Pawel Teisseyre

41 papers A 5B 2Journal 26Unranked 7
YearRankTypeTitle / Venue / Authors
2026 B conf
Detecting Propensity Score Shifts Across Groups in Positive-Unlabeled Data.
IDA
Illia Tesliuk, Pawel Teisseyre
2025 A conf
A Generalized Approach to Label Shift: The Conditional Probability Shift Model.
ECAI
Pawel Teisseyre, Jan Mielniczuk
2025 J jnl
A generalized approach to label shift: the Conditional Probability Shift Model.
CoRR
Pawel Teisseyre, Jan Mielniczuk
2025 J jnl
Class prior estimation for positive-unlabeled learning when label shift occurs.
CoRR
Jan Mielniczuk, Wojciech Rejchel, Pawel Teisseyre
2025 A conf
Learning from biased positive-unlabeled data via threshold calibration.
AISTATS
Pawel Teisseyre, Timo Martens, Jessa Bekker, Jesse Davis
2024 J jnl
A Short Survey and Comparison of CNN-Based Music Genre Classification Using Multiple Spectral Features.
IEEE Access
Wangduk Seo, Sung-Hyun Cho, Pawel Teisseyre, Jaesung Lee
2024 J jnl
Cost-constrained multi-label group feature selection using shadow features.
CoRR
Tomasz Klonecki, Pawel Teisseyre, Jaesung Lee
2024 J jnl
Joint empirical risk minimization for instance-dependent positive-unlabeled data.
Knowl. Based Syst.
Wojciech Rejchel, Pawel Teisseyre, Jan Mielniczuk
2024 A conf
Verifying the Selected Completely at Random Assumption in Positive-Unlabeled Learning.
ECAI
Pawel Teisseyre, Konrad Furmanczyk, Jan Mielniczuk
2024 J jnl
Verifying the Selected Completely at Random Assumption in Positive-Unlabeled Learning.
CoRR
Pawel Teisseyre, Konrad Furmanczyk, Jan Mielniczuk
2023 B conf
Cost-constrained Group Feature Selection Using Information Theory.
MDAI
Tomasz Klonecki, Pawel Teisseyre, Jaesung Lee
2023 J jnl
Cost-constrained feature selection in multilabel classification using an information-theoretic approach.
Pattern Recognit.
Tomasz Klonecki, Pawel Teisseyre, Jaesung Lee
2023 A conf
Double Logistic Regression Approach to Biased Positive-Unlabeled Data.
ECAI
Konrad Furmanczyk, Jan Mielniczuk, Wojciech Rejchel, Pawel Teisseyre
2023 J jnl
Effective Exploitation of Macroeconomic Indicators for Stock Direction Classification Using the Multimodal Fusion Transformer.
IEEE Access
Tae-Won Lee, Pawel Teisseyre, Jaesung Lee
2023 J jnl
Feature selection under budget constraint in medical applications: analysis of penalized empirical risk minimization methods.
Appl. Intell.
Tomasz Klonecki, Pawel Teisseyre
2023 J jnl
Joint empirical risk minimization for instance-dependent positive-unlabeled data.
CoRR
Wojciech Rejchel, Pawel Teisseyre, Jan Mielniczuk
2023 J jnl
Multilabel all-relevant feature selection using lower bounds of conditional mutual information.
Expert Syst. Appl.
Pawel Teisseyre, Jaesung Lee
2022 J jnl
Joint Feature Selection and Classification for Positive Unlabelled Multi-Label Data Using Weighted Penalized Empirical Risk Minimization.
Int. J. Appl. Math. Comput. Sci.
Pawel Teisseyre
2022 J jnl
Joint estimation of posterior probability and propensity score function for positive and unlabelled data.
CoRR
Konrad Furmanczyk, Jan Mielniczuk, Wojciech Rejchel, Pawel Teisseyre
2021 J jnl
Classifier chains for positive unlabelled multi-label learning.
Knowl. Based Syst.
Pawel Teisseyre
2021 — conf
Controlling Costs in Feature Selection: Information Theoretic Approach.
ICCS (2)
Pawel Teisseyre, Tomasz Klonecki
2021 — conf
Detection of Conditional Dependence Between Multiple Variables Using Multiinformation.
ICCS (6)
Jan Mielniczuk, Pawel Teisseyre
2021 J jnl
Estimating the class prior for positive and unlabelled data via logistic regression.
Adv. Data Anal. Classif.
Malgorzata Lazecka, Jan Mielniczuk, Pawel Teisseyre
2021 J jnl
How to Gain on Power: Novel Conditional Independence Tests Based on Short Expansion of Conditional Mutual Information.
J. Mach. Learn. Res.
Mariusz Kubkowski, Jan Mielniczuk, Pawel Teisseyre
2020 — conf
Different Strategies of Fitting Logistic Regression for Positive and Unlabelled Data.
ICCS (4)
Pawel Teisseyre, Jan Mielniczuk, Malgorzata Lazecka
2020 A conf
Learning Classifier Chains Using Matrix Regularization: Application to Multimorbidity Prediction.
ECAI
Pawel Teisseyre
2020 — conf
Testing the Significance of Interactions in Genetic Studies Using Interaction Information and Resampling Technique.
ICCS (3)
Pawel Teisseyre, Jan Mielniczuk, Michal J. Dabrowski
2019 J jnl
Cost-sensitive classifier chains: Selecting low-cost features in multi-label classification.
Pattern Recognit.
Pawel Teisseyre, Damien Zufferey, Marta Slomka
2019 J jnl
Stopping rules for mutual information-based feature selection.
Neurocomputing
Jan Mielniczuk, Pawel Teisseyre
2018 — conf
Information-Theoretic Feature Selection Using High-Order Interactions.
LOD
Mateusz Pawluk, Pawel Teisseyre, Jan Mielniczuk
2017 J jnl
CCnet: Joint multi-label classification and feature selection using classifier chains and elastic net regularization.
Neurocomputing
Pawel Teisseyre
2017 J jnl
Diversity of editors and teams versus quality of cooperative work: experiments on wikipedia.
J. Intell. Inf. Syst.
Marcin Sydow, Katarzyna Baraniak, Pawel Teisseyre
2016 J jnl
Asymptotic consistency and order specification for logistic classifier chains in multi-label learning.
CoRR
Pawel Teisseyre
2016 J jnl
Feature ranking for multi-label classification using Markov Networks.
CoRR
Pawel Teisseyre
2016 J jnl
Feature ranking for multi-label classification using Markov networks.
Neurocomputing
Pawel Teisseyre
2016 J jnl
Random Subspace Method for high-dimensional regression with the R package regRSM.
Comput. Stat.
Pawel Teisseyre, Robert A. Klopotek, Jan Mielniczuk
2016 — ch.
What Do We Choose When We Err? Model Selection and Testing for Misspecified Logistic Regression Revisited.
Challenges in Computational Statistics and Data Mining
Jan Mielniczuk, Pawel Teisseyre
2015 — conf
What Do Your Look-alikes Say about You? Exploiting Strong and Weak Similarities for Author Profiling.
CLEF (Working Notes)
Piotr Przybyla, Pawel Teisseyre
2014 J jnl
Analysing Utterances in Polish Parliament to Predict Speaker's Background.
J. Quant. Linguistics
Piotr Przybyla, Pawel Teisseyre
2014 J jnl
Using random subspace method for prediction and variable importance assessment in linear regression.
Comput. Stat. Data Anal.
Jan Mielniczuk, Pawel Teisseyre
2011 — conf
Model Selection in Logistic Regression Using p-Values and Greedy Search.
SIIS
Jan Mielniczuk, Pawel Teisseyre