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ORCIDNathalie Japkowicz
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- affiliation: American University, Washington, DC, USA
- affiliation (former): University of Ottawa, Canada
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2020 – today
- 2024
[j50]Kamil Faber
, Roberto Corizzo, Bartlomiej Sniezynski, Nathalie Japkowicz:
Lifelong Continual Learning for Anomaly Detection: New Challenges, Perspectives, and Insights. IEEE Access 12: 41364-41380 (2024)- [j49]Zhen Liu, Ruoyu Wang, Nathalie Japkowicz, Heitor Murilo Gomes, Bitao Peng, Wenbin Zhang:
SeGDroid: An Android malware detection method based on sensitive function call graph learning. Expert Syst. Appl. 235: 121125 (2024) - [j48]Lucas P. Damasceno, Egzona Rexhepi, Allison Shafer, Ian Whitehouse, Nathalie Japkowicz, Charles C. Cavalcante, Roberto Corizzo, Zois Boukouvalas:
Exploiting sparsity and statistical dependence in multivariate data fusion: an application to misinformation detection for high-impact events. Mach. Learn. 113(4): 2183-2205 (2024) - [j47]Kushankur Ghosh, Colin Bellinger, Roberto Corizzo, Paula Branco, Bartosz Krawczyk, Nathalie Japkowicz:
The class imbalance problem in deep learning. Mach. Learn. 113(7): 4845-4901 (2024) - [j46]Lucas P. Damasceno, Egzona Rexhepi, Allison Shafer, Ian Whitehouse, Nathalie Japkowicz, Charles C. Cavalcante, Roberto Corizzo, Zois Boukouvalas:
Correction to: Exploiting sparsity and statistical dependence in multivariate data fusion: an application to misinformation detection for high-impact events. Mach. Learn. 113(9): 7127-7128 (2024) - [j45]Kamil Faber, Dominik Zurek, Marcin Pietron, Nathalie Japkowicz, Antonio Vergari, Roberto Corizzo:
From MNIST to ImageNet and back: benchmarking continual curriculum learning. Mach. Learn. 113(10): 8137-8164 (2024) - [c121]Dhanush Kikkisetti, Raza Ul-Mustafa, Wendy Melillo, Roberto Corizzo, Zois Boukouvalas, Jeff Gill, Nathalie Japkowicz:
Coded Term Discovery for Online Hate Speech Detection. DSAA 2024: 1-10 - [c120]Yaning Wu, Nathalie Japkowicz, Sébastien Gilbert, Roberto Corizzo:
Attention-Based Medical Knowledge Injection in Deep Image Classification Models. IJCNN 2024: 1-8 - [i18]Dhanush Kikkisetti, Raza Ul-Mustafa, Wendy Melillo, Roberto Corizzo, Zois Boukouvalas, Jeff Gill, Nathalie Japkowicz:
Using LLMs to discover emerging coded antisemitic hate-speech in extremist social media. CoRR abs/2401.10841 (2024) - [i17]Raza Ul-Mustafa, Nathalie Japkowicz:
Monitoring the evolution of antisemitic discourse on extremist social media using BERT. CoRR abs/2403.05548 (2024) - [i16]Xuanyu Su, Yansong Li, Diana Inkpen, Nathalie Japkowicz:
HateSieve: A Contrastive Learning Framework for Detecting and Segmenting Hateful Content in Multimodal Memes. CoRR abs/2408.05794 (2024) - 2023
- [j44]Evan Crothers, Nathalie Japkowicz, Herna L. Viktor:
Machine-Generated Text: A Comprehensive Survey of Threat Models and Detection Methods. IEEE Access 11: 70977-71002 (2023) - [j43]Miriam Seoane Santos, Pedro Henriques Abreu, Nathalie Japkowicz, Alberto Fernández, João A. M. Santos:
A unifying view of class overlap and imbalance: Key concepts, multi-view panorama, and open avenues for research. Inf. Fusion 89: 228-253 (2023) - [j42]Kamil Faber, Roberto Corizzo, Bartlomiej Sniezynski, Nathalie Japkowicz:
VLAD: Task-agnostic VAE-based lifelong anomaly detection. Neural Networks 165: 248-273 (2023) - [j41]Roberto Corizzo, Gianvito Pio, Emanuele Pio Barracchia, Antonio Pellicani, Nathalie Japkowicz, Michelangelo Ceci:
HURI: Hybrid user risk identification in social networks. World Wide Web (WWW) 26(5): 3409-3439 (2023) - [c119]Nicolas Antonio Cloutier, Nathalie Japkowicz:
Fine-tuned generative LLM oversampling can improve performance over traditional techniques on multiclass imbalanced text classification. IEEE Big Data 2023: 5181-5186 - [c118]Colin Bellinger, Roberto Corizzo, Nathalie Japkowicz:
