According to our database1, Ricard Gavaldà authored at least 90 papers between 1990 and 2019.
Legend:Book In proceedings Article PhD thesis Other
Proceedings of the Encyclopedia of Big Data Technologies., 2019
Probabilistic model for robust traffic state identification in urban networks.
Proceedings of the 2019 IEEE Intelligent Transportation Systems Conference, 2019
Interpretable Patient Trajectories from Temporally Annotated Health Records.
Proceedings of the 32nd IEEE International Symposium on Computer-Based Medical Systems, 2019
A new method of moments for latent variable models.
Mach. Learn., 2018
Generating Synthetic but Plausible Healthcare Record Datasets.
Pipeline design to identify key features and classify the chemotherapy response on lung cancer patients using large-scale genetic data.
BMC Syst. Biol., 2018
Identifiability and transportability in dynamic causal networks.
Int. J. Data Sci. Anal., 2017
Clustering Patients with Tensor Decomposition.
Proceedings of the Machine Learning for Health Care Conference, 2017
Machine Learning Assists the Classification of Reports by Citizens on Disease-Carrying Mosquitoes.
Proceedings of the First Workshop on Data Science for Social Good co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Dicovery in Databases, 2016
Does Training Affect Match Performance? A Study Using Data Mining And Tracking Devices.
Proceedings of the Workshop on Machine Learning and Data Mining for Sports Analytics 2016 co-located with the 2016 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2016
From Training to Match Performance: A Predictive and Explanatory Study on Novel Tracking Data.
Proceedings of the IEEE International Conference on Data Mining Workshops, 2016
Fraud Detection in Energy Consumption: A Supervised Approach.
Proceedings of the 2016 IEEE International Conference on Data Science and Advanced Analytics, 2016
An efficient closed frequent itemset miner for the MOA stream mining system.
AI Commun., 2015
Characterizing chronic disease and polymedication prescription patterns from electronic health records.
Proceedings of the 2015 IEEE International Conference on Data Science and Advanced Analytics, 2015
Learning Read-Constant Polynomials of Constant Degree Modulo Composites.
Theory Comput. Syst., 2014
Adaptively learning probabilistic deterministic automata from data streams.
Mach. Learn., 2014
A methodology for the evaluation of high response time on E-commerce users and sales.
Inf. Syst. Frontiers, 2014
Building Green Cloud Services at Low Cost.
Proceedings of the IEEE 34th International Conference on Distributed Computing Systems, 2014
Introduction to the special issue on social web mining.
ACM Trans. Intell. Syst. Technol., 2013
Learning probabilistic automata: A study in state distinguishability.
Theor. Comput. Sci., 2013
Empowering automatic data-center management with machine learning.
Proceedings of the 28th Annual ACM Symposium on Applied Computing, 2013
Power-Aware Multi-data Center Management Using Machine Learning.
Proceedings of the 42nd International Conference on Parallel Processing, 2013
The Architecture of a Churn Prediction System Based on Stream Mining.
Proceedings of the Artificial Intelligence Research and Development, 2013
Bootstrapping and Learning PDFA in Data Streams.
Proceedings of the Eleventh International Conference on Grammatical Inference, 2012
Energy-efficient and multifaceted resource management for profit-driven virtualized data centers.
Future Gener. Comput. Syst., 2012
Online Techniques for Dealing with Concept Drift in Process Mining.
Proceedings of the Advances in Intelligent Data Analysis XI - 11th International Symposium, 2012
Applying Trust Metrics Based on User Interactions to Recommendation in Social Networks.
Proceedings of the International Conference on Advances in Social Networks Analysis and Mining, 2012
Detecting Sentiment Change in Twitter Streaming Data.
Proceedings of the Second Workshop on Applications of Pattern Analysis, 2011
Mining frequent closed trees in evolving data streams.
Intell. Data Anal., 2011
Non-intrusive Estimation of QoS Degradation Impact on E-Commerce User Satisfaction.
Proceedings of The Tenth IEEE International Symposium on Networking Computing and Applications, 2011
Mining frequent closed graphs on evolving data streams.
Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011
Optimal Resource Allocation in a Virtualized Software Aging Platform with Software Rejuvenation.
Proceedings of the IEEE 22nd International Symposium on Software Reliability Engineering, 2011
Adaptive Scheduling on Power-Aware Managed Data-Centers Using Machine Learning.
Proceedings of the 12th IEEE/ACM International Conference on Grid Computing, 2011
SalaboMiner - A Biomedical Literature Mining Tool for Inferring the Genetics of Complex Diseases.
Proceedings of the BIOINFORMATICS 2011, 2011
Resource-bounded Dimension in Computational Learning Theory
J2EE instrumentation for software aging root cause application component determination with AspectJ.
Proceedings of the 24th IEEE International Symposium on Parallel and Distributed Processing, 2010
Characterization of workload and resource consumption for an online travel and booking site.
Proceedings of the 2010 IEEE International Symposium on Workload Characterization, 2010
Learning PDFA with Asynchronous Transitions.
Proceedings of the Grammatical Inference: Theoretical Results and Applications, 2010
Towards energy-aware scheduling in data centers using machine learning.
Proceedings of the 1st International Conference on Energy-Efficient Computing and Networking, 2010
Adaptive on-line software aging prediction based on machine learning.
Proceedings of the 2010 IEEE/IFIP International Conference on Dependable Systems and Networks, 2010
A Lower Bound for Learning Distributions Generated by Probabilistic Automata.
Proceedings of the Algorithmic Learning Theory, 21st International Conference, 2010
The frequency spectrum of finite samples from the intermittent silence process.
J. Assoc. Inf. Sci. Technol., 2009
Self-adaptive utility-based web session management.
