|
Books |
Brazdil P.,
Giraud-Carrier C., Soares C., Vilalta R. (2008)
Metalearning:
Applications to Data Mining.
Springer Verlag. ISBN: 978-3-540-73262-4
|
Journal Papers and Book Chapters |
Vilalta R.,
Stepinski T. (2008)
Cluster
Validation.
Encyclopedia of Data Warehousing and Data Mining,
2nd edition, J. Wang Ed.
Giraud-Carrier C.,
Brazdil P. and Soares C., Vilalta R. (2008)
Meta-Learning.
Encyclopedia of Data Warehousing and Data Mining,
2nd edition, J. Wang Ed.
Stepinski T., Vilalta R., Achari M., (2007)
Machine Learning Tools for Automatic Mapping of Martian Landforms.
IIIE Intelligent Systems, 22(6).
Vilalta R., Stepinski T., Achari M., (2007)
An Efficient Approach to External Cluster Assessment with an
Application to Martian Topography.
Data Mining and Knowledge Discovery Journal. Vol. 14, pp. 1-23. Springer
Eick C., Rouhana A.,
Bagherjeiran A., Vilalta R. (2006)
Using Clustering
to Learn Distance Functions for Supervised Similarity Assessment.
Journal of Engineering
Applications of Artificial Intelligence. Vol.
19, Issue 4, pp. 395-401.
Stepinski T., Vilalta R.
(2005)
Digital Topography Models for Martian Surfaces.
IEEE Geoscience and Remote
Sensing Letters. Vol. 2 (3) pp. 260-264.
Vilalta R., Giraud-Carrier C., Brazdil P. (2005)
Meta-Learning:
Concepts and Techniques.
Data Mining and
Knowledge Discovery Handbook: A Complete Guide for Practitioners and
Researchers.
Oded Maimon and Lior
Rokach, Editors. Springer Publishers.
Vilalta R.,
Giraud-Carrier C., Brazdil P. Soares C. (2004)
Using Meta-Learning to
Support Data Mining.
International Journal
of Computer Science and Applications. Vol. 1, No. 1, pp. 31-45.
Giraud-Carrier C., Vilalta R., Brazdil P. (2004)
Introduction
to the Special Issue on Meta-Learning.
Machine Learning, Vol. 54,
No. 3 pp. 187-193.
Vilalta R., Oblinger D. (2003)
Evaluation Metrics in Classification: A Quantification of
Distance-Bias.
Computational Intelligence, Vol. 29, No. 3, pp. 264-283.
Vilalta
R., Drissi Y. (2002).
A
Perspective View and Survey Of Meta-Learning.
Journal
of Artificial Intelligence Review, 18, No. 2, pp. 77-95.
Vilalta R., Apte C., Hellerstein J., Ma S., Weiss
S. (2002)
Predictive Algorithms in the Management of
Computer Systems.
IBM
Systems Journal, Special Issue on Artificial Intelligence, Vol 41, No. 3.
|
Conference and Workshop Papers |
Sun, C., Vilalta R. (2007)
Data
Selection using SASH Trees for Support Vector Machines.
5th
International Conference on Machine Learning and Data Mining (MLDM-07),
Ghosh S., Stepinski T.,
Vilalta R. (2007)
Automatic
Mapping of Martian Landforms Using Segmentation-Based Classification.
38th
Lunar and Planetary Science Conference.
Stepinski T., Ghosh S.,
Vilalta R. (2007)
Machine
Learning for Automatic Mapping of Planetary Surfaces.
Nineteenth
Annual Conference on Innovative Applications of Artificial Intelligence
(IAAI-07).
Subhlok J., Johnson O., Subramaniam V., Vilalta R., Yun C. (2007)
Tablet PC Video
based Hybrid Coursework in Computer Science: Report from a Pilot Project.
38th
ACM Technical Symposium on Computer Science Education (SIGCSE-2007).
Vilalta R., Mutchler G.,
Taylor S., Knuteson B. (2006)
Ninth
Workshop on Mining Scientific and Engineering Datasets (MSD06),
in
conjunction with the Sixth SIAM International Conference on Data Mining,
Stepinski T., Ghosh S.,
Vilalta R. (2006)
Automatic
Recognition of Landforms on Mars Using Terrain Segmentation and Classification.