Performance Estimation bias in Class Imbalance with Minority Subconcepts. LIDTA 2023: 31-44 - [e7]Nuno Moniz, Paula Branco, Luís Torgo, Nathalie Japkowicz, Michal Wozniak, Shuo Wang:
Fifth International Workshop on Learning with Imbalanced Domains: Theory and Applications, 18 September 2023, LIDTA@ECML-PKDD, Turin, Italy. Proceedings of Machine Learning Research 241, PMLR 2023 [contents] - [i15]Evan Crothers, Herna L. Viktor, Nathalie Japkowicz:
In BLOOM: Creativity and Affinity in Artificial Lyrics and Art. CoRR abs/2301.05402 (2023) - [i14]Kamil Faber, Roberto Corizzo, Bartlomiej Sniezynski, Nathalie Japkowicz:
Lifelong Learning for Anomaly Detection: New Challenges, Perspectives, and Insights. CoRR abs/2303.07557 (2023) - [i13]Kamil Faber, Dominik Zurek, Marcin Pietron, Nathalie Japkowicz, Antonio Vergari, Roberto Corizzo:
From MNIST to ImageNet and Back: Benchmarking Continual Curriculum Learning. CoRR abs/2303.11076 (2023) - [i12]Yueyang Liu, Zois Boukouvalas, Nathalie Japkowicz:
A Semi-Supervised Framework for Misinformation Detection. CoRR abs/2304.11318 (2023) - [i11]Evan Crothers, Herna L. Viktor, Nathalie Japkowicz:
Faithful to Whom? Questioning Interpretability Measures in NLP. CoRR abs/2308.06795 (2023) - [i10]Shoffan Saifullah, Rafal Drezewski, Anton Yudhana, Andri Pranolo, Wilis Kaswijanti, Andiko Putro Suryotomo, Seno Aji Putra, Alin Khaliduzzaman, Anton Satria Prabuwono, Nathalie Japkowicz:
Nondestructive chicken egg fertility detection using CNN-transfer learning algorithms. CoRR abs/2309.16257 (2023) - 2022
- [j40]Miriam Seoane Santos, Pedro Henriques Abreu, Nathalie Japkowicz, Alberto Fernández, Carlos Soares, Szymon Wilk, João A. M. Santos:
On the joint-effect of class imbalance and overlap: a critical review. Artif. Intell. Rev. 55(8): 6207-6275 (2022) - [j39]William Klement, Sébastien Gilbert, Virginia F. Resende, Donna E. Maziak, Andrew J. E. Seely, Farid M. Shamji, Sudhir R. Sundaresan, Patrick J. Villeneuve, Nathalie Japkowicz:
The validation of chest tube management after lung resection surgery using a random forest classifier. Int. J. Data Sci. Anal. 13(3): 251-263 (2022) - [j38]Roberto Corizzo, Michael Baron, Nathalie Japkowicz:
CPDGA: Change point driven growing auto-encoder for lifelong anomaly detection. Knowl. Based Syst. 247: 108756 (2022) - [c117]Indranil Sur, Zachary Daniels, Abrar Rahman, Kamil Faber, Gianmarco J. Gallardo, Tyler L. Hayes, Cameron E. Taylor, Mustafa Burak Gurbuz, James Seale Smith, Sahana Pramod Joshi, Nathalie Japkowicz, Michael Baron, Zsolt Kira, Christopher Kanan, Roberto Corizzo, Ajay Divakaran, Michael R. Piacentino, Jesse Hostetler, Aswin Raghavan:
System Design for an Integrated Lifelong Reinforcement Learning Agent for Real-Time Strategy Games. AIMLSystems 2022: 12:1-12:9 - [c116]Roberto Corizzo, Rodrigo Yepez-Lopez, Sébastien Gilbert, Nathalie Japkowicz:
LSTM-based Pulmonary Air Leak Forecasting for Chest Tube Management. IEEE Big Data 2022: 5217-5222 - [c115]Zachary Alan Daniels, Aswin Raghavan, Jesse Hostetler, Abrar Rahman, Indranil Sur, Michael R. Piacentino, Ajay Divakaran, Roberto Corizzo, Kamil Faber, Nathalie Japkowicz, Michael Baron, James Seale Smith, Sahana Pramod Joshi, Zsolt Kira, Cameron Ethan Taylor, Mustafa Burak Gurbuz, Constantine Dovrolis, Tyler L. Hayes, Christopher Kanan, Jhair Gallardo:
Model-Free Generative Replay for Lifelong Reinforcement Learning: Application to Starcraft-2. CoLLAs 2022: 1120-1145 - [c114]Lucas P. Damasceno, Allison Shafer, Nathalie Japkowicz, Charles C. Cavalcante, Zois Boukouvalas:
Efficient Multivariate Data Fusion for Misinformation Detection During High Impact Events. DS 2022: 253-268 - [c113]Kamil Faber, Roberto Corizzo, Bartlomiej Sniezynski, Nathalie Japkowicz:
