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Rich Caruana: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Tom M. Mitchell, Rich Caruana, Dayne Freitag, John P. McDermott, David Zabowski
    Experience with a Learning Personal Assistant. [Citation Graph (1, 0)][DBLP]
    Commun. ACM, 1994, v:37, n:7, pp:80-91 [Journal]
  2. Engin Ipek, Sally A. McKee, Rich Caruana, Bronis R. de Supinski, Martin Schulz
    Efficiently exploring architectural design spaces via predictive modeling. [Citation Graph (0, 0)][DBLP]
    ASPLOS, 2006, pp:195-206 [Conf]
  3. Rich Caruana, Mohamed Farid Elhawary, Nam Nguyen, Casey Smith
    Meta Clustering. [Citation Graph (0, 0)][DBLP]
    ICDM, 2006, pp:107-118 [Conf]
  4. Rich Caruana, Art Munson, Alexandru Niculescu-Mizil
    Getting the Most Out of Ensemble Selection. [Citation Graph (0, 0)][DBLP]
    ICDM, 2006, pp:828-833 [Conf]
  5. Larry J. Eshelman, Rich Caruana, J. David Schaffer
    Biases in the Crossover Landscape. [Citation Graph (0, 0)][DBLP]
    ICGA, 1989, pp:10-19 [Conf]
  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. [Citation Graph (0, 0)][DBLP]
    ICGA, 1989, pp:51-60 [Conf]
  7. Shumeet Baluja, Rich Caruana
    Removing the Genetics from the Standard Genetic Algorithm. [Citation Graph (0, 0)][DBLP]
    ICML, 1995, pp:38-46 [Conf]
  8. Rich Caruana
    Multitask Learning: A Knowledge-Based Source of Inductive Bias. [Citation Graph (0, 0)][DBLP]
    ICML, 1993, pp:41-48 [Conf]
  9. Rich Caruana
    Algorithms and Applications for Multitask Learning. [Citation Graph (0, 0)][DBLP]
    ICML, 1996, pp:87-95 [Conf]
  10. Rich Caruana, Dayne Freitag
    Greedy Attribute Selection. [Citation Graph (0, 0)][DBLP]
    ICML, 1994, pp:28-36 [Conf]
  11. Rich Caruana, Alexandru Niculescu-Mizil
    An empirical comparison of supervised learning algorithms. [Citation Graph (0, 0)][DBLP]
    ICML, 2006, pp:161-168 [Conf]
  12. Rich Caruana, Alexandru Niculescu-Mizil, Geoff Crew, Alex Ksikes
    Ensemble selection from libraries of models. [Citation Graph (0, 0)][DBLP]
    ICML, 2004, pp:- [Conf]
  13. Rich Caruana, J. David Schaffer
    Representation and Hidden Bias: Gray vs. Binary Coding for Genetic Algorithms. [Citation Graph (0, 0)][DBLP]
    ML, 1988, pp:153-161 [Conf]
  14. Rich Caruana, J. David Schaffer, Larry J. Eshelman
    Using Multiple Representations to Improve Inductive Bias: Gray and Binary Coding for Genetic Algorithms. [Citation Graph (0, 0)][DBLP]
    ML, 1989, pp:375-378 [Conf]
  15. Joseph O'Sullivan, John Langford, Rich Caruana, Avrim Blum
    FeatureBoost: A Meta-Learning Algorithm that Improves Model Robustness. [Citation Graph (0, 0)][DBLP]
    ICML, 2000, pp:703-710 [Conf]
  16. Alexandru Niculescu-Mizil, Rich Caruana
    Predicting good probabilities with supervised learning. [Citation Graph (0, 0)][DBLP]
    ICML, 2005, pp:625-632 [Conf]
  17. Rich Caruana, Larry J. Eshelman, J. David Schaffer
    Representation and Hidden Bias II: Eliminating Defining Length Bias in Genetic Search via Shuffle Crossover. [Citation Graph (0, 0)][DBLP]
    IJCAI, 1989, pp:750-755 [Conf]
  18. Cristian Bucila, Rich Caruana, Alexandru Niculescu-Mizil
    Model compression. [Citation Graph (0, 0)][DBLP]
    KDD, 2006, pp:535-541 [Conf]
  19. 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. [Citation Graph (0, 0)][DBLP]
    KDD, 2006, pp:909-915 [Conf]
  20. Rich Caruana, Alexandru Niculescu-Mizil
    Data mining in metric space: an empirical analysis of supervised learning performance criteria. [Citation Graph (0, 0)][DBLP]
    KDD, 2004, pp:69-78 [Conf]
  21. Art Munson, Claire Cardie, Rich Caruana
    Optimizing to Arbitrary NLP Metrics using Ensemble Selection. [Citation Graph (0, 0)][DBLP]
    HLT/EMNLP, 2005, pp:- [Conf]
  22. Rich Caruana
    Learning Many Related Tasks at the Same Time with Backpropagation. [Citation Graph (0, 0)][DBLP]
    NIPS, 1994, pp:657-664 [Conf]
  23. Rich Caruana
    A Dozen Tricks with Multitask Learning. [Citation Graph (0, 0)][DBLP]
    Neural Networks: Tricks of the Trade, 1996, pp:165-191 [Conf]
