Pavel Brazdil

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New Functions for Unsupervised Asymmetrical Paraphrase Detection

João Cordeiro, Gaël Dias, Pavel Brazdil, 2007, J. Softw..

Knowledge States and Meta-Knowledge Maintenance

Pavel Brazdil, 1987, EWSL.

Discovery Science, 12th International Conference, DS 2009, Porto, Portugal, October 3-5, 2009

João Gama, Alípio Mário Jorge, Pavel Brazdil, 2009, Discovery Science.

Characterization of Classification Algorithms

João Gama, Pavel Brazdil, João Gama, 1995, EPIA.

Zoomed Ranking: Selection of Classification Algorithms Based on Relevant Performance Information

Carlos Soares, Pavel Brazdil, Carlos Soares, 2000, PKDD.

Ranking Learning Algorithms: Using IBL and Meta-Learning on Accuracy and Time Results

Carlos Soares, Pavel Brazdil, Joaquim Pinto da Costa, 2003, Machine Learning.

Sampling-Based Relative Landmarks: Systematically Test-Driving Algorithms Before Choosing

Carlos Soares, Pavel Brazdil, Johann Petrak, 2001, EPIA.

Analysis of Publications of FEP and their Affinities

Pavel Brazdil, André Martinez, Luís Trigo, 2018 .

Panel: Learning in Distributed Systems and Multi-Agent Environments

Luís Torgo, Matjaz Gams, Walter Van de Velde, 1991, EWSL.

Incremental Sparse TFIDF & Incremental Similarity with Bipartite Graphs pdf

Pavel Brazdil, Rui Portocarrero Sarmento, 2018, ArXiv.

Incremental TextRank - Automatic Keyword Extraction for Text Streams

João Gama, Pavel Brazdil, Rui Portocarrero Sarmento, 2018, ICEIS.

Reducing Rankings of Classifiers by Eliminating Redundant Classifiers

Rui Pereira, Carlos Soares, Pavel Brazdil, 2001, EPIA.

Use of Derivation Trees in Discrimination

Pavel Brazdil, P. Brazdil, 1984, European Conference on Artificial Intelligence.

Metalearning and Algorithm Selection: progress, state of the art and introduction to the 2018 Special Issue

Pavel Brazdil, Christophe G. Giraud-Carrier, P. Brazdil, 2017, Machine Learning.

Architecture for Iterative Learning of Recursive Definitions

Alípio Mário Jorge, Pavel Brazdil, P. Brazdil, 1996 .

Proceedings of the10th Portuguese Conference on Artificial Intelligence on Progress in Artificial Intelligence, Knowledge Extraction, Multi-agent Systems, Logic Programming and Constraint Solving

Alípio Mário Jorge, Pavel Brazdil, P. Brazdil, 2001 .

Introduction to the Special Issue on Meta-Learning

Ricardo Vilalta, Pavel Brazdil, Christophe G. Giraud-Carrier, 2004, Machine Learning.

Learning by Refining Algorithm Sketches

Alípio Mário Jorge, Pavel Brazdil, 1994, ECAI.

Linear tree

João Gama, Pavel Brazdil, 1999, Intell. Data Anal..

Introduction

Ryszard S. Michalski, Pavel Brazdil, 2003, Machine Learning.

A Comparative Study of Some Issues Concerning Algorithm Recommendation Using Ranking Methods

Carlos Soares, Pavel Brazdil, 2002, IBERAMIA.

Fast Algorithm Selection Using Learning Curves

Joaquin Vanschoren, Jan N. van Rijn, Pavel Brazdil, 2015, IDA.

Efficient Incremental Laplace Centrality Algorithm for Dynamic Networks

João Gama, Pavel Brazdil, Rui Portocarrero Sarmento, 2017, COMPLEX NETWORKS.

Market Basket Analysis

Johannes Fürnkranz, Luís Torgo, Thomas Stützle, 2010, Encyclopedia of Machine Learning.

A Meta-learning Approach to Improve Progressive Sampling

Pavel Brazdil, Rui Leite, 2004, PRIS.

Cost-Sensitive Decision Trees Applied to Medical Data

Pavel Brazdil, Altamiro da Costa Pereira, Alberto Freitas, 2007, DaWaK.

