2008 |
50 | EE | Nam Nguyen,
Rich Caruana:
Improving Classification with Pairwise Constraints: A Margin-Based Approach.
ECML/PKDD (2) 2008: 113-124 |
49 | EE | Daria Sorokina,
Rich Caruana,
Mirek Riedewald,
Daniel Fink:
Detecting statistical interactions with additive groves of trees.
ICML 2008: 1000-1007 |
48 | EE | Rich Caruana,
Nikolaos Karampatziakis,
Ainur Yessenalina:
An empirical evaluation of supervised learning in high dimensions.
ICML 2008: 96-103 |
47 | EE | Engin Ipek,
Onur Mutlu,
José F. Martínez,
Rich Caruana:
Self-Optimizing Memory Controllers: A Reinforcement Learning Approach.
ISCA 2008: 39-50 |
46 | EE | Nam Nguyen,
Rich Caruana:
Classification with partial labels.
KDD 2008: 551-559 |
45 | 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 |
44 | | 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 |
43 | EE | David B. Skalak,
Alexandru Niculescu-Mizil,
Rich Caruana:
Classifier Loss Under Metric Uncertainty.
ECML 2007: 310-322 |
42 | EE | Daria Sorokina,
Rich Caruana,
Mirek Riedewald:
Additive Groves of Regression Trees.
ECML 2007: 323-334 |
41 | EE | Nam Nguyen,
Rich Caruana:
Consensus Clusterings.
ICDM 2007: 607-612 |
40 | 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 |
39 | 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 |
38 | EE | Rich Caruana,
Mohamed Farid Elhawary,
Nam Nguyen,
Casey Smith:
Meta Clustering.
ICDM 2006: 107-118 |
37 | EE | Rich Caruana,
Art Munson,
Alexandru Niculescu-Mizil:
Getting the Most Out of Ensemble Selection.
ICDM 2006: 828-833 |
36 | EE | Rich Caruana,
Alexandru Niculescu-Mizil:
An empirical comparison of supervised learning algorithms.
ICML 2006: 161-168 |
35 | EE | Lars Backstrom,
Rich Caruana:
C2FS: An Algorithm for Feature Selection in Cascade Neural Networks.
IJCNN 2006: 4748-4753 |
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 |