  24. Rich Caruana, Shumeet Baluja, Tom M. Mitchell
    Using the Future to Sort Out the Present: Rankprop and Multitask Learning for Medical Risk Evaluation. [Citation Graph (0, 0)][DBLP]
    NIPS, 1995, pp:959-965 [Conf]
  25. Rich Caruana, Steve Lawrence, C. Lee Giles
    Overfitting in Neural Nets: Backpropagation, Conjugate Gradient, and Early Stopping. [Citation Graph (0, 0)][DBLP]
    NIPS, 2000, pp:402-408 [Conf]
  26. Rich Caruana, Virginia R. de Sa
    Promoting Poor Features to Supervisors: Some Inputs Work Better as Outputs. [Citation Graph (0, 0)][DBLP]
    NIPS, 1996, pp:389-395 [Conf]
  27. John Langford, Rich Caruana
    (Not) Bounding the True Error. [Citation Graph (0, 0)][DBLP]
    NIPS, 2001, pp:809-816 [Conf]
  28. Rich Caruana, Alexandru Niculescu-Mizil
    An Empirical Evaluation of Supervised Learning for ROC Area. [Citation Graph (0, 0)][DBLP]
    ROCAI, 2004, pp:1-8 [Conf]
  29. Rich Caruana, Alexandru Niculescu-Mizil
    Data Mining in Metric Space: An Empirical Analysis of Supervised Learning Performance Criteria. [Citation Graph (0, 0)][DBLP]
    ROCAI, 2004, pp:9-18 [Conf]
  30. Adam L. Berger, Rich Caruana, David Cohn, Dayne Freitag, Vibhu O. Mittal
    Bridging the lexical chasm: statistical approaches to answer-finding. [Citation Graph (0, 0)][DBLP]
    SIGIR, 2000, pp:192-199 [Conf]
  31. Rich Caruana
    The Automatic Training of Rule Bases that Use Numerical Uncertainty Representations. [Citation Graph (0, 0)][DBLP]
    UAI, 1987, pp:347-356 [Conf]
  32. 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. [Citation Graph (0, 0)][DBLP]
    Artificial Intelligence in Medicine, 1997, v:9, n:2, pp:107-138 [Journal]
  33. Rich Caruana
    The automatic training of rule bases that use numerical uncertainty representations. [Citation Graph (0, 0)][DBLP]
    Int. J. Approx. Reasoning, 1988, v:2, n:3, pp:330-331 [Journal]
  34. 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. [Citation Graph (0, 0)][DBLP]
    Journal of Biomedical Informatics, 2005, v:38, n:5, pp:347-366 [Journal]
  35. Rich Caruana, Virginia R. de Sa
    Benefitting from the Variables that Variable Selection Discards. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2003, v:3, n:, pp:1245-1264 [Journal]
  36. Rich Caruana
    Multitask Learning. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1997, v:28, n:1, pp:41-75 [Journal]
  37. Rich Caruana, Thorsten Joachims, Lars Backstrom
    KDD-Cup 2004: results and analysis. [Citation Graph (0, 0)][DBLP]
    SIGKDD Explorations, 2004, v:6, n:2, pp:95-108 [Journal]
  38. David B. Skalak, Alexandru Niculescu-Mizil, Rich Caruana
    Classifier Loss Under Metric Uncertainty. [Citation Graph (0, 0)][DBLP]
    ECML, 2007, pp:310-322 [Conf]
  39. Daria Sorokina, Rich Caruana, Mirek Riedewald
    Additive Groves of Regression Trees. [Citation Graph (0, 0)][DBLP]
    ECML, 2007, pp:323-334 [Conf]
  40. Alexandru Niculescu-Mizil, Rich Caruana
    Obtaining Calibrated Probabilities from Boosting. [Citation Graph (0, 0)][DBLP]
    UAI, 2005, pp:413-0 [Conf]

  41. Consensus Clusterings. [Citation Graph (, )][DBLP]


  42. Detecting and Interpreting Variable Interactions in Observational Ornithology Data. [Citation Graph (, )][DBLP]


  43. Detecting statistical interactions with additive groves of trees. [Citation Graph (, )][DBLP]


  44. An empirical evaluation of supervised learning in high dimensions. [Citation Graph (, )][DBLP]


  45. C2FS: An Algorithm for Feature Selection in Cascade Neural Networks. [Citation Graph (, )][DBLP]


  46. Self-Optimizing Memory Controllers: A Reinforcement Learning Approach. [Citation Graph (, )][DBLP]


  47. Classification with partial labels. [Citation Graph (, )][DBLP]


  48. On Feature Selection, Bias-Variance, and Bagging. [Citation Graph (, )][DBLP]


  49. Improving Classification with Pairwise Constraints: A Margin-Based Approach. [Citation Graph (, )][DBLP]


  50. Predicting parallel application performance via machine learning approaches. [Citation Graph (, )][DBLP]


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