Please note: This is a beta version of the new dblp website.
You can find the classic dblp view of this page here.
You can find the classic dblp view of this page here.
Ricardo Vilalta
2010 – today
- 2013
[c30]Francisco Ocegueda-Hernandez, Ricardo Vilalta: An Empirical Study of the Suitability of Class Decomposition for Linear Models: When Does It Work Well? SDM 2013: 432-440- 2011
- [j10]Wei Ding, Tomasz F. Stepinski, Yang Mu, Lourenço P. C. Bandeira, Ricardo Vilalta, Youxi Wu, Zhenyu Lu, Tianyu Cao, Xindong Wu: Subkilometer crater discovery with boosting and transfer learning. ACM TIST 2(4): 39 (2011)
- 2010
- [j9]Soumya Ghosh, Tomasz F. Stepinski, Ricardo Vilalta: Automatic Annotation of Planetary Surfaces With Geomorphic Labels. IEEE T. Geoscience and Remote Sensing 48(1-1): 175-185 (2010)
- [c29]Wei Ding, Tomasz F. Stepinski, Lourenço P. C. Bandeira, Ricardo Vilalta, Youxi Wu, Zhenyu Lu, Tianyu Cao: Automatic detection of craters in planetary images: an embedded framework using feature selection and boosting. CIKM 2010: 749-758
- [c28]Predrag T. Tosic, Ricardo Vilalta: Learning and Meta-Learning for Coordination of Autonomous Unmanned Vehicles - A Preliminary Analysis. ECAI 2010: 163-168
- [c27]Ricardo Vilalta, Francisco Ocegueda-Hernandez, C. Bagaria: A Conceptual Study of Model Selection in Classification - Multiple Local Models vs One Global Model. ICAART (1) 2010: 113-118
- [c26]Predrag T. Tosic, Ricardo Vilalta: A unified framework for reinforcement learning, co-learning and meta-learning how to coordinate in collaborative multi-agent systems. ICCS 2010: 2217-2226
- [p2]Ricardo Vilalta, Christophe G. Giraud-Carrier, Pavel Brazdil: Meta-Learning - Concepts and Techniques. Data Mining and Knowledge Discovery Handbook 2010: 717-731
- [r4]Ricardo Vilalta, Christophe G. Giraud-Carrier, Pavel Brazdil, Carlos Soares: Inductive Transfer. Encyclopedia of Machine Learning 2010: 545-548
- [r3]Pavel Brazdil, Ricardo Vilalta, Christophe G. Giraud-Carrier, Carlos Soares: Metalearning. Encyclopedia of Machine Learning 2010: 662-666
2000 – 2009
- 2009
- [b1]Pavel Brazdil, Christophe G. Giraud-Carrier, Carlos Soares, Ricardo Vilalta: Metalearning - Applications to Data Mining. Cognitive Technologies, Springer 2009, ISBN 978-3-540-73262-4, pp. I-X, 1-176
- [c25]Rachsuda Jiamthapthaksin, Christoph F. Eick, Ricardo Vilalta: A Framework for Multi-Objective Clustering and Its Application to Co-Location Mining. ADMA 2009: 188-199
- [r2]Ricardo Vilalta, Tomasz F. Stepinski: Cluster Validation. Encyclopedia of Data Warehousing and Mining 2009: 231-236
- [r1]Christophe G. Giraud-Carrier, Pavel Brazdil, Carlos Soares, Ricardo Vilalta: Meta-Learning. Encyclopedia of Data Warehousing and Mining 2009: 1207-1215
- 2007
- [j8]Ricardo Vilalta, Tomasz F. Stepinski, Murali-Krishna Achari: An efficient approach to external cluster assessment with an application to martian topography. Data Min. Knowl. Discov. 14(1): 1-23 (2007)
- [j7]Tomasz F. Stepinski, Ricardo Vilalta, Soumya Ghosh: Machine Learning Tools for Automatic Mapping of Martian Landforms. IEEE Intelligent Systems 22(6): 100-106 (2007)
- [c24]Tomasz F. Stepinski, Soumya Ghosh, Ricardo Vilalta: Machine Learning for Automatic Mapping of Planetary Surfaces. AAAI 2007: 1807-1812
- [c23]Chaofan Sun, Ricardo Vilalta: Data Selection Using SASH Trees for Support Vector Machines. MLDM 2007: 286-295
- [c22]Jaspal Subhlok, Olin Johnson, Venkat Subramaniam, Ricardo Vilalta, Chang Yun: Tablet PC video based hybrid coursework in computer science: report from a pilot project. SIGCSE 2007: 74-78
- 2006
- [j6]Christoph F. Eick, Alain Rouhana, Abraham Bagherjeiran, Ricardo Vilalta: Using clustering to learn distance functions for supervised similarity assessment. Eng. Appl. of AI 19(4): 395-401 (2006)
- [c21]Ricardo Vilalta: Identifying and Characterizing Class Clusters to Explain Learning Performance. AAAI Spring Symposium: What Went Wrong and Why: Lessons from AI Research and Applications 2006: 19-25
- [c20]Tomasz F. Stepinski, Soumya Ghosh, Ricardo Vilalta: Automatic Recognition of Landforms on Mars Using Terrain Segmentation and Classification. Discovery Science 2006: 255-266
