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Nathalie Japkowicz

Nathalie Japkowicz

D-Index & Metrics

Computer Science

D-Index
45
Citations
24450
World Ranking
6974
National Ranking
3053

Overview

Nathalie Japkowicz is affiliated with American University in the United States and has contributed extensively to the field of Computer Science, with a focus on Artificial Intelligence. Their research spans multiple subfields including Signal Processing, Sociology and Political Science, Radiology, Nuclear Medicine and Imaging, and Computer Networks and Communications.

The scientist has published significant work on topics such as anomaly detection techniques and applications, imbalanced data classification techniques, misinformation and its impacts, network security and intrusion detection, COVID-19 diagnosis using AI, hate speech and cyberbullying detection, and data stream mining techniques.

Recent notable papers include:

  • "The class imbalance problem in deep learning" (2022) published in Machine Learning
  • "Machine-Generated Text: A Comprehensive Survey of Threat Models and Detection Methods" (2023) published in IEEE Access
  • "On the joint-effect of class imbalance and overlap: a critical review" (2022) published in Artificial Intelligence Review
  • "A unifying view of class overlap and imbalance: Key concepts, multi-view panorama, and open avenues for research" (2022) published in Information Fusion
  • "Research on unsupervised feature learning for Android malware detection based on Restricted Boltzmann Machines" (2021) published in Future Generation Computer Systems

Japkowicz has frequently collaborated with several researchers, including Roberto Corizzo, Evan Crothers, Zois Boukouvalas, Kamil Faber, and Herna L. Viktor.

Their work has appeared in various publication venues with multiple contributions to:

  • arXiv (Cornell University)
  • Machine Learning
  • IEEE Access
  • 2021 IEEE International Conference on Big Data (Big Data)
  • 2022 International Joint Conference on Neural Networks (IJCNN)

Japkowicz has also authored a book titled Machine Learning Evaluation, published in 2024 by Cambridge University Press.

Best Publications

  • The class imbalance problem: A systematic study

    Nathalie Japkowicz;Shaju Stephen

  • Editorial: special issue on learning from imbalanced data sets

    Nitesh V. Chawla;Nathalie Japkowicz;Aleksander Kotcz

  • SPECIAL ISSUE ON LEARNING FROM IMBALANCED DATA SETS

    N Chawla;N Japkowicz;A Kolcz

  • Beyond accuracy, f-score and ROC: a family of discriminant measures for performance evaluation

    Marina Sokolova;Nathalie Japkowicz;Stan Szpakowicz

  • Applying support vector machines to imbalanced datasets

    Rehan Akbani;Stephen Kwek;Nathalie Japkowicz

  • A Multiple Resampling Method for Learning from Imbalanced Data Sets

    Andrew Estabrooks;Taeho Jo;Nathalie Japkowicz

  • Evaluating Learning Algorithms: A Classification Perspective

    Nathalie Japkowicz;Mohak Shah

  • Class imbalances versus small disjuncts

    Taeho Jo;Nathalie Japkowicz

  • Learning from Imbalanced Data Sets: A Comparison of Various Strategies *

    Nathalie Japkowicz

  • A novelty detection approach to classification

    Nathalie Japkowicz;Catherine Myers;Mark Gluck

  • Anomaly Detection in Automobile Control Network Data with Long Short-Term Memory Networks

    Adrian Taylor;Sylvain Leblanc;Nathalie Japkowicz

  • Boosting support vector machines for imbalanced data sets

    Benjamin X. Wang;Nathalie Japkowicz

  • Evaluating Learning Algorithms: Contents

    Unknown

  • Frequency-based anomaly detection for the automotive CAN bus

    Adrian Taylor;Nathalie Japkowicz;Sylvain Leblanc

  • Nonlinear Autoassociation Is Not Equivalent to PCA

    Nathalie Japkowicz;Stephen Jose Hanson;Mark A. Gluck

  • Concept-Learning in the Presence of Between-Class and Within-Class Imbalances

    Nathalie Japkowicz

  • Supervised Versus Unsupervised Binary-Learning by Feedforward Neural Networks

    Nathalie Japkowicz

  • Machine-Generated Text: A Comprehensive Survey of Threat Models and Detection Methods

    Unknown

  • A Feature Selection and Evaluation Scheme for Computer Virus Detection

    Olivier Henchiri;Nathalie Japkowicz

  • Concept learning in the absence of counterexamples: an autoassociation-based approach to classification

    Nathalie Japkowicz;Jose Hanson;Casimir Kulikowski

  • A Mixture-of-Experts Framework for Learning from Imbalanced Data Sets

    Andrew Estabrooks;Nathalie Japkowicz

  • Canadian Conference on Artificial Intelligence

    William Klement;Peter A Flach;Nathalie Japkowicz;Stan Matwin

  • Privacy-preserving collaborative association rule mining

    Justin Zhan;Stan Matwin;LiWu Chang

Frequent Co-Authors

Stan Matwin
Stan Matwin Dalhousie University
Michelangelo Ceci
Michelangelo Ceci University of Bari Aldo Moro
Bartosz Krawczyk
Bartosz Krawczyk Rochester Institute of Technology
Stan Szpakowicz
Stan Szpakowicz University of Ottawa
Osmar R. Zaïane
Osmar R. Zaïane University of Alberta
Evangelos E. Milios
Evangelos E. Milios Dalhousie University
Peter A. Flach
Peter A. Flach University of Bristol
Jerzy Stefanowski
Jerzy Stefanowski Poznań University of Technology
Mark A. Gluck
Mark A. Gluck Rutgers, The State University of New Jersey
Tulay Adali
Tulay Adali University of Maryland, Baltimore County

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