Selecting parameters of SVM using meta-learning and kernel matrix-based meta-features

Carlos Soares, Pavel Brazdil, 2006, SAC '06.

Learning Recursion with Iterative Bootstrap Induction (Extended Abstract)

Alípio Mário Jorge, Pavel Brazdil, 1995, ECML.

Proceedings of the 9th European conference on Principles and Practice of Knowledge Discovery in Databases

Luís Torgo, João Gama, Rui Camacho, 2005 .

Characterizing the Applicability of Classification Algorithms Using Meta-Level Learning

João Gama, Pavel Brazdil, Bob Henery, 1994, ECML.

Determining the Best Classification Algorithm with Recourse to Sampling and Metalearning

Pavel Brazdil, Rui Leite, 2010, Advances in Machine Learning I.

Improving Progressive Sampling via Meta-learning on Learning Curves

Pavel Brazdil, Rui Leite, P. Brazdil, 2004, ECML.

Integration of Knowledge in Multi-Agent Environments

Pavel Brazdil, P. Brazdil, 1992 .

Improving Progressive Sampling via Meta-learning

Pavel Brazdil, Rui Leite, 2003, EPIA.

Learning to Relate Terms in a Multiple Agent Environment

Stephen Muggleton, Pavel Brazdil, 1991, EWSL.

Learning from Imperfect Data

Peter Clark, Pavel Brazdil, P. Brazdil, 1990 .

Proceedings of the 3rd Planning to Learn Workshop (WS9) at ECAI 2010

Abraham Bernstein, Pavel Brazdil, Jörg-Uwe Kietz, 2010 .

Association and Temporality between News and Tweets

Pavel Brazdil, Vânia Moutinho, João Cordeiro, 2019, KDIR.

Organizational Survival In Cooperation Networks: The Case Of Automobile Manufacturing

Paula Brito, Pavel Brazdil, Pedro Campos, 2006, PRO-VE.

Metalearning - Applications to Data Mining

Ricardo Vilalta, Pavel Brazdil, Christophe G. Giraud-Carrier, 2008, Cognitive Technologies.

Experimental Learning Model

Pavel Brazdil, P. Brazdil, 1978, AISB/GI.

Proceedings of the 2015 International Workshop on Meta-Learning and Algorithm Selection (MetaSel 2015), Porto, Portugal, September 7, 2015

Lars Kotthoff, Joaquin Vanschoren, Pavel Brazdil, 2015 .

Approaches to Inductive Logic Programming

Pavel Brazdil, P. Brazdil, 1992, Advanced Topics in Artificial Intelligence.

Dynamic Laplace: Efficient Centrality Measure for Weighted or Unweighted Evolving Networks pdf

João Gama, Pavel Brazdil, Rui Portocarrero Sarmento, 2018, ArXiv.

On the Behavior of SVM and Some Older Algorithms in Binary Text Classification Tasks

Pavel Brazdil, Fabrice Colas, P. Brazdil, 2006, TSD.

Mean Squared Error

Johannes Fürnkranz, Luís Torgo, Thomas Stützle, 2010, Encyclopedia of Machine Learning.

Decision tree-based characterization for meta-learning

Peter A. Flach, Carlos Soares, Pavel Brazdil, 2002 .

Proceedings of the 12th International Conference on Discovery Science

João Gama, Alípio Mário Jorge, Pavel Brazdil, 2009 .

Redundant Covering with Global Evaluation in the RC1 Inductive Learner

Alneu de Andrade Lopes, Pavel Brazdil, 1998, SBIA.

Rule Induction for Sentence Reduction

João Cordeiro, Gaël Dias, Pavel Brazdil, 2013, EPIA.

Comparing Strategies of Collaborative Networks for R&D: An Agent-Based Study

Pavel Brazdil, Pedro Campos, Isabel Mota, 2013 .

Text Categorization Using an Ensemble Classifier Based on a Mean Co-association Matrix

Pavel Brazdil, João Mendes-Moreira, Luís Moreira-Matias, 2012, MLDM.

Comparison of SVM and Some Older Classification Algorithms in Text Classification Tasks

Pavel Brazdil, Fabrice Colas, P. Brazdil, 2006, IFIP AI.

