Ricardo Vilalta

Orcid: 0000-0001-8165-8805

Affiliations:
  • University of Houston, USA


According to our database1, Ricardo Vilalta authored at least 76 papers between 1997 and 2024.

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Bibliography

2024
Robust errant beam prognostics with conditional modeling for particle accelerators.
Mach. Learn. Sci. Technol., March, 2024

Corrigendum: Applications and techniques for fast machine learning in science.
Frontiers Big Data, 2024

2023
Physics-informed neural networks in the recreation of hydrodynamic simulations from dark matter.
CoRR, 2023

2022
Applications and Techniques for Fast Machine Learning in Science.
Frontiers Big Data, 2022

2021
Applications and Techniques for Fast Machine Learning in Science.
CoRR, 2021

Learning Abstract Task Representations.
Proceedings of the AAAI Workshop on Meta-Learning and MetaDL Challenge, 2021

2020
Active learning with RESSPECT: Resource allocation for extragalactic astronomical transients.
Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

2019
Algorithms and Statistical Models for Scientific Discovery in the Petabyte Era.
CoRR, 2019

Filter-Based Information-Theoretic Feature Selection.
Proceedings of the 3rd International Conference on Advances in Artificial Intelligence, 2019

2018
Transfer Learning in Astronomy: A New Machine-Learning Paradigm.
CoRR, 2018

A General Approach to Domain Adaptation with Applications in Astronomy.
CoRR, 2018

Conceptual Domain Adaptation Using Deep Learning.
CoRR, 2018

2017
Inductive Transfer.
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Metalearning.
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Photometric redshift estimation: An active learning approach.
Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

Disk failure prediction in heterogeneous environments.
Proceedings of the International Symposium on Performance Evaluation of Computer and Telecommunication Systems, 2017

2016
Analysis of correlation between pediatric asthma exacerbation and exposure to pollutant mixtures with association rule mining.
Artif. Intell. Medicine, 2016

Automated supernova Ia classification using adaptive learning techniques.
Proceedings of the 2016 IEEE Symposium Series on Computational Intelligence, 2016

Exploring the spectroscopic diversity of type Ia supernovae with Deep Learning and Unsupervised Clustering.
Proceedings of the Astroinformatics 2016, Sorrento, Italy, October 19-25, 2016, 2016

2015
The overlooked potential of Generalized Linear Models in astronomy, I: Binomial regression.
Astron. Comput., 2015

Star Classification Under Data Variability: An Emerging Challenge in Astroinformatics.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

Perinasal indicators of deceptive behavior.
Proceedings of the 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, 2015

2014
Domain Adaptation under Data Misalignment: An Application to Cepheid Variable Star Classification.
Proceedings of the 22nd International Conference on Pattern Recognition, 2014

Fault resilient physical neural networks on a single chip.
Proceedings of the 2014 International Conference on Compilers, 2014

A Data Complexity Approach to Kernel Selection for Support Vector Machines.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013
A machine learning approach to Cepheid variable star classification using data alignment and maximum likelihood.
Astron. Comput., 2013

An Empirical Study of the Suitability of Class Decomposition for Linear Models: When Does It Work Well?
Proceedings of the 13th SIAM International Conference on Data Mining, 2013

2012
Modeling repetitive patterns: A bridge between pattern theory and data mining.
Proceedings of the 2012 IEEE International Conference on Granular Computing, 2012

2011
Subkilometer crater discovery with boosting and transfer learning.
ACM Trans. Intell. Syst. Technol., 2011

2010
Inductive Transfer.
Proceedings of the Encyclopedia of Machine Learning, 2010

Metalearning.
Proceedings of the Encyclopedia of Machine Learning, 2010

Meta-Learning - Concepts and Techniques.
Proceedings of the Data Mining and Knowledge Discovery Handbook, 2nd ed., 2010

Automatic Annotation of Planetary Surfaces With Geomorphic Labels.
IEEE Trans. Geosci. Remote. Sens., 2010

A unified framework for reinforcement learning, co-learning and meta-learning how to coordinate in collaborative multi-agent systems.
Proceedings of the International Conference on Computational Science, 2010

A Conceptual Study of Model Selection in Classification - Multiple Local Models vs One Global Model.
Proceedings of the ICAART 2010 - Proceedings of the International Conference on Agents and Artificial Intelligence, Volume 1, 2010

Learning and Meta-Learning for Coordination of Autonomous Unmanned Vehicles - A Preliminary Analysis.
Proceedings of the ECAI 2010, 2010

Automatic detection of craters in planetary images: an embedded framework using feature selection and boosting.
Proceedings of the 19th ACM Conference on Information and Knowledge Management, 2010

2009
Cluster Validation.
Proceedings of the Encyclopedia of Data Warehousing and Mining, Second Edition (4 Volumes), 2009

