Nathalie Japkowicz

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A sub-concept-based feature selection method for one-class classification

Li Liu, Zhen Liu, Nathalie Japkowicz, 2020, Soft Comput..

Adaptive Threshold for Outlier Detection on Data Streams

Zhen Liu, James Clark, Nathalie Japkowicz, 2018, 2018 IEEE 5th International Conference on Data Science and Advanced Analytics (DSAA).

Deep Learning Versus Conventional Learning in Data Streams with Concept Drifts

Iluju Kiringa, Nathalie Japkowicz, Sid Ryan, 2019, 2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA).

Clustering using an Autoassociator: A Case Study in Network Event Correlation

Nathalie Japkowicz, Reuben Smith, Maxwell G. Dondo, 2005, IASTED PDCS.

Morton-PELT: Efficient De-Noising Spatial-Change Point Detection for Large Scale Normalized Digital Elevation Model Data Set

Nathalie Japkowicz, Zhao Yang, Elias Ioup, 2019, 2019 International Conference on Computational Science and Computational Intelligence (CSCI).

AutoCorrel II: a neural network event correlation approach

Nathalie Japkowicz, Peter Mason, Reuben Smith, 2006, SPIE Defense + Commercial Sensing.

Evaluating Learning Algorithms: Two Case Studies

Mohak Shah, Nathalie Japkowicz, 2011 .

Visualizing High Dimensional Classifier Performance Data

Nathalie Japkowicz, Rocío Alaiz-Rodríguez, Peter E. Tischer, 2009 .

Active Learning for One-Class Classification

Nathalie Japkowicz, Vincent Barnabe-Lortie, Colin Bellinger, 2015, 2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA).

Subconcept Based One Class Classification Method with Cluster Updating

Zhen Liu, Nathalie Japkowicz, Ruoyu Wang, 2020, ICMLC.

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

Nathalie Japkowicz, Jose Hanson, Casimir Kulikowski, 1999 .

Applying Support Vector Machines to Imbalanced Datasets

Stephen Kwek, Nathalie Japkowicz, Rehan Akbani, 2004, ECML.

AAAI-07 Workshop Reports

James A. Hendler, Huajun Chen, Alfred Kobsa, 2007, AI Mag..

AutoCorrel: a neural network event correlation approach

Nathalie Japkowicz, Reuben Smith, Maxwell G. Dondo, 2006, SPIE Defense + Commercial Sensing.

A multi-view two-level classification method for generalized multi-instance problems

Stan Matwin, Xuan Liu, Hongyu Guo, 2014, 2014 IEEE International Conference on Big Data (Big Data).

Anomaly Detection via Coupled Gaussian Kernels

Nathalie Japkowicz, Guichong Li, Lian Yang, 2012, Canadian Conference on AI.

Supervised Versus Unsupervised Binary-Learning by Feedforward Neural Networks

Nathalie Japkowicz, N. Japkowicz, 2004, Machine Learning.

Privacy-Preserving Collaborative Association Rule Mining

Stan Matwin, Justin Zhijun Zhan, LiWu Chang, 2005, ICEB.

Spark-GHSOM: Growing Hierarchical Self-Organizing Map for large scale mixed attribute datasets

Michelangelo Ceci, Iluju Kiringa, Nathalie Japkowicz, 2019, Inf. Sci..

Frequency-based anomaly detection for the automotive CAN bus

Nathalie Japkowicz, Sylvain Leblanc, Sylvain P. Leblanc, 2015, 2015 World Congress on Industrial Control Systems Security (WCICSS).

Canadian Conference on Artificial Intelligence

Stan Matwin, Peter A. Flach, Nathalie Japkowicz, 2009 .

One-Class versus Binary Classification: Which and When?

Nathalie Japkowicz, Colin Bellinger, Shiven Sharma, 2012, 2012 11th International Conference on Machine Learning and Applications.

