Jan Mielniczuk

Publication Activity (10 Years)

Years Active: 1993-2024
Publications (10 Years): 28

Top Topics

Mutual Information

Unlabelled Data

Logistic Regression

Top Venues

J. Mach. Learn. Res.

Publications

Jan Mielniczuk, Adam Wawrzenczyk
Augmented prediction of a true class for Positive Unlabeled data under selection bias. CoRR (2024)
Pawel Teisseyre, Konrad Furmanczyk, Jan Mielniczuk
Verifying the Selected Completely at Random Assumption in Positive-Unlabeled Learning. CoRR (2024)
Mateusz Platek, Jan Mielniczuk
Enhancing naive classifier for positive unlabeled data based on logistic regression approach. FedCSIS (2023)
Jan Mielniczuk, Adam Wawrzenczyk
Single-sample versus case-control sampling scheme for Positive Unlabeled data: the story of two scenarios. CoRR (2023)
Mateusz Platek, Jan Mielniczuk
Enhancing naive classifier for positive unlabeled data based on logistic regression approach. CoRR (2023)
Jan Mielniczuk, Adam Wawrzenczyk
One-Class Classification Approach to Variational Learning from Biased Positive Unlabeled Data. ECAI (2023)
Konrad Furmanczyk, Jan Mielniczuk, Wojciech Rejchel, Pawel Teisseyre
Double Logistic Regression Approach to Biased Positive-Unlabeled Data. ECAI (2023)
Wojciech Rejchel, Pawel Teisseyre, Jan Mielniczuk
Joint empirical risk minimization for instance-dependent positive-unlabeled data. CoRR (2023)
Adam Wawrzenczyk, Jan Mielniczuk
Outlier Detection Under False Omission Rate Control. ICCS (3) (2023)
Konrad Furmanczyk, Jan Mielniczuk, Wojciech Rejchel, Pawel Teisseyre
Joint estimation of posterior probability and propensity score function for positive and unlabelled data. CoRR (2022)
Adam Wawrzenczyk, Jan Mielniczuk
Revisiting Strategies for Fitting Logistic Regression for Positive and Unlabeled Data. Int. J. Appl. Math. Comput. Sci. 32 (2) (2022)
Jan Mielniczuk
Nonparametric Statistical Inference with an Emphasis on Information-Theoretic Methods. Entropy 24 (4) (2022)
Jan Mielniczuk
Information Theoretic Methods for Variable Selection - A Review. Entropy 24 (8) (2022)
Mariusz Kubkowski, Jan Mielniczuk, Pawel Teisseyre
How to Gain on Power: Novel Conditional Independence Tests Based on Short Expansion of Conditional Mutual Information. J. Mach. Learn. Res. 22 (2021)
Malgorzata Lazecka, Jan Mielniczuk
Multiple Testing of Conditional Independence Hypotheses Using Information-Theoretic Approach. MDAI (2021)
Jan Mielniczuk, Pawel Teisseyre
Detection of Conditional Dependence Between Multiple Variables Using Multiinformation. ICCS (6) (2021)
Malgorzata Lazecka, Jan Mielniczuk, Pawel Teisseyre
Estimating the class prior for positive and unlabelled data via logistic regression. Adv. Data Anal. Classif. 15 (4) (2021)
Mariusz Kubkowski, Malgorzata Lazecka, Jan Mielniczuk
Distributions of a General Reduced-Order Dependence Measure and Conditional Independence Testing. ICCS (7) (2020)
Pawel Teisseyre, Jan Mielniczuk, Michal J. Dabrowski
Testing the Significance of Interactions in Genetic Studies Using Interaction Information and Resampling Technique. ICCS (3) (2020)
Pawel Teisseyre, Jan Mielniczuk, Malgorzata Lazecka
Different Strategies of Fitting Logistic Regression for Positive and Unlabelled Data. ICCS (4) (2020)
Mariusz Kubkowski, Jan Mielniczuk
Selection Consistency of Lasso-Based Procedures for Misspecified High-Dimensional Binary Model and Random Regressors. Entropy 22 (2) (2020)
Malgorzata Lazecka, Jan Mielniczuk
Analysis of Information-Based Nonparametric Variable Selection Criteria. Entropy 22 (9) (2020)
Jan Mielniczuk, Pawel Teisseyre
Stopping rules for mutual information-based feature selection. Neurocomputing 358 (2019)
Mariusz Kubkowski, Jan Mielniczuk
Selection consistency of Lasso-based procedures for misspecified high-dimensional binary model and random regressors. CoRR (2019)
Mateusz Pawluk, Pawel Teisseyre, Jan Mielniczuk
Information-Theoretic Feature Selection Using High-Order Interactions. LOD (2018)
Jan Mielniczuk, Marcin Rdzanowski
Use of Information Measures and Their Approximations to Detect Predictive Gene-Gene Interaction. Entropy 19 (1) (2017)
Pawel Teisseyre, Robert A. Klopotek, Jan Mielniczuk
Random Subspace Method for high-dimensional regression with the R package regRSM. Comput. Stat. 31 (3) (2016)
Piotr Pokarowski, Jan Mielniczuk
Combined l1 and greedy l0 penalized least squares for linear model selection. J. Mach. Learn. Res. 16 (2015)
Jan Mielniczuk, Pawel Teisseyre
Using random subspace method for prediction and variable importance assessment in linear regression. Comput. Stat. Data Anal. 71 (2014)
Jan Mielniczuk, Pawel Teisseyre
Model Selection in Logistic Regression Using p-Values and Greedy Search. SIIS (2011)
Jan Mielniczuk, Piotr Wojdyllo
Decorrelation of Wavelet Coefficients for Long-Range Dependent Processes. IEEE Trans. Inf. Theory 53 (5) (2007)
Jan Mielniczuk, Piotr Wojdyllo
Estimation of Hurst exponent revisited. Comput. Stat. Data Anal. 51 (9) (2007)
Jan Mielniczuk, Joanna Tyrcha
Consistency of multilayer perceptron regression estimators. Neural Networks 6 (7) (1993)