Multistrategy Ensemble Learning

Johannes Fürnkranz, Luís Torgo, Thomas Stützle, 2010, Encyclopedia of Machine Learning.

Learning Paraphrases from WNS Corpora

João Cordeiro, Gaël Dias, Pavel Brazdil, 2007, FLAIRS Conference.

Measures to Evaluate Rankings of Classification Algorithms

Carlos Soares, Pavel Brazdil, Joaquim Pinto da Costa, 2000 .

Learning Simple Arithmetic

Pavel Brazdil, 1977, IJCAI.

Density-based graph model summarization: Attaining better performance and efficiency

Pavel Brazdil, Mohammadreza Valizadeh, 2015, Intell. Data Anal..

Using Meta-Learning to Support Data Mining

Ricardo Vilalta, Pavel Brazdil, Christophe G. Giraud-Carrier, 2004, Int. J. Comput. Sci. Appl..

Exploiting Sampling and Meta-learning for Parameter Setting forSupport Vector Machines

Carlos Soares, Pavel Brazdil, Adam Woznica, 2002 .

Incremental Approach for Automatic Generation of Domain-Specific Sentiment Lexicon

Pavel Brazdil, Shamsuddeen Hassan Muhammad, Alípio Jorge, 2020, ECIR.

Análise semântica de sentimento em artigos de opinião

Pavel Brazdil, Purificação Silvano, João Cordeiro, 2019 .

Multi-Armed Bandit

Johannes Fürnkranz, Luís Torgo, Katharina Morik, 2010, Encyclopedia of Machine Learning.

Missing Values

Johannes Fürnkranz, Luís Torgo, Thomas Stützle, 2010, Encyclopedia of Machine Learning.

Simplifying the Algorithm Selection Using Reduction of Rankings of Classification Algorithms

Pavel Brazdil, Alhassan Adamu, Salisu Mamman Abdulrahman, 2019, ICSCA.

Sentence Compression for Portuguese

Fernando Antônio Asevedo Nóbrega, Pavel Brazdil, Thiago A. S. Pardo, 2020, PROPOR.

TEXT SUMMARIZATION: USING CENTRALITY IN THE PATHFINDER NETWORK

Pavel Brazdil, Kaustubh Patil, Kaustubh K. Patil, 2007 .

Inductive Transfer

Ricardo Vilalta, Carlos Soares, Pavel Brazdil, 2010, Encyclopedia of Machine Learning.

Meta-learning to select the best meta-heuristic for the Traveling Salesman Problem: A comparison of meta-features

André Carlos Ponce de Leon Ferreira de Carvalho, Carlos Soares, Pavel Brazdil, 2016, Neurocomputing.

Inductive Transfer

Ricardo Vilalta, Carlos Soares, Pavel Brazdil, 2010, Encyclopedia of Machine Learning.

Proceedings of the European Conference on Machine Learning

Pavel Brazdil, P. Brazdil, 1993 .

Constructive Induction on Continuous Spaces

João Gama, Pavel Brazdil, João Gama, 1998 .

Cost-Sensitive Learning in Medicine

Pavel Brazdil, Altamiro Costa-Pereira, Alberto Freitas, 2009 .

A Meta-Learning Method to Select the Kernel Width in Support Vector Regression

Carlos Soares, Pavel Brazdil, Petr Kuba, 2004, Machine Learning.

Algorithm Selection via Meta-learning and Sample-based Active Testing

Joaquin Vanschoren, Jan N. van Rijn, Pavel Brazdil, 2015, MetaSel@PKDD/ECML.

Ranking Classification Algorithms Based on Relevant Performance Information

Carlos Soares, Pavel Brazdil, 2000 .

Proceedings of the 2014 International Conference on Meta-learning and Algorithm Selection - Volume 1201

Lars Kotthoff, Joaquin Vanschoren, Carlos Soares, 2014 .

Knowledge Discovery in Databases: PKDD 2005, 9th European Conference on Principles and Practice of Knowledge Discovery in Databases, Porto, Portugal, October 3-7, 2005, Proceedings

Luís Torgo, João Gama, Rui Camacho, 2005, PKDD.