Ensemble of Multiple Kernel SVM Classifiers

Stan Matwin, Xuan Liu, Xiaoguang Wang, 2014, Canadian Conference on AI.

An Ensemble Method Based on AdaBoost and Meta-Learning

Stan Matwin, Xuan Liu, Xiaoguang Wang, 2013, Canadian Conference on AI.

Mining the Hidden Structure of Inductive Learning Data Sets

Nathalie Japkowicz, 2012, Canadian Conference on AI.

A Novelty Detection Approach to Classification

Nathalie Japkowicz, Mark A. Gluck, Catherine Myers, 1995, IJCAI.

Inner Ensembles: Using Ensemble Methods Inside the Learning Algorithm

Stan Matwin, Nathalie Japkowicz, Chris Drummond, 2013, ECML/PKDD.

Assessing the Impact of Changing Environments on Classifier Performance

Nathalie Japkowicz, Rocío Alaíz-Rodríguez, N. Japkowicz, 2008, Canadian Conference on AI.

Discovery Science: 18th International Conference, DS 2015, Banff, AB, Canada, October 4-6, 2015. Proceedings

Stan Matwin, Nathalie Japkowicz, 2015 .

Multi-class learning using data driven ECOC with deep search and re-balancing

Jie Zhou, Nathalie Japkowicz, Vincent Barnabe-Lortie, 2015, 2015 IEEE International Conference on Data Science and Advanced Analytics (DSAA).

Three and Four Phase Scenarios for Dynamic Document Organization

Taeho Jo, Nathalie Japkowicz, 2006, 2006 IEEE International Conference on Systems, Man and Cybernetics.

Beyond Accuracy, F-Score and ROC: A Family of Discriminant Measures for Performance Evaluation

Stan Szpakowicz, Nathalie Japkowicz, Marina Sokolova, 2006, Australian Conference on Artificial Intelligence.

Smoothing gamma ray spectra to improve outlier detection

Nathalie Japkowicz, Vincent Barnabe-Lortie, Colin Bellinger, 2014, the 2014 Seventh IEEE Symposium on Computational Intelligence for Security and Defense Applications (CISDA).

Pattern and Anomaly Localization in Complex and Dynamic Data

Iluju Kiringa, Nathalie Japkowicz, Sid Ryan, 2019, 2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA).

Anomaly Detection and Repair for Accurate Predictions in Geo-distributed Big Data

Michelangelo Ceci, Nathalie Japkowicz, Roberto Corizzo, 2019, Big Data Res..

Evaluating Learning Algorithms: Contents

Mohak Shah, Nathalie Japkowicz, Mohak Shah, 2011 .

Beyond the Boundaries of SMOTE - A Framework for Manifold-Based Synthetically Oversampling

Nathalie Japkowicz, Chris Drummond, Colin Bellinger, 2016, ECML/PKDD.

Automated Approach To Classification Of Mine-Like Objects Using Multiple-Aspect Sonar Images

Stan Matwin, Nathalie Japkowicz, Xiaoguang Wang, 2014, J. Artif. Intell. Soft Comput. Res..

Learning with Drift Detection based on k Time Sub-concept Windows

Zhen Liu, Li Liu, Dan Tao, 2019, 2019 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-TW).

2015 IEEE International Conference on Data Science and Advanced Analytics, DSAA 2015, Campus des Cordeliers, Paris, France, October 19-21, 2015

Wolfgang Lehner, Jingyuan Zhang, Qingbo Hu, 2015, DSAA.

Adaptability of the backpropagation procedure

Nathalie Japkowicz, Stephen Jose Hanson, 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).

Proceedings of the 22nd Canadian Conference on Artificial Intelligence: Advances in Artificial Intelligence

Nathalie Japkowicz, Yong Gao, 2009 .

One-Class Ensembles for Rare Genomic Sequences Identification

Nathalie Japkowicz, Roberto Corizzo, Jonathan Kaufmann, 2020, DS.

