Caruana, Avrim Blum: FeatureBoost: A Meta-Learning Algorithm that Improves Model Robustness. ICML 2000: 703-710
20		Rich Caruana, Steve Lawrence, C. Lee Giles: Overfitting in Neural Nets: Backpropagation, Conjugate Gradient, and Early Stopping. NIPS 2000: 402-408
19	EE	Adam L. Berger, Rich Caruana, David Cohn, Dayne Freitag, Vibhu O. Mittal: Bridging the lexical chasm: statistical approaches to answer-finding. SIGIR 2000: 192-199
1997
18		Gregory F. Cooper, Constantin F. Aliferis, R. Ambrosino, John M. Aronis, Bruce G. Buchanan, Rich Caruana, Michael J. Fine, Clark Glymour, G. Gordon, B. H. Hanusa, Janine E. Janosky, Christopher Meek, Tom M. Mitchell, Thomas Richardson, Peter Spirtes: An evaluation of machine-learning methods for predicting pneumonia mortality. Artificial Intelligence in Medicine 9(2): 107-138 (1997)
17		Rich Caruana: Multitask Learning. Machine Learning 28(1): 41-75 (1997)
1996
16		Rich Caruana: Algorithms and Applications for Multitask Learning. ICML 1996: 87-95
15	EE	Rich Caruana, Virginia R. de Sa: Promoting Poor Features to Supervisors: Some Inputs Work Better as Outputs. NIPS 1996: 389-395
14	EE	Rich Caruana: A Dozen Tricks with Multitask Learning. Neural Networks: Tricks of the Trade 1996: 165-191
1995
13		Shumeet Baluja, Rich Caruana: Removing the Genetics from the Standard Genetic Algorithm. ICML 1995: 38-46
12	EE	Rich Caruana, Shumeet Baluja, Tom M. Mitchell: Using the Future to Sort Out the Present: Rankprop and Multitask Learning for Medical Risk Evaluation. NIPS 1995: 959-965
1994
11		Rich Caruana, Dayne Freitag: Greedy Attribute Selection. ICML 1994: 28-36
10	EE	Rich Caruana: Learning Many Related Tasks at the Same Time with Backpropagation. NIPS 1994: 657-664
9		Tom M. Mitchell, Rich Caruana, Dayne Freitag, John P. McDermott, David Zabowski: Experience with a Learning Personal Assistant. Commun. ACM 37(7): 80-91 (1994)
1993
8		Rich Caruana: Multitask Learning: A Knowledge-Based Source of Inductive Bias. ICML 1993: 41-48
1989
7		Larry J. Eshelman, Rich Caruana, J. David Schaffer: Biases in the Crossover Landscape. ICGA 1989: 10-19
6		J. David Schaffer, Rich Caruana, Larry J. Eshelman, Rajarshi Das: A Study of Control Parameters Affecting Online Performance of Genetic Algorithms for Function Optimization. ICGA 1989: 51-60
5		Rich Caruana, Larry J. Eshelman, J. David Schaffer: Representation and Hidden Bias II: Eliminating Defining Length Bias in Genetic Search via Shuffle Crossover. IJCAI 1989: 750-755
4		Rich Caruana, J. David Schaffer, Larry J. Eshelman: Using Multiple Representations to Improve Inductive Bias: Gray and Binary Coding for Genetic Algorithms. ML 1989: 375-378
1988
3		Rich Caruana, J. David Schaffer: Representation and Hidden Bias: Gray vs. Binary Coding for Genetic Algorithms. ML 1988: 153-161
2		Rich Caruana: The automatic training of rule bases that use numerical uncertainty representations. Int. J. Approx. Reasoning 2(3): 330-331 (1988)
1987
1	EE	Rich Caruana: The Automatic Training of Rule Bases that Use Numerical Uncertainty Representations. UAI 1987: 347-356

Coauthor Index

1	Vijoy Abraham	[29]
2	Constantin F. Aliferis	[18] [29]
3	R. Ambrosino	[18]
4	John M. Aronis	[18] [29]
5	Lars Backstrom	[24]
6	Shumeet Baluja	[12] [13]
7	Adam L. Berger	[19]
8	Pavel Berkhin	[43]
9	Avrim Blum	[21]
10	Bruce G. Buchanan	[18] [29]
11	Cristian Bucila	[34]
12	Claire Cardie	[32]
13	David Cohn	[19]
14	Gregory F. Cooper	[18] [29]
15	Geoff Crew	[28]
16	Rajarshi Das	[6]
17	Mohamed Farid Elhawary	[33] [37]
18	Larry J. Eshelman	[4] [5] [6] [7]
19	Michael J. Fine	[18] [29]
20	Daniel Fink	[33]
21	Dayne Freitag	[9] [11] [19]
22	C. Lee Giles (Clyde Lee Giles)	[20]
23	Clark Glymour	[18]
24	G. Gordon	[18]
25	B. H. Hanusa	[18]
26	Wesley M. Hochachka	[33]
27	Engin Ipek	[38] [39] [44]
28	Janine E. Janosky	[18] [29]
29	Thorsten Joachims	[24]
30	Steve Kelling	[33]
31	Alex Ksikes	[28]
32	John Langford	[21] [22]
33	Steve Lawrence	[20]
34	Gary Livingston	[29]
35	John P. McDermott	[9]
36	Sally A. McKee	[38] [39] [44]
37	Christopher Meek	[18]
38	Tom M. Mitchell	[9] [12] [18] [29]
39	Vibhu O. Mittal	[19]
40	Art Munson	[32] [33] [36]
41	Nam Nguyen	[37] [40]
42	Alexandru Niculescu-Mizil	[25] [26] [27] [28] [30] [31] [34] [35] [36] [42]
43	Joseph O'Sullivan	[21]
44	Thomas Richardson	[18]
45	Mirek Riedewald	[33] [41]
46	Virginia R. de Sa	[15] [23]
47	J. David Schaffer	[3] [4] [5] [6] [7]
48	Martin Schulz	[38] [39] [44]
49	Karan Singh	[39] [44]
50	David B. Skalak	[42]
51	Casey Smith	[37]
52	Daria Sorokina	[33] [41]
53	Peter Spirtes	[18]
54	Bronis R. de Supinski	[38] [39] [44]
55	Xindong Wu	[43]
56	David Zabowski	[9]

Colors in the list of coauthors