Using active testing and meta-level information for selection of classification algorithms

Joaquin Vanschoren, Pavel Brazdil, Rui Leite, 2010 .

Combining Feature and Algorithm Hyperparameter Selection using some Metalearning Methods

Pavel Brazdil, Salisu Abdulrahman, Miguel Cachada, 2017, AutoML@PKDD/ECML.

Improving the Robustness and Encoding Complexity of Behavioural Clones

Rui Camacho, Pavel Brazdil, Rui Camacho, 2001, ECML.

Improved Dataset Characterisation for Meta-learning

Peter A. Flach, Yonghong Peng, Carlos Soares, 2002, Discovery Science.

Does SVM Really Scale Up to Large Bag of Words Feature Spaces?

Pavel Paclík, Joost N. Kok, Pavel Brazdil, 2007, IDA.

Machine Learning: ECML 2005, 16th European Conference on Machine Learning, Porto, Portugal, October 3-7, 2005, Proceedings

Luís Torgo, João Gama, Rui Camacho, 2005, ECML.

META-LEARNING AND ALGORITHM SELECTION WORKSHOP AT ECAI 2014

Lars Kotthoff, Joaquin Vanschoren, Carlos Soares, 2014 .

Combining regression models and metaheuristics to optimize space allocation in the retail industry

Fábio Pinto, Carlos Soares, Pavel Brazdil, 2015, Intell. Data Anal..

Knowledge Integration and Learning

Luís Torgo, Pavel Brazdil, Rua Campo Alegre, 1991 .

Identifying, Ranking and Tracking Community Leaders in Evolving Social Networks

Masahiro Kimura, João Gama, Pavel Brazdil, 2019, COMPLEX NETWORKS.

Selecting Classification Algorithms with Active Testing

Joaquin Vanschoren, Pavel Brazdil, Rui Leite, 2012, MLDM.

Report on the Experiments with Feature Selection in Meta-Level Learning

Carlos Soares, Pavel Brazdil, Ljupco Todorovski, 2000 .

Active Testing Strategy to Predict the Best Classification Algorithm via Sampling and Metalearning

Pavel Brazdil, Rui Leite, P. Brazdil, 2010, ECAI.

Cascade Generalization

João Gama, Pavel Brazdil, João Gama, 2000, Machine Learning.

Progress in Artificial Intelligence

Alípio Mário Jorge, Pavel Brazdil, P. Brazdil, 2002, Lecture Notes in Computer Science.

Impact of Feature Selection on Average Ranking Method via Metalearning

Pavel Brazdil, Salisu Mamman Abdulrahman, Miguel Viana Cachada, 2017 .

Proceedings of the 16th European conference on Machine Learning

Luís Torgo, João Gama, Rui Camacho, 2005 .

Microeconomic Model Based on MAS Framework: Modeling an Adaptive Producer

Pavel Brazdil, Frederico Teixeira, P. Brazdil, 2011 .

Measures for Combining Accuracy and Time for Meta-learning

Pavel Brazdil, Salisu Abdulrahman, 2014, MetaSel@ECAI.

Speeding up algorithm selection using average ranking and active testing by introducing runtime

Joaquin Vanschoren, Jan N. van Rijn, Pavel Brazdil, 2018, Machine Learning.

A Comparison of Ranking Methods for Classification Algorithm Selection

Carlos Soares, Pavel Brazdil, Carlos Soares, 2000, ECML.

On the Use of Fast Subsampling Estimates for Algorithm Recommendation

Johannes Fürnkranz, Carlos Soares, Pavel Brazdil, 2002 .

Integrity Constraints in ILP Using a Monte Carlo Approach

Alípio Mário Jorge, Pavel Brazdil, 1996, Inductive Logic Programming Workshop.

Predicting relative performance of classifiers from samples

Pavel Brazdil, Rui Leite, 2005, ICML '05.

Combining the Principal Components Method with Decision TreeLearning

Pavel Brazdil, Lubomír Popelínský, P. Brazdil, 2000 .

Retrieval, Visualization and Validation of Affinities between Documents

Pavel Brazdil, Martin Vita, Rui Sarmento, 2015, KMIS.