Classifier Utility Visualization by Distance-Preserving Projection of High Dimensional Performance D

Nathalie Japkowicz, Peter E. Tischer, Pritika Sanghi, 2008, ISAIM.

Node similarity in the citation graph

Evangelos E. Milios, Nathalie Japkowicz, Jeannette C. M. Janssen, 2006, Knowledge and Information Systems.

Introduction to the Special Issue on Data Mining for Cybersecurity

Yuval Elovici, Nathalie Japkowicz, 2018, IEEE Intell. Syst..

Are we better off without Counter-Examples?

Nathalie Japkowicz, N. Japkowicz, 1999 .

The PerfSim Algorithm for Concept Drift Detection in Imbalanced Data

Herna L. Viktor, Nathalie Japkowicz, Daniel K. Antwi, 2012, 2012 IEEE 12th International Conference on Data Mining Workshops.

Special issue on discovery science

Stan Matwin, Nathalie Japkowicz, 2016, Machine Learning.

Advances in Artificial Intelligence

Nathalie Japkowicz, Yong Gao, 2009 .

Learning with Concept Drift Detection based on Sub-concepts from k Time Sub Windows

Li Liu, Zhen Liu, Nathalie Japkowicz, 2020 .

A Multiple Resampling Method for Learning from Imbalanced Data Sets

Taeho Jo, Nathalie Japkowicz, Andrew Estabrooks, 2004, Comput. Intell..

A Cost Skew Aware Predictive System for Chest Drain Management

Nathalie Japkowicz, Nicholas J. Denis, Danny French, 2020, Canadian Conference on AI.

Clustering in the Presence of Concept Drift

Herna L. Viktor, João Gama, Nathalie Japkowicz, 2018, ECML/PKDD.

A Meta-learning Approach for Selecting between Response Automation Strategies in a Help-desk Domain

Ingrid Zukerman, Nathalie Japkowicz, Yuval Marom, 2007, AAAI.

Editorial: special issue on learning from imbalanced data sets

Nitesh V. Chawla, Nathalie Japkowicz, Aleksander Kotcz, 2004, SKDD.

Border Sampling through Coupling Markov Chain Monte Carlo

Nathalie Japkowicz, Guichong Li, R. Kurt Ungar, 2008, 2008 Eighth IEEE International Conference on Data Mining.

AAAI 2000 Workshop Reports

Gerd Wagner, David W. Aha, Yolanda Gil, 2001, AI Mag..

A Machine Learning Perspective on Big Data Analysis

Nathalie Japkowicz, Jerzy Stefanowski, 2016 .

Meta-MapReduce for scalable data mining

Stan Matwin, Xuan Liu, Xiaoguang Wang, 2015, Journal of Big Data.

Evaluating Misclassifications in Imbalanced Data

Stan Matwin, Nathalie Japkowicz, William Elazmeh, 2006, ECML.

A Recognition-based Alternative to Discrimination-based Perceptrons

Nathalie Japkowicz, Todd Eavis, N. Japkowicz, 2000 .

Evaluating Learning Algorithms: A Classification Perspective

Mohak Shah, Nathalie Japkowicz, Mohak Shah, 2011 .

On the Benefits (or Not) of a Clustering Algorithm in Student Tracking

Reva Freedman, Nathalie Japkowicz, 2013, AIED.

Sampling a Longer Life: Binary versus One-class classification Revisited

Osmar R. Zaïane, Nathalie Japkowicz, Colin Bellinger, 2017, LIDTA@PKDD/ECML.

Learning over subconcepts: Strategies for 1‐class classification

Nathalie Japkowicz, Anil Somayaji, Shiven Sharma, 2018, Comput. Intell..

One-class classification - From theory to practice: A case-study in radioactive threat detection

Nathalie Japkowicz, Colin Bellinger, Shiven Sharma, 2018, Expert Syst. Appl..

Automatic Target Recognition using multiple-aspect sonar images

Stan Matwin, Xuan Liu, Xiaoguang Wang, 2014, 2014 IEEE Congress on Evolutionary Computation (CEC).