- 2005
- [c19]Abraham Bagherjeiran, Christoph F. Eick, Chun-Sheng Chen, Ricardo Vilalta: Adaptive Clustering: Obtaining Better Clusters Using Feedback and Past Experience. ICDM 2005: 565-568
- [c18]Abraham Bagherjeiran, Ricardo Vilalta, Christoph F. Eick: Content-Based Image Retrieval through a Multi-Agent Meta-Learning Framework. ICTAI 2005: 24-28
- [c17]Christoph F. Eick, Alain Rouhana, Abraham Bagherjeiran, Ricardo Vilalta: Using Clustering to Learn Distance Functions for Supervised Similarity Assessment. MLDM 2005: 120-131
- [c16]Bruce Knuteson, Ricardo Vilalta: Testing Theories in Particle Physics Using Maximum Likelihood and Adaptive Bin Allocation. PKDD 2005: 552-560
- [p1]Ricardo Vilalta, Christophe G. Giraud-Carrier, Pavel Brazdil: Meta-Learning. The Data Mining and Knowledge Discovery Handbook 2005: 731-748
- 2004
- [j5]Ricardo Vilalta, Christophe G. Giraud-Carrier, Pavel Brazdil, Carlos Soares: Using Meta-Learning to Support Data Mining. IJCSA 1(1): 31-45 (2004)
- [j4]Christophe G. Giraud-Carrier, Ricardo Vilalta, Pavel Brazdil: Introduction to the Special Issue on Meta-Learning. Machine Learning 54(3): 187-193 (2004)
- [c15]Ricardo Vilalta, Murali-Krishna Achari, Christoph F. Eick: Piece-Wise Model Fitting Using Local Data Patterns. ECAI 2004: 559-563
- [c14]Christoph F. Eick, Nidal M. Zeidat, Ricardo Vilalta: Using Representative-Based Clustering for Nearest Neighbor Dataset Editing. ICDM 2004: 375-378
- [c13]Ricardo Vilalta, Tomasz F. Stepinski, Murali-Krishna Achari, Francisco Ocegueda-Hernandez: A Quantification of Cluster Novelty with an Application to Martian Topography. PKDD 2004: 434-445
- 2003
- [j3]Ricardo Vilalta, Daniel Oblinger: Evaluation Metrics in Classification: A Quantification of Distance-Bias. Computational Intelligence 19(3): 264-283 (2003)
- [c12]Ricardo Vilalta, Irina Rish: A Decomposition of Classes via Clustering to Explain and Improve Naive Bayes. ECML 2003: 444-455
- [c11]Ricardo Vilalta, Murali-Krishna Achari, Christoph F. Eick: Class Decomposition via Clustering: A New Framework for Low-Variance Classifiers. ICDM 2003: 673-676
- [c10]Ramendra K. Sahoo, Adam J. Oliner, Irina Rish, Manish Gupta, José E. Moreira, Sheng Ma, Ricardo Vilalta, Anand Sivasubramaniam: Critical event prediction for proactive management in large-scale computer clusters. KDD 2003: 426-435
- 2002
- [j2]Ricardo Vilalta, Youssef Drissi: A Perspective View and Survey of Meta-Learning. Artif. Intell. Rev. 18(2): 77-95 (2002)
- [j1]Ricardo Vilalta, Chidanand Apté, Joseph L. Hellerstein, Sheng Ma, Sholom M. Weiss: Predictive algorithms in the management of computer systems. IBM Systems Journal 41(3): 461-474 (2002)
- [c9]
- [c8]Ricardo Vilalta, Youssef Drissi: A Characterization of Difficult Problems in Classification. ICMLA 2002: 133-138
- [c7]Carlotta Domeniconi, Chang-Shing Perng, Ricardo Vilalta, Sheng Ma: A Classification Approach for Prediction of Target Events in Temporal Sequences. PKDD 2002: 125-137
- 2001
- [c6]Ricardo Vilalta, Sheng Ma, Joseph L. Hellerstein: Rule Induction of Computer Events. DSOM 2001: 75-86
- [c5]Ricardo Vilalta, Mark Brodie, Daniel Oblinger, Irina Rish: A Unified Framework for Evaluation Metrics in Classification Using Decision Trees. ECML 2001: 503-514
- 2000
- [c4]Ricardo Vilalta, Chidanand Apté, Sholom M. Weiss: Operational Data Analysis: Improved Predictions Using Multi-computer Pattern Detection. DSOM 2000: 37-46
- [c3]Ricardo Vilalta, Daniel Oblinger: A Quantification of Distance Bias Between Evaluation Metrics In Classification. ICML 2000: 1087-1094
1990 – 1999
- 1997
- [c2]Ricardo Vilalta, Gunnar Blix, Larry A. Rendell: Global Data Analysis and the Fragmentation Problem in Decision Tree Induction. ECML 1997: 312-326
- [c1]Ricardo Vilalta, Larry A. Rendell: Integrating Feature Construction with Multiple Classifiers in Decision Tree Induction. ICML 1997: 394-402
Coauthor Index
data released under the ODC-BY 1.0 license. See also our legal information page
last updated on 2013-10-02 11:23 CEST by the dblp team