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Information Theoretic Methods for Variable Selection—A Review

Entropy (Basel, Switzerland), 2022-08, Vol.24 (8), p.1079

Mielniczuk, Jan

2022

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Nonparametric Statistical Inference with an Emphasis on Information-Theoretic Methods

Entropy (Basel, Switzerland), 2022-04, Vol.24 (4), p.553

Mielniczuk, Jan

2022

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Analysis of conditional randomisation and permutation schemes with application to conditional independence testing

Test (Madrid, Spain), 2023-12, Vol.32 (4), p.1459-1478

2023

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Asymptotic Distributions of Empirical Interaction Information

Methodology and computing in applied probability, 2021-03, Vol.23 (1), p.291-315

2021

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Revisiting strategies for fitting logistic regression for positive and unlabeled data

International journal of applied mathematics and computer science, 2022-06, Vol.32 (2)

2022

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Selection Consistency of Lasso-Based Procedures for Misspecified High-Dimensional Binary Model and Random Regressors

Entropy (Basel, Switzerland), 2020-01, Vol.22 (2), p.153

2020

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Estimating the class prior for positive and unlabelled data via logistic regression

Advances in data analysis and classification, 2021-12, Vol.15 (4), p.1039-1068

2021

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Analysis of Information-Based Nonparametric Variable Selection Criteria

Entropy (Basel, Switzerland), 2020-08, Vol.22 (9), p.974

2020

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Nonparametric Statistical Inference with an Emphasis on Information-Theoretic Methods

Mielniczuk, Jan

2022

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Use of Information Measures and Their Approximations to Detect Predictive Gene-Gene Interaction

Entropy (Basel, Switzerland), 2017-01, Vol.19 (1), p.23-23

2017

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Using random subspace method for prediction and variable importance assessment in linear regression

Computational statistics & data analysis, 2014-03, Vol.71, p.725-742

2014

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Searching for improvements in predicting human eye colour from DNA

International journal of legal medicine, 2021-11, Vol.135 (6), p.2175-2187

2021

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Challenges in Computational Statistics and Data Mining

1st ed. 2016., 2015

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Stopping rules for mutual information-based feature selection

Neurocomputing (Amsterdam), 2019-09, Vol.358, p.255-274

2019

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Projections of a general binary model on a logistic regression

Linear algebra and its applications, 2018-01, Vol.536, p.152-173

2018

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Dealing with Data Difficulty Factors While Learning from Imbalanced Data

Challenges in Computational Statistics and Data Mining, 2016, Vol.605, p.333-363

2016

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Joint empirical risk minimization for instance-dependent positive-unlabeled data

Knowledge-based systems, 2024-11, Vol.304, p.112444, Article 112444

2024

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Squared error-based shrinkage estimators of discrete probabilities and their application to variable selection

Statistical papers (Berlin, Germany), 2023-02, Vol.64 (1), p.41-72

2023

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A deeper look at two concepts of measuring gene–gene interactions: logistic regression and interaction information revisited

Genetic epidemiology, 2018-03, Vol.42 (2), p.187-200

2018

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Improving Lasso for model selection and prediction

Scandinavian journal of statistics, 2022-06, Vol.49 (2), p.831-863

2022

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Multiple Testing of Conditional Independence Hypotheses Using Information-Theoretic Approach

Modeling Decisions for Artificial Intelligence, p.81-92

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Predicting Physical Appearance from DNA Data-Towards Genomic Solutions

Genes, 2022-01, Vol.13 (1), p.121

2022

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Detection of Conditional Dependence Between Multiple Variables Using Multiinformation

Computational Science – ICCS 2021, p.677-690

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Normalized and standard Dantzig estimators: Two approaches

Electronic journal of statistics, 2015-01, Vol.9 (1)

2015

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value model selection criteria for exponential families of increasing dimension

Metrika, 2014-02, Vol.77 (2), p.257-284

2014

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Information Theoretic Methods for Variable Selection—A Review

Nonparametric Statistical Inference with an Emphasis on Information-Theoretic Methods

Analysis of conditional randomisation and permutation schemes with application to conditional independence testing

Asymptotic Distributions of Empirical Interaction Information

Revisiting strategies for fitting logistic regression for positive and unlabeled data

Selection Consistency of Lasso-Based Procedures for Misspecified High-Dimensional Binary Model and Random Regressors

Estimating the class prior for positive and unlabelled data via logistic regression

Analysis of Information-Based Nonparametric Variable Selection Criteria

Nonparametric Statistical Inference with an Emphasis on Information-Theoretic Methods

Use of Information Measures and Their Approximations to Detect Predictive Gene-Gene Interaction

Using random subspace method for prediction and variable importance assessment in linear regression

Searching for improvements in predicting human eye colour from DNA

Challenges in Computational Statistics and Data Mining

Stopping rules for mutual information-based feature selection

Projections of a general binary model on a logistic regression

Dealing with Data Difficulty Factors While Learning from Imbalanced Data

Joint empirical risk minimization for instance-dependent positive-unlabeled data

Squared error-based shrinkage estimators of discrete probabilities and their application to variable selection

A deeper look at two concepts of measuring gene–gene interactions: logistic regression and interaction information revisited

Improving Lasso for model selection and prediction

Multiple Testing of Conditional Independence Hypotheses Using Information-Theoretic Approach

Predicting Physical Appearance from DNA Data-Towards Genomic Solutions

Detection of Conditional Dependence Between Multiple Variables Using Multiinformation

Normalized and standard Dantzig estimators: Two approaches

value model selection criteria for exponential families of increasing dimension

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