Contextual One-Class Classification in Data Streams pdf

Herna L. Viktor, Nathalie Japkowicz, Richard Hugh Moulton, 2019, ArXiv.

Resampling and Cost-Sensitive Methods for Imbalanced Multi-instance Learning

Stan Matwin, Xuan Liu, Xiaoguang Wang, 2013, 2013 IEEE 13th International Conference on Data Mining Workshops.

Workshop summary: The fourth workshop on evaluation methods for machine learning

Nathalie Japkowicz, Chris Drummond, Sofus A. Macskassy, 2009, International Conference on Machine Learning.

Threaded ensembles of autoencoders for stream learning

Yue Dong, Nathalie Japkowicz, N. Japkowicz, 2018, Comput. Intell..

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

Nathalie Japkowicz, Andrew Estabrooks, N. Japkowicz, 2001, IDA.

Multi-label Classification of Anemia Patients

Nathalie Japkowicz, Herna Viktor, Colin Bellinger, 2015, 2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA).

Independent Component Analysis for Trustworthy Cyberspace during High Impact Events: An Application to Covid-19 pdf

Anupam Joshi, Aritran Piplai, Sudip Mittal, 2020, ArXiv.

Manifold-based synthetic oversampling with manifold conformance estimation

Nathalie Japkowicz, Chris Drummond, Colin Bellinger, 2018, Machine Learning.

Evaluating Learning Algorithms: Bibliography

Mohak Shah, Nathalie Japkowicz, 2011 .

Using SVM with Adaptively Asymmetric MisClassification Costs for Mine-Like Objects Detection

Stan Matwin, Xuan Liu, Xiaoguang Wang, 2012, 2012 11th International Conference on Machine Learning and Applications.

Clustering Based One-Class Classification for Compliance Verification of the Comprehensive Nuclear-Test-Ban Treaty

Nathalie Japkowicz, Colin Bellinger, Shiven Sharma, 2012, Canadian Conference on AI.

An Automatic Evaluation Framework for Improving a Configurable Text Summarizer

Terry Copeck, Stan Szpakowicz, Nathalie Japkowicz, 2004, Canadian Conference on AI.

Evangelos E. Milios, Nathalie Japkowicz, Jeannette C. M. Janssen, 2001, CASCON.

Cost-Sensitive Boosting Algorithms for Imbalanced Multi-instance Datasets

Stan Matwin, Xuan Liu, Xiaoguang Wang, 2013, Canadian Conference on AI.

A mixture-of-experts framework for text classification

Nathalie Japkowicz, Andrew Estabrooks, N. Japkowicz, 2001, CoNLL.

A System for Translating Locative Prepositions from English into French

Janyce Wiebe, Nathalie Japkowicz, 1991, ACL.

Using Unsupervised Learning to Guide Resampling in Imbalanced Data Sets

Evangelos E. Milios, Nathalie Japkowicz, Adam Nickerson, 2001, AISTATS.

A Projection-Based Framework for Classifier Performance Evaluation

Nathalie Japkowicz, Peter E. Tischer, Pritika Sanghi, 2008, ECML/PKDD.

Synthetic Oversampling for Advanced Radioactive Threat Detection

Nathalie Japkowicz, Chris Drummond, Colin Bellinger, 2015, 2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA).

Applying Least Angle Regression to ELM

Nathalie Japkowicz, Hang Shao, N. Japkowicz, 2012, Canadian Conference on AI.

Anomaly behaviour detection based on the meta-Morisita index for large scale spatio-temporal data set

Zhao Yang, Nathalie Japkowicz, 2018, J. Big Data.

PEEP- An Information Extraction base approach for Privacy Protection in Email

Stan Matwin, Nathalie Japkowicz, Yimin Ma, 2005, CEAS.

Evaluation Methods for Ordinal Classification

Nathalie Japkowicz, Lisa Gaudette, N. Japkowicz, 2009, Canadian Conference on AI.