The Principal Components Method as a Pre-processing Stage forDecision Tree Learning

Pavel Brazdil, Lubomír Popelínský, 2000 .

Meta-Learning - Concepts and Techniques

Ricardo Vilalta, Pavel Brazdil, Christophe G. Giraud-Carrier, 2010, Data Mining and Knowledge Discovery Handbook.

Mean Absolute Error

Johannes Fürnkranz, Luís Torgo, Thomas Stützle, 2010, Encyclopedia of Machine Learning and Data Mining.

Inverse Resolution

Pierre Flener, Eamonn J. Keogh, Ricardo Vilalta, 2010, Encyclopedia of Machine Learning and Data Mining.

Ranking Classification Algorithms and Combinations of Methods

Pavel Brazdil, P. Brazdil, 2001, PRIS.

Exploring actor–object relationships for query-focused multi-document summarization

Pavel Brazdil, Mohammadreza Valizadeh, P. Brazdil, 2015, Soft Comput..

Abstract: The importance of considering costs in inductive learning

Pavel Brazdil, Altamiro Costa-Pereira, Alberto Freitas, 2012 .

A method of processing unknown attribute values by ID3

Pavel Brazdil, Ivan Bruha, 1992, Proceedings ICCI `92: Fourth International Conference on Computing and Information.

Evolving Networks and Social Network Analysis Methods and Techniques

João Gama, Pavel Brazdil, Rui Portocarrero Sarmento, 2018, Social Media and Journalism - Trends, Connections, Implications.

Paraphrase Alignment for Synonym Evidence Discovery

João Cordeiro, Gaël Dias, Pavel Brazdil, 2010, COLING.

Effect of Incomplete Meta-dataset on Average Ranking Method pdf

Pavel Brazdil, Salisu Abdulrahman, P. Brazdil, 2016, AutoML@ICML.

Unsupervised Induction of Sentence Compression Rules

Gaël Dias, Pavel Brazdil, Joao Cordeiro, 2009 .

Induction with Subtheory Selection

Pavel Brazdil, P. Brazdil, 2007 .

Learning Text Extraction Rules, without Ignoring Stop Words

João Cordeiro, Pavel Brazdil, P. Brazdil, 2004, PRIS.

Progress in artificial intelligence : knowledge extraction, multi-agent systems, logic programming, and constraint solving : 10th Portuguese Conference on Artificial Intelligence, EPIA 2001, Porto, Portugal, December 17-20, 2001 : proceedings

Alípio Mário Jorge, Pavel Brazdil, 2001 .

PKDD2000 workshop on Data Mining, Decision Support, Meta-learning and ILP : Forum for Practical Problem Presentation and Prospective Solutions

Peter A. Flach, Nicolas Lachiche, Alípio Mário Jorge, 2000 .

An Iterative Process for Building Learning Curves and Predicting Relative Performance of Classifiers

Pavel Brazdil, Rui Leite, P. Brazdil, 2007, EPIA Workshops.

Towards a Human-AI Hybrid Framework for Inter-Researcher Similarity Detection

António Correia, Pavel Brazdil, Luís Trigo, 2021, 2021 IEEE 2nd International Conference on Human-Machine Systems (ICHMS).

Text documents streams with improved incremental similarity

João Gama, Pavel Brazdil, Rui Portocarrero Sarmento, 2021, Social Network Analysis and Mining.

NaijaSenti: A Nigerian Twitter Sentiment Corpus for Multilingual Sentiment Analysis

Monojit Choudhury, Pavel Brazdil, David Ifeoluwa Adelani, 2022, LREC.

Factors influencing hospital high length of stay outliers

Pavel Brazdil, Armando Teixeira-Pinto, Altamiro Costa-Pereira, 2012, BMC Health Services Research.

International Workshop on Meta-Learning and Algorithm Selection (MetaSel 2015, Porto, Portugal September 7, 2015; co-located with ECMLPKDD 2015)

Lars Kotthoff, Joaquin Vanschoren, Pavel Brazdil, 2015 .

Selecting Classification Algorithms with Active Testing on Similar Datasets

Joaquin Vanschoren, Pavel Brazdil, Rui Leite, 2012 .