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Unsupervised feature selection with ensemble learning

Machine learning, 2015-01, Vol.98 (1-2), p.157-180

2015

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A hybrid algorithm for Bayesian network structure learning with application to multi-label learning

Expert systems with applications, 2014-11, Vol.41 (15), p.6755-6772

2014

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Answering Student Queries with a Supervised Memory Conversational Agent

The International FLAIRS Conference Proceedings, 2023, Vol.36

2023

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Ensemble multi-label text categorization based on rotation forest and latent semantic indexing

Expert systems with applications, 2016-09, Vol.57, p.1-11

2016

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Analysis of lifestyle and metabolic predictors of visceral obesity with Bayesian Networks

BMC bioinformatics, 2010-09, Vol.11 (1), p.487-487, Article 487

2010

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A semi-supervised feature ranking method with ensemble learning

Pattern recognition letters, 2012-07, Vol.33 (10), p.1426-1433

2012

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Bayesian networks

Neurocomputing (Amsterdam), 2010, Vol.73 (4), p.561-562

Aussem, Alex

2010

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An extensive empirical comparison of ensemble learning methods for binary classification

Pattern analysis and applications : PAA, 2016-11, Vol.19 (4), p.1093-1128

2016

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A Comparison of Multi-Label Feature Selection Methods Using the Random Forest Paradigm

Advances in Artificial Intelligence, p.95-106

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Dynamic Ensemble Selection with Probabilistic Classifier Chains

Machine Learning and Knowledge Discovery in Databases, p.169-186

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On the use of binary stochastic autoencoders for multi-label classification under the zero-one loss

Procedia computer science, 2018, Vol.144, p.71-80

2018

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An Experimental Comparison of Hybrid Algorithms for Bayesian Network Structure Learning

Lecture notes in computer science, 2012, Vol.7523, p.58-73

2012

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A novel Markov boundary based feature subset selection algorithm

Neurocomputing (Amsterdam), 2010-01, Vol.73 (4), p.578-584

2010

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Data-Efficient Information Extraction from Documents with Pre-trained Language Models

Document Analysis and Recognition – ICDAR 2021 Workshops, p.455-469

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F-Measure Maximization in Multi-Label Classification with Conditionally Independent Label Subsets

Machine Learning and Knowledge Discovery in Databases, 2016, Vol.9851, p.619-631

2016

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A conservative feature subset selection algorithm with missing data

Neurocomputing (Amsterdam), 2010-01, Vol.73 (4), p.585-590

2010

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Analysis of nasopharyngeal carcinoma risk factors with Bayesian networks

Artificial intelligence in medicine, 2012-01, Vol.54 (1), p.53-62

2012

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Sufficient Conditions for Error Backflow Convergence in Dynamical Recurrent Neural Networks

Neural computation, 2002-08, Vol.14 (8), p.1907-1927

Aussem, Alex

2002

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Closed Loop Stability of FIR-Recurrent Neural Networks

Artificial Neural Networks and Neural Information Processing — ICANN/ICONIP 2003, 2003, p.523-529

2003

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A Practical Approach to Reduce the Learning Bias Under Covariate Shift

Machine Learning and Knowledge Discovery in Databases, p.71-86

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Calibrated k-labelsets for Ensemble Multi-label Classification

Neural Information Processing, 2015, Vol.9489, p.573-582

2015

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Dynamical recurrent neural networks towards prediction and modeling of dynamical systems

Neurocomputing (Amsterdam), 1999, Vol.28 (1), p.207-232

Aussem, Alex

1999

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Learning the local Bayesian network structure around the ZNF217 oncogene in breast tumours

Computers in biology and medicine, 2013-05, Vol.43 (4), p.334-341

2013

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Combining Neural Network Forecasts on Wavelet-transformed Time Series

Connection science, 1997-03, Vol.9 (1), p.113-122

1997

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Recurrent Neural Network Approach for Table Field Extraction in Business Documents

2019 International Conference on Document Analysis and Recognition (ICDAR), 2019, p.1308-1313

2019

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Unsupervised feature selection with ensemble learning

A hybrid algorithm for Bayesian network structure learning with application to multi-label learning

Answering Student Queries with a Supervised Memory Conversational Agent

Ensemble multi-label text categorization based on rotation forest and latent semantic indexing

Analysis of lifestyle and metabolic predictors of visceral obesity with Bayesian Networks

A semi-supervised feature ranking method with ensemble learning

Bayesian networks

An extensive empirical comparison of ensemble learning methods for binary classification

A Comparison of Multi-Label Feature Selection Methods Using the Random Forest Paradigm

Dynamic Ensemble Selection with Probabilistic Classifier Chains

On the use of binary stochastic autoencoders for multi-label classification under the zero-one loss

An Experimental Comparison of Hybrid Algorithms for Bayesian Network Structure Learning

A novel Markov boundary based feature subset selection algorithm

Data-Efficient Information Extraction from Documents with Pre-trained Language Models

F-Measure Maximization in Multi-Label Classification with Conditionally Independent Label Subsets

A conservative feature subset selection algorithm with missing data

Analysis of nasopharyngeal carcinoma risk factors with Bayesian networks

Sufficient Conditions for Error Backflow Convergence in Dynamical Recurrent Neural Networks

Closed Loop Stability of FIR-Recurrent Neural Networks

A Practical Approach to Reduce the Learning Bias Under Covariate Shift

Calibrated k-labelsets for Ensemble Multi-label Classification

Dynamical recurrent neural networks towards prediction and modeling of dynamical systems

Learning the local Bayesian network structure around the ZNF217 oncogene in breast tumours

Combining Neural Network Forecasts on Wavelet-transformed Time Series

Recurrent Neural Network Approach for Table Field Extraction in Business Documents

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