Cost-Based Sampling of Individual Instances

Stan Matwin, Peter A. Flach, Nathalie Japkowicz, 2009, Canadian Conference on AI.

Cascading Customized Naïve Bayes Couple

Nathalie Japkowicz, Guichong Li, R. Kurt Ungar, 2010, Canadian Conference on AI.

Motivating the inclusion of meteorological indicators in the CTBT feature-space

Nathalie Japkowicz, Colin Bellinger, 2011, 2011 IEEE Symposium on Computational Intelligence for Security and Defense Applications (CISDA).

A Feature Selection and Evaluation Scheme for Computer Virus Detection

Nathalie Japkowicz, Olivier Henchiri, N. Japkowicz, 2006, Sixth International Conference on Data Mining (ICDM'06).

English to Chinese Translation of Prepositions

Nathalie Japkowicz, Hui Li, Caroline Barrière, 2005, Canadian Conference on AI.

Machine learning for radioxenon event classification for the Comprehensive Nuclear-Test-Ban Treaty.

Nathalie Japkowicz, Guichong Li, Trevor J Stocki, 2010, Journal of environmental radioactivity.

The class imbalance problem: A systematic study

Nathalie Japkowicz, Shaju Stephen, N. Japkowicz, 2002, Intell. Data Anal..

Performance Evaluation in Machine Learning

Mohak Shah, Nathalie Japkowicz, Mohak Shah, 2015 .

Reports on the Twenty-First National Conference on Artificial Intelligence (AAAI-06) Workshop Program

Hugo Liu, Amit P. Sheth, Christopher W. Geib, 2006, AI Mag..

Mobile app traffic flow feature extraction and selection for improving classification robustness

Zhen Liu, Nathalie Japkowicz, Deyu Tang, 2019, J. Netw. Comput. Appl..

Full Border Identification for Reduction of Training Sets

Nathalie Japkowicz, Guichong Li, R. Kurt Ungar, 2008, Canadian Conference on AI.

ReMix: Calibrated Resampling for Class Imbalance in Deep learning pdf

Nathalie Japkowicz, Roberto Corizzo, Colin Bellinger, 2020, 2012.02312.

Threaded Ensembles of Supervised and Unsupervised Neural Networks for Stream Learning

Yue Dong, Nathalie Japkowicz, N. Japkowicz, 2016, Canadian Conference on AI.

Instance Selection by Border Sampling in Multi-class Domains

Nathalie Japkowicz, Guichong Li, R. Kurt Ungar, 2009, ADMA.

Using Classifier Performance Visualization to Improve Collective Ranking Techniques for Biomedical Abstracts Classification

Nathalie Japkowicz, Alexandre Kouznetsov, N. Japkowicz, 2010, Canadian Conference on AI.

Boosting support vector machines for imbalanced data sets

Nathalie Japkowicz, Benjamin X. Wang, N. Japkowicz, 2008, Knowledge and Information Systems.

PEEP- Privacy Enforcement in Email Project

Stan Matwin, Nathalie Japkowicz, William Elazmeh, 2005, PST.

A Recognition-Based Alternative to Discrimination-Based Multi-layer Perceptrons

Nathalie Japkowicz, Todd Eavis, N. Japkowicz, 2000, Canadian Conference on AI.

Explicit feature mapping via multi-layer perceptron and its application to Mine-Like Objects detection

Nathalie Japkowicz, Hang Shao, 2014, 2014 International Joint Conference on Neural Networks (IJCNN).

Privacy Compliance Enforcement in Email

Stan Matwin, Nathalie Japkowicz, William Elazmeh, 2005, Canadian Conference on AI.

Case Authoring from Text and Historical Experiences

Stan Matwin, Nathalie Japkowicz, Marvin Zaluski, 2003, Canadian Conference on AI.