Comput. Networks, 2009
Adaptive XML Tree Classification on Evolving Data Streams.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2009
New ensemble methods for evolving data streams.
Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 28, 2009
Adaptive Learning from Evolving Data Streams.
Proceedings of the Advances in Intelligent Data Analysis VIII, 2009
Predicting Web Server Crashes: A Case Study in Comparing Prediction Algorithms.
Proceedings of the Fifth International Conference on Autonomic and Autonomous Systems, 2009
An Algebraic Perspective on Boolean Function Learning.
Proceedings of the Algorithmic Learning Theory, 20th International Conference, 2009
Improving Adaptive Bagging Methods for Evolving Data Streams.
Proceedings of the Advances in Machine Learning, 2009
Mining adaptively frequent closed unlabeled rooted trees in data streams.
Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2008
Reducing wasted resources to help achieve green data centers.
Proceedings of the 22nd IEEE International Symposium on Parallel and Distributed Processing, 2008
Towards Feasible PAC-Learning of Probabilistic Deterministic Finite Automata.
Proceedings of the Grammatical Inference: Algorithms and Applications, 2008
Tailoring Resources: The Energy Efficient Consolidation Strategy Goes Beyond Virtualization.
Proceedings of the 2008 International Conference on Autonomic Computing, 2008
Adaptive distributed mechanism against flooding network attacks based on machine learning.
Proceedings of the 1st ACM Workshop on Security and Artificial Intelligence, 2008
Web Customer Modeling for Automated Session Prioritization on High Traffic Sites.
Proceedings of the User Modeling 2007, 11th International Conference, 2007
Learning from Time-Changing Data with Adaptive Windowing.
Proceedings of the Seventh SIAM International Conference on Data Mining, 2007
Theor. Comput. Sci., 2006
Learning expressions and programs over monoids.
Inf. Comput., 2006
PAC-Learning of Markov Models with Hidden State.
Proceedings of the Machine Learning: ECML 2006, 2006
Kalman Filters and Adaptive Windows for Learning in Data Streams.
Proceedings of the Discovery Science, 9th International Conference, 2006
Tractable Clones of Polynomials over Semigroups
Electronic Colloquium on Computational Complexity (ECCC), 2005
An Algebraic View on Exact Learning from Queries.
Proceedings of the New Computational Paradigms, 2005
Non-Automatizability of Bounded-Depth Frege Proofs.
Comput. Complex., 2004
Algebraic Characterizations of Small Classes of Boolean Functions.
Proceedings of the STACS 2003, 20th Annual Symposium on Theoretical Aspects of Computer Science, Berlin, Germany, February 27, 2003
Adaptive Sampling Methods for Scaling Up Knowledge Discovery Algorithms.
Data Min. Knowl. Discov., 2002
Monotone Proofs of the Pigeon Hole Principle.
Math. Log. Q., 2001
Learning Expressions over Monoids.
Proceedings of the STACS 2001, 2001
Sequential Sampling Algorithms: Unified Analysis and Lower Bounds.
Proceedings of the Stochastic Algorithms: Foundations and Applications, 2001
Discontinuities in Recurrent Neural Networks.
Neural Computation, 1999
Bounding the Expected Length of Longest Common Subsequences and Forests.
Theory Comput. Syst., 1999
Practical Algorithms for On-line Sampling.
Proceedings of the Discovery Science, 1998
Computational power of neural networks: a characterization in terms of Kolmogorov complexity.
IEEE Trans. Inf. Theory, 1997
Coding Complexity: The Computational Complexity of Succinct Descriptions.
Proceedings of the Advances in Algorithms, Languages, and Complexity, 1997
Algorithms for Learning Finite Automata from Queries: A Unified View.
Proceedings of the Advances in Algorithms, Languages, and Complexity, 1997
An Optimal Parallel Algorithm for Learning DFA.
J. UCS, 1996
Oracles and Queries That Are Sufficient for Exact Learning.
J. Comput. Syst. Sci., 1996
Bounding the Complexity of Advice Functions.
J. Comput. Syst. Sci., 1995
Learning Ordered Binary Decision Diagrams.
Proceedings of the Algorithmic Learning Theory, 6th International Conference, 1995
The Query Complexity of Learning DFA.
New Gener. Comput., 1994
Structural Analysis of Polynomial-Time Query Learnability.
Math. Syst. Theory, 1994
An Approach to Correctness of Data Parallel Algorithms.
J. Parallel Distributed Comput., 1994
The Complexity of Learning with Queries.
Proceedings of the Ninth Annual Structure in Complexity Theory Conference, Amsterdam, The Netherlands, June 28, 1994
On the Computational Complexity of Small Descriptions.
SIAM J. Comput., 1993
A Positive Relativization of Polynomial Time Versus Polylog Space.
Inf. Process. Lett., 1993
Some Structural Complexity Aspects of Neural Computation.
Proceedings of the Eigth Annual Structure in Complexity Theory Conference, San Diego, 1993
Correctness of flat data parallel algorithms: an axiomatic approach and examples.
Proceedings of the PARLE '92: Parallel Architectures and Languages Europe, 1992
A Note on the Query Complexity of Learning DFA (Extended Abstract).
Proceedings of the Algorithmic Learning Theory, Third Workshop, 1992
Kolmogorov randomness and its applications to structural complexity theory.
PhD thesis, 1992
Strong and Robustly Strong Polynomial-Time Reducibilities to Sparse Sets.
Theor. Comput. Sci., 1991
Generalized Kolmogorov Complexity in Relativized Separations (Extended Abstract).
Proceedings of the Mathematical Foundations of Computer Science 1990, 1990