Ninth
International Conference on Discovery Science (DS-2006),
Vilalta R. (2006)
Identifying and Characterizing Class-Clusters to Explain Learning
Performance.
AAAI
2006 Spring Symposia: What Went Wrong and Why: Lessons from AI Research and
Applications.
Ed.
Dan Shapiro.
Vilalta R., Sarda P., Mutchler G., Padley P. (2005)
Signal Enhancement
Using Classification Techniques and Physical Constraints.
Conference
on Statistical Problems in Particle Physics, Astrophysics and Cosmology
(PHYSTAT05),
Bagherjeiran A., Eick C., Chen C.,
Vilalta R. (2005)
Adaptive Clustering: Obtaining Better Clusters Using
Feedback and Past Experience.
Fifth IEEE International
Conference on Data Mining (ICDM05), New
Knuteson B., Vilalta R.
(2005)
Testing
Theories in Particle Physics Using Maximum Likelihood and Adaptive Bin
Allocation.
9th
European Conference on Principles and Practices of Knowledge Discovery in
Databases (PKDD05),
Bagherjeiran A., Vilalta R. Eick C. (2005)
Content-Based Image
Retrieval Through a Multi-Agent Meta-Learning
Framework.
17th
IEEE Conference on Tools with Artificial Intelligence (ICTAI05),
Eick C., Rouhana A., Bagherjeiran A., Vilalta R.(2005)
Using Clustering to Learn Distance Functions for Supervised
Similarity Assessment.
International Conference on
Machine Learning and Data Mining (MLDM05),
Vilalta R., Stepinski T., Achari M., Ocegueda-Hernandez F.(2004)
A Quantification of Cluster Novelty with
an Application to Martian Topography.
8th European
Conference on Principles and Practice of Knowledge Discovery in Databases
(PKDD04).
Eick C., Zeidat N., Vilalta R. (2004)
Using Representative-Based Clustering for
Nearest Neighbor Dataset Editing.
Fourth IEEE International
Conference on Data Mining (ICDM04),
Vilalta R., Achari M., Eick C.(2004)
Piece-Wise Model Fitting Using Local Data
Patterns.
Sixteenth European
Conference on Artificial Intelligence (ECAI04).
Vilalta R., Stepinski T.
(2004)
Thematic
Maps of Martian Topography Generated by a Clustering Algorithm.
35th Lunar and
Planetary Science Conference (LPSC04).
Vilalta R., Achari M.,
Eick C. (2003)
Class Decomposition Via Clustering:
A New Framework For Low-Variance Classifiers.
Proceedings of the Third
IEEE International Conference on Data Mining (ICDM03),
Vilalta R.,
A Decomposition Of Classes Via Clustering
To Explain And Improve Naive Bayes.
Proceedings of the European
Conference on Machine Learning (ECML03).
Vilalta R., Achari M.
(2003)
A Hierarchical Approach to Classification
for Systems with Complex Low-Level Interactions.
Proceedings of the IEEE
International Symposium on Intelligent Control (ISIC03),
Vilalta R., Padley P., Lee S.J., Sun C., Bagherjeiran A. (2003)
Evaluating and Constructing Features For
Identification of Tau Leptons.
Proceedings of the
Conference on Statistical Problems in Particle Physics, Astrophysics, and
Cosmology (PHYSTAT03).
Sahoo
R. K., Oliner A. J., Rish I., Gupta M., Moreira J. E., Ma S., Vilalta R. (2003)
Critical Event Prediction for Proactive
Management in Large-scale Computer Clusters.
The
Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
(KDD03),
Stepinski
T., Vilalta R., Achari M., McGovern P.J. (2003)
34th
Lunar and Planetary Science Conference (LPSC03). League City, Texas.
Vilalta R., Stepinski T.
(2003)
Classification
of Martian Terrain Using Automated Discovery of Structure Algorithm Applied to
Digital Topography.
Meeting of the American
Geophysical Union (AGU03), San Francisco CA.