Warning: statistical benchmarking is addictive. Kicking the habit in machine learning

Nathalie Japkowicz, Chris Drummond, C. Drummond, 2010, J. Exp. Theor. Artif. Intell..

Visualizing Classifier Performance on Different Domains

Nathalie Japkowicz, Peter E. Tischer, Rocío Alaíz-Rodríguez, 2008, 2008 20th IEEE International Conference on Tools with Artificial Intelligence.

Text Summarization as Controlled Search

Terry Copeck, Stan Szpakowicz, Nathalie Japkowicz, 2002, Canadian Conference on AI.

Applying instance-weighted support vector machines to class imbalanced datasets

Stan Matwin, Xuan Liu, Xiaoguang Wang, 2014, 2014 IEEE International Conference on Big Data (Big Data).

Framework for extreme imbalance classification: SWIM—sampling with the majority class

Nathalie Japkowicz, Osmar R. Zaïane, Colin Bellinger, 2019, Knowledge and Information Systems.

Compact Features for Sentiment Analysis

Nathalie Japkowicz, Lisa Gaudette, 2011, Canadian Conference on AI.

Evaluating Learning Algorithms: Introduction

Mohak Shah, Nathalie Japkowicz, 2011 .

Nonlinear Autoassociation Is Not Equivalent to PCA

Nathalie Japkowicz, Mark A. Gluck, Stephen Jose Hanson, 2000, Neural Computation.

Using Unsupervised Learning for Network Alert Correlation

Nathalie Japkowicz, Peter Mason, Reuben Smith, 2008, Canadian Conference on AI.

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

Nathalie Japkowicz, N. Japkowicz, 2001, Canadian Conference on AI.

Evaluating Learning Algorithms: Recent Developments

Mohak Shah, Nathalie Japkowicz, 2011 .

Probing the Limits of Anomaly Detectors for Automobiles with a Cyberattack Framework

Adrian Taylor, Nathalie Japkowicz, Sylvain Leblanc, 2018, IEEE Intelligent Systems.

Bootstrapping Training-Data Representations for Inductive Learning: A Case Study in Molecular Biology

Haym Hirsh, Nathalie Japkowicz, 1994, AAAI.

Improving Active Learning for One-Class Classification Using Dimensionality Reduction

Nathalie Japkowicz, Mohsen Ghazel, 2017, Canadian Conference on AI.

Evaluating Data Mining Models: A Pattern Language

Stan Matwin, Nathalie Japkowicz, Jerffeson Teixeira de Souza, 2002 .

Boosting Support Vector Machines for Imbalanced Data Sets

Nathalie Japkowicz, Benjamin X. Wang, 2008, ISMIS.

Autocorrel I: A Neural Network Based Network Event Correlation Approach

Nathalie Japkowicz, Reuben Smith, N. Japkowicz, 2005 .

Improving Bayesian Learning Using Public Knowledge

Stan Matwin, Nathalie Japkowicz, Farid Seifi, 2010, Canadian Conference on AI.

Class imbalances versus small disjuncts

Taeho Jo, Nathalie Japkowicz, N. Japkowicz, 2004, SKDD.

Anomaly detection in gamma ray spectra: A machine learning perspective

Nathalie Japkowicz, Colin Bellinger, Shiven Sharma, 2012, 2012 IEEE Symposium on Computational Intelligence for Security and Defence Applications.

Robustness of Classifiers to Changing Environments

Stan Matwin, Nathalie Japkowicz, Chris Drummond, 2010, Canadian Conference on AI.

Guest Editorial Special Issue on Recent Advances in Theory, Methodology, and Applications of Imbalanced Learning

Manuel Roveri, Jing-Hao Xue, Nathalie Japkowicz, 2020, IEEE Trans. Neural Networks Learn. Syst..

Big Data Analysis: New Algorithms for a New Society

Nathalie Japkowicz, Jerzy Stefanowski, 2015 .

