Pawel Teisseyre

Orcid: 0000-0002-4296-9819

According to our database1, Pawel Teisseyre authored at least 33 papers between 2011 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Joint empirical risk minimization for instance-dependent positive-unlabeled data.
Knowl. Based Syst., 2024

Cost-constrained multi-label group feature selection using shadow features.
CoRR, 2024

A Short Survey and Comparison of CNN-Based Music Genre Classification Using Multiple Spectral Features.
IEEE Access, 2024

Verifying the Selected Completely at Random Assumption in Positive-Unlabeled Learning.
Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

2023
Feature selection under budget constraint in medical applications: analysis of penalized empirical risk minimization methods.
Appl. Intell., December, 2023

Cost-constrained feature selection in multilabel classification using an information-theoretic approach.
Pattern Recognit., September, 2023

Multilabel all-relevant feature selection using lower bounds of conditional mutual information.
Expert Syst. Appl., April, 2023

Effective Exploitation of Macroeconomic Indicators for Stock Direction Classification Using the Multimodal Fusion Transformer.
IEEE Access, 2023

Cost-constrained Group Feature Selection Using Information Theory.
Proceedings of the Modeling Decisions for Artificial Intelligence, 2023

Double Logistic Regression Approach to Biased Positive-Unlabeled Data.
Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

2022
Joint estimation of posterior probability and propensity score function for positive and unlabelled data.
CoRR, 2022

Joint Feature Selection and Classification for Positive Unlabelled Multi-Label Data Using Weighted Penalized Empirical Risk Minimization.
Int. J. Appl. Math. Comput. Sci., 2022

2021
Classifier chains for positive unlabelled multi-label learning.
Knowl. Based Syst., 2021

How to Gain on Power: Novel Conditional Independence Tests Based on Short Expansion of Conditional Mutual Information.
J. Mach. Learn. Res., 2021

Estimating the class prior for positive and unlabelled data via logistic regression.
Adv. Data Anal. Classif., 2021

Controlling Costs in Feature Selection: Information Theoretic Approach.
Proceedings of the Computational Science - ICCS 2021, 2021

Detection of Conditional Dependence Between Multiple Variables Using Multiinformation.
Proceedings of the Computational Science - ICCS 2021, 2021

2020
Different Strategies of Fitting Logistic Regression for Positive and Unlabelled Data.
Proceedings of the Computational Science - ICCS 2020, 2020

Testing the Significance of Interactions in Genetic Studies Using Interaction Information and Resampling Technique.
Proceedings of the Computational Science - ICCS 2020, 2020

Learning Classifier Chains Using Matrix Regularization: Application to Multimorbidity Prediction.
Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

2019
Cost-sensitive classifier chains: Selecting low-cost features in multi-label classification.
Pattern Recognit., 2019

Stopping rules for mutual information-based feature selection.
Neurocomputing, 2019

2018
Information-Theoretic Feature Selection Using High-Order Interactions.
Proceedings of the Machine Learning, Optimization, and Data Science, 2018

2017
Diversity of editors and teams versus quality of cooperative work: experiments on wikipedia.
J. Intell. Inf. Syst., 2017

CCnet: Joint multi-label classification and feature selection using classifier chains and elastic net regularization.
Neurocomputing, 2017

2016
What Do We Choose When We Err? Model Selection and Testing for Misspecified Logistic Regression Revisited.
Proceedings of the Challenges in Computational Statistics and Data Mining, 2016

Feature ranking for multi-label classification using Markov networks.
Neurocomputing, 2016

Random Subspace Method for high-dimensional regression with the R package regRSM.
Comput. Stat., 2016

Asymptotic consistency and order specification for logistic classifier chains in multi-label learning.
CoRR, 2016

2015
What Do Your Look-alikes Say about You? Exploiting Strong and Weak Similarities for Author Profiling.
Proceedings of the Working Notes of CLEF 2015, 2015

2014
Analysing Utterances in Polish Parliament to Predict Speaker's Background.
J. Quant. Linguistics, 2014

Using random subspace method for prediction and variable importance assessment in linear regression.
Comput. Stat. Data Anal., 2014

2011
Model Selection in Logistic Regression Using p-Values and Greedy Search.
Proceedings of the Security and Intelligent Information Systems, 2011


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