Meta-Learning.
Proceedings of the Encyclopedia of Data Warehousing and Mining, Second Edition (4 Volumes), 2009

A Framework for Multi-Objective Clustering and Its Application to Co-Location Mining.
Proceedings of the Advanced Data Mining and Applications, 5th International Conference, 2009

Metalearning - Applications to Data Mining.
Cognitive Technologies, Springer, ISBN: 978-3-540-73262-4, 2009

2007
Machine Learning Tools for Automatic Mapping of Martian Landforms.
IEEE Intell. Syst., 2007

An efficient approach to external cluster assessment with an application to martian topography.
Data Min. Knowl. Discov., 2007

Tablet PC video based hybrid coursework in computer science: report from a pilot project.
Proceedings of the 38th SIGCSE Technical Symposium on Computer Science Education, 2007

Data Selection Using SASH Trees for Support Vector Machines.
Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2007

Machine Learning for Automatic Mapping of Planetary Surfaces.
Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence, 2007

2006
Using clustering to learn distance functions for supervised similarity assessment.
Eng. Appl. Artif. Intell., 2006

Automatic Recognition of Landforms on Mars Using Terrain Segmentation and Classification.
Proceedings of the Discovery Science, 9th International Conference, 2006

Identifying and Characterizing Class Clusters to Explain Learning Performance.
Proceedings of the What Went Wrong and Why: Lessons from AI Research and Applications, 2006

2005
Digital topography models for Martian surfaces.
IEEE Geosci. Remote. Sens. Lett., 2005

Testing Theories in Particle Physics Using Maximum Likelihood and Adaptive Bin Allocation.
Proceedings of the Knowledge Discovery in Databases: PKDD 2005, 2005

Content-Based Image Retrieval through a Multi-Agent Meta-Learning Framework.
Proceedings of the 17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2005), 2005

Adaptive Clustering: Obtaining Better Clusters Using Feedback and Past Experience.
Proceedings of the 5th IEEE International Conference on Data Mining (ICDM 2005), 2005

Meta-Learning.
Proceedings of the Data Mining and Knowledge Discovery Handbook., 2005

2004
Introduction to the Special Issue on Meta-Learning.
Mach. Learn., 2004

Using Meta-Learning to Support Data Mining.
Int. J. Comput. Sci. Appl., 2004

A Quantification of Cluster Novelty with an Application to Martian Topography.
Proceedings of the Knowledge Discovery in Databases: PKDD 2004, 2004

Using Representative-Based Clustering for Nearest Neighbor Dataset Editing.
Proceedings of the 4th IEEE International Conference on Data Mining (ICDM 2004), 2004

Piece-Wise Model Fitting Using Local Data Patterns.
Proceedings of the 16th Eureopean Conference on Artificial Intelligence, 2004

2003
Evaluation Metrics in Classification: A Quantification of Distance-Bias.
Comput. Intell., 2003

Critical event prediction for proactive management in large-scale computer clusters.
Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 24, 2003

Class Decomposition via Clustering: A New Framework for Low-Variance Classifiers.
Proceedings of the 3rd IEEE International Conference on Data Mining (ICDM 2003), 2003

A Decomposition of Classes via Clustering to Explain and Improve Naive Bayes.
Proceedings of the Machine Learning: ECML 2003, 2003

A hierarchical approach to classification for systems with complex low-level interactions.
Proceedings of the International Symposium on Intelligent Control, 2003

2002
Predictive algorithms in the management of computer systems.
IBM Syst. J., 2002

A Perspective View and Survey of Meta-Learning.
Artif. Intell. Rev., 2002

A Classification Approach for Prediction of Target Events in Temporal Sequences.
Proceedings of the Principles of Data Mining and Knowledge Discovery, 2002

A Characterization of Difficult Problems in Classification.
Proceedings of the 2002 International Conference on Machine Learning and Applications, 2002

Predicting Rare Events In Temporal Domains.
Proceedings of the 2002 IEEE International Conference on Data Mining (ICDM 2002), 2002

2001
A Unified Framework for Evaluation Metrics in Classification Using Decision Trees.
Proceedings of the Machine Learning: EMCL 2001, 2001

Rule Induction of Computer Events.
Proceedings of the Operations & Management, 2001

2000
A Quantification of Distance Bias Between Evaluation Metrics In Classification.
Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000

Operational Data Analysis: Improved Predictions Using Multi-computer Pattern Detection.
Proceedings of the Services Management in Intelligent Networks, 2000

1998
On the Development of Inductive Learning Algorithms: Generating Flexible and Adaptable Concept Representations
PhD thesis, 1998

1997
Integrating Feature Construction with Multiple Classifiers in Decision Tree Induction.
Proceedings of the Fourteenth International Conference on Machine Learning (ICML 1997), 1997

Global Data Analysis and the Fragmentation Problem in Decision Tree Induction.
Proceedings of the Machine Learning: ECML-97, 1997


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