ECHAD: Embedding-Based Change Detection From Multivariate Time Series in Smart Grids

Michelangelo Ceci, Nathalie Japkowicz, Roberto Corizzo, 2020, IEEE Access.

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

Nathalie Japkowicz, Sylvain Leblanc, Sylvain P. Leblanc, 2016, 2016 IEEE International Conference on Data Science and Advanced Analytics (DSAA).

Gene selection for the reconstruction of stem cell differentiation trees: a linear programming approach

Nathalie Japkowicz, Theodore J. Perkins, Mohamed A. Ghadie, 2015, Bioinform..

2nd Workshop on Learning with Imbalanced Domains: Preface

Stan Matwin, Luís Torgo, Bartosz Krawczyk, 2018, LIDTA@ECML/PKDD.

The Class Imbalance Problem: Significance and Strategies

Nathalie Japkowicz, N. Japkowicz, 2000 .

SPECIAL ISSUE ON LEARNING FROM IMBALANCED DATA SETS

Nitesh V. Chawla, Nathalie Japkowicz, A Kolcz, 2004 .

Vessel track correlation and association using fuzzy logic and Echo State Networks

Rami S. Abielmona, Rafael Falcon, Nathalie Japkowicz, 2014, 2014 IEEE Congress on Evolutionary Computation (CEC).

Smooth Receiver Operating Characteristics (smROC) Curves

Stan Matwin, Peter A. Flach, Nathalie Japkowicz, 2011, ECML/PKDD.

Homography Estimation from Image Pairs with Hierarchical Convolutional Networks

Robert Laganière, Nathalie Japkowicz, Farzan Erlik Nowruzi, 2017, 2017 IEEE International Conference on Computer Vision Workshops (ICCVW).

The Decision List Machine

John Shawe-Taylor, Mario Marchand, Nathalie Japkowicz, 2002, NIPS.

Parallelizing Feature Selection

Stan Matwin, Nathalie Japkowicz, Jerffeson Teixeira de Souza, 2006, Algorithmica.

Fuzzy String Matching with a Deep Neural Network

Nathalie Japkowicz, Miodrag Bolic, Mathieu Lemay, 2018, Appl. Artif. Intell..

Supervised Learning with Unsupervised Output Separation

Nathalie Japkowicz, N. Japkowicz, 2002 .

Sampling Online Social Networks Using Coupling from the Past

Nathalie Japkowicz, Kenton White, Guichong Li, 2012, 2012 IEEE 12th International Conference on Data Mining Workshops.

Scalable auto-encoders for gravitational waves detection from time series data

Michelangelo Ceci, Nathalie Japkowicz, Eftim Zdravevski, 2020, Expert Syst. Appl..

A Visualization-Based Exploratory Technique for Classifier Comparison with Respect to Multiple Metrics and Multiple Domains

Nathalie Japkowicz, Peter E. Tischer, Rocío Alaíz-Rodríguez, 2008, ECML/PKDD.

A Unified Framework for Relative Clause Simplification and Relative Pronoun Correction

Nathalie Japkowicz, Christina George, 2007, IC-AI.

Evaluating Learning Algorithms: Datasets and Experimental Framework

Mohak Shah, Nathalie Japkowicz, 2011 .

Chest Tube Management After Lung Resection Surgery using a Classifier

Nathalie Japkowicz, William Klement, Sebastien Gilbert, 2019, 2019 IEEE International Conference on Data Science and Advanced Analytics (DSAA).

A statistical pattern based feature extraction method on system call traces for anomaly detection

Zhen Liu, Nathalie Japkowicz, Ruoyu Wang, 2020, Inf. Softw. Technol..

Unknown malcode detection and the imbalance problem

Yuval Elovici, Nathalie Japkowicz, Nir Nissim, 2009, Journal in Computer Virology.

Meta-learning for large scale machine learning with MapReduce

Stan Matwin, Xuan Liu, Xiaoguang Wang, 2013, 2013 IEEE International Conference on Big Data.