Vilalta
R., Ma Sheng (2002).
Predicting
Rare Events inTemporal Domains.
Proceedings
of the 2002 IEEE International Conference on
Domeniconi C., Perng C.,
Vilalta R., Ma S. (2002)
A Classification Approach for Prediction of Target Events in
Temporal Sequences.
Proceedings of the 6th European Conference on Principles and Practice of
Knowledge Discovery in Databases (PKDD'02), Helsinki, Finland.
Vilalta
R., Drissi Y. (2002)
A Characterization of Difficult Problems in Classification.
Proceedings of the International Conference on Machine Learning and
Applications (ICMLA02), Las Vegas, Nevada.
Sahoo R., Bae M., Vilalta R.,
Moreira J., Ma S., Gupta M. (2002)
Workshop
on Self-Healing, Adaptive, and Self-Managed Systems as part of the
16th
Annual ACM International Conference on Supercomputing.
Vilalta
R., Brodie M., Oblinger D.,
A Unified
Framework For Evaluation Metrics In Classification Using Decision Trees .
Proceedings of the 12th European Conference on Machine
Learning (ECML01),
Vilalta R., Ma S., Hellerstein J. (2001)
Rule Induction
of Computer Events
Proceedings
of the 12th IFIP/IEEE International Workshop on
Distributed Systems: Operations & Management (DSOM01),
Vilalta
R., Drissi Y. (2001)
Research
Directions in Meta-Learning
Proceedings of the International Conference on
Artificial Intelligence, (ICAI01)
Vilalta
R., Oblinger D. (2000)
A
Quantification Of Distance-Bias Between Evaluation
Metrics In Classification
Proceedings of the 17th International Conference on
Machine Learning (ICML00). Stanford
University, Stanford, CA., pp.1087-1094.
Vilalta
R., Rish
What Works Well
Where in Inductive Learning?
Workshop during the 17th International Conference on
Machine Learning (ICML00).
Vilalta R., Apte C., Weiss S.
(2000)
Operational
Data Analysis: Improved Predictions Using Multi-Computer Pattern Detection.
Proceedings
of the International Workshop on Distributed Systems: Operations &
Management (DSOM00), Austin Texas.
Vilalta
R. (1999)
Understanding
Accuracy Performance Through Concept Characterization
And Algorithm Analysis.
Workshop on Recent Advances in Meta-Learning and Future Work, as part of the
16th International Conference on Machine Learning,
Bled Slovenia. Edited by Christophe Giraud-Carrier and Bernhard Pfahringer. pp
3-9.
Vilalta
R., Rendell L. (1997)
Integrating
Feature Construction with Multiple Classifiers in Decision Tree Induction
Proceedings of the 14th International Conference on
Machine Learning (ICML97).
Vanderbilt
University, Nashville, TN. Morgan Kaufman Publishers, San Francisco CA. pp
394-402.
Vilalta
R., Blix G., Rendell L. (1997)
Global Data
Analysis and the Fragmentation problem in Decision Tree Induction
Proceedings
of the 9th European Conference on Machine Learning (ECML97).
Lecture
Notes in Artificial Intelligence. Vol. XXX. Springer-Verlag, Heinderberg, pp 312-326.
Perez E., Vilalta R., Rendell
L. (1996)
On the Importance
of Change of Representation in Induction (Invited talk).
Presented at the Workshop of Inductive Learning for the 1996 Canadian
Conference on Artificial Intelligence.
|
Technical Reports |
Vilalta
R., Blix G., Rendell L. (1995)
The Value of Lookahead Feature Construction in Decision Tree
Induction.
Beckman Institute, University of Illinois at Urbana-Champaign, Technical
Report UIUC-BI-AI-95-01.
|
Thesis |
Vilalta
R. (1998)
University
of Illinois at Urbana-Champaign. PhD Thesis.
|
Patents Issued |
Vilalta
R., Irina R. (2005)
Method
and Apparatus for Selecting a Data Classification Model Using Meta-Learning.
Vilalta
R., Drissi Y. (2004)
Method
and Apparatus for Building a Data Classification Model Using Interactive
Adaptive Learning Algorithms.