Network Event Correlation Using Unsupervised Machine Learning Algorithms

Nathalie Japkowicz, Maxwell G. Dondo, Reuben Smith, 2006 .

Towards Ethical Content-Based Detection Of Online Influence Campaigns

Nathalie Japkowicz, Herna Viktor, Evan Crothers, 2019, 2019 IEEE 29th International Workshop on Machine Learning for Signal Processing (MLSP).

Meta-Morisita Index: Anomaly Behaviour Detection for Large Scale Tracking Data with Spatio-Temporal Marks

Zhao Yang, Nathalie Japkowicz, 2017, 2017 IEEE International Conference on Data Mining Workshops (ICDMW).

Synthetic Oversampling with the Majority Class: A New Perspective on Handling Extreme Imbalance

Osmar R. Zaïane, Bartosz Krawczyk, Nathalie Japkowicz, 2018, 2018 IEEE International Conference on Data Mining (ICDM).

Evaluating Learning Algorithms: Conclusion

Mohak Shah, Nathalie Japkowicz, Mohak Shah, 2011 .

STochFS: A Framework for Combining Feature Selection Outcomes Through a Stochastic Process

Stan Matwin, Nathalie Japkowicz, Jerffeson Teixeira de Souza, 2005, PKDD.

Evaluating Learning Algorithms: Additional Information on the Data

Mohak Shah, Nathalie Japkowicz, 2011 .

Undersampling with Support Vectors for Multi-Class Imbalanced Data Classification

Bartosz Krawczyk, Nathalie Japkowicz, Roberto Corizzo, 2021, 2021 International Joint Conference on Neural Networks (IJCNN).

Research on unsupervised feature learning for Android malware detection based on Restricted Boltzmann Machines

Nathalie Japkowicz, Deyu Tang, Wenbin Zhang, 2021, Future Gener. Comput. Syst..

Mean User-Text Agglomeration (MUTA): Practical User Representation and Visualization for Detection of Online Influence Operations

Nathalie Japkowicz, Evan Crothers, Herna Viktor, 2021, CSoNet.

Spatially-Aware Autoencoders for Detecting Contextual Anomalies in Geo-Distributed Data

Michelangelo Ceci, Nathalie Japkowicz, Roberto Corizzo, 2021, DS.

On the combined effect of class imbalance and concept complexity in deep learning

Bartosz Krawczyk, Nathalie Japkowicz, Roberto Corizzo, 2021, 2021 IEEE International Conference on Big Data (Big Data).

A Semi-supervised Framework for Misinformation Detection

Nathalie Japkowicz, Zois Boukouvalas, Yueyang Liu, 2023, DS.

Calibrated Resampling for Imbalanced and Long-Tails in Deep Learning

Nathalie Japkowicz, Roberto Corizzo, Colin Bellinger, 2021, DS.

The Case for Latent Variable Vs Deep Learning Methods in Misinformation Detection: An Application to COVID-19

Sudip Mittal, Tülay Adali, Nathalie Japkowicz, 2021, DS.

WATCH: Wasserstein Change Point Detection for High-Dimensional Time Series Data

Nathalie Japkowicz, Roberto Corizzo, Bartlomiej Sniezynski, 2021, 2021 IEEE International Conference on Big Data (Big Data).

3.2 Stage 2: Inter-feature Extrapolation towards a Bootstrapping Approach to Constructive Induction

Haym Hirsh, Nathalie Japkowicz, Morgan Kaufmann, 1994 .

A Framework for Comparative Evaluation of Classifiers in the Presence of Class Imbalance

Nathalie Japkowicz, William Elazmeh, 2006 .

Adaptive learning on mobile network traffic data

Nathalie Japkowicz, Deyu Tang, Ruoyu Wang, 2018, Connect. Sci..

Automatic Correction of French to English Relative Pronoun Translations using Natural Language Processing and Machine Learning Techniques

Nathalie Japkowicz, N. Japkowicz, C. George, 2005 .