Active Lifelong Anomaly Detection with Experience Replay. DSAA 2022: 1-10 - [c112]Evan Crothers, Nathalie Japkowicz, Herna L. Viktor, Paula Branco:
Adversarial Robustness of Neural-Statistical Features in Detection of Generative Transformers. IJCNN 2022: 1-8 - [c111]Kamil Faber, Roberto Corizzo, Bartlomiej Sniezynski, Michael Baron, Nathalie Japkowicz:
LIFEWATCH: Lifelong Wasserstein Change Point Detection. IJCNN 2022: 1-8 - [c110]Myles Russell, Dylan Russell, Roberto Corizzo, Nathalie Japkowicz:
Machine Learning for Surgical Risk Assessment Decision Systems. IJCNN 2022: 1-8 - [c109]Roberto Corizzo, Junfeng Ge, Colin Bellinger, Xiaoqiang Zhu, Paula Branco, Kuang-chih Lee, Nathalie Japkowicz, Ruiming Tang, Tao Zhuang, Han Zhu, Biye Jiang, Jiaxin Mao, Weinan Zhang:
4th Workshop on Deep Learning Practice and Theory for High-Dimensional Sparse and Imbalanced Data with KDD 2022. KDD 2022: 4860-4861 - [c108]Nuno Moniz, Paula Branco, Luís Torgo, Nathalie Japkowicz, Michal Wozniak, Shuo Wang:
4th Workshop on Learning with Imbalanced Domains: Preface. LIDTA 2022: 1-7 - [e6]Nuno Moniz, Paula Branco, Luís Torgo, Nathalie Japkowicz, Michal Wozniak, Shuo Wang:
Fourth International Workshop on Learning with Imbalanced Domains: Theory and Applications, LIDTA 2022, Grenoble, France, September 23, 2022. Proceedings of Machine Learning Research 183, PMLR 2022 [contents] - [i9]Kamil Faber, Roberto Corizzo, Bartlomiej Sniezynski, Michael Baron, Nathalie Japkowicz:
WATCH: Wasserstein Change Point Detection for High-Dimensional Time Series Data. CoRR abs/2201.07125 (2022) - [i8]Evan Crothers, Nathalie Japkowicz, Herna L. Viktor, Paula Branco:
Adversarial Robustness of Neural-Statistical Features in Detection of Generative Transformers. CoRR abs/2203.07983 (2022) - [i7]Evan Crothers, Nathalie Japkowicz, Herna L. Viktor:
Machine Generated Text: A Comprehensive Survey of Threat Models and Detection Methods. CoRR abs/2210.07321 (2022) - [i6]Indranil Sur, Zachary Daniels, Abrar Rahman, Kamil Faber, Gianmarco J. Gallardo, Tyler L. Hayes, Cameron E. Taylor, Mustafa Burak Gurbuz, James Seale Smith, Sahana Pramod Joshi, Nathalie Japkowicz, Michael Baron, Zsolt Kira, Christopher Kanan, Roberto Corizzo, Ajay Divakaran, Michael R. Piacentino, Jesse Hostetler, Aswin Raghavan:
System Design for an Integrated Lifelong Reinforcement Learning Agent for Real-Time Strategy Games. CoRR abs/2212.04603 (2022) - 2021
- [j37]Zhen Liu, Ruoyu Wang, Nathalie Japkowicz, Deyu Tang, Wenbin Zhang, Jie Zhao:
Research on unsupervised feature learning for Android malware detection based on Restricted Boltzmann Machines. Future Gener. Comput. Syst. 120: 91-108 (2021) - [c107]Kamil Faber, Roberto Corizzo, Bartlomiej Sniezynski, Michael Baron, Nathalie Japkowicz:
WATCH: Wasserstein Change Point Detection for High-Dimensional Time Series Data. IEEE BigData 2021: 4450-4459 - [c106]Roberto Corizzo, Yohan Dauphin, Colin Bellinger, Eftim Zdravevski, Nathalie Japkowicz:
Explainable image analysis for decision support in medical healthcare. IEEE BigData 2021: 4667-4674 - [c105]Kushankur Ghosh, Colin Bellinger, Roberto Corizzo, Bartosz Krawczyk, Nathalie Japkowicz:
On the combined effect of class imbalance and concept complexity in deep learning. IEEE BigData 2021: 4859-4868 - [c104]Evan Crothers, Herna L. Viktor, Nathalie Japkowicz:
Mean User-Text Agglomeration (MUTA): Practical User Representation and Visualization for Detection of Online Influence Operations. CSoNet 2021: 305-318 - [c103]Yueyang Liu, Zois Boukouvalas, Nathalie Japkowicz:
A Semi-supervised Framework for Misinformation Detection. DS 2021: 57-66 - [c102]Colin Bellinger, Roberto Corizzo, Nathalie Japkowicz:
Calibrated Resampling for Imbalanced and Long-Tails in Deep Learning. DS 2021: 242-252 - [c101]Caitlin Moroney, Evan Crothers, Sudip Mittal, Anupam Joshi, Tülay Adali, Christine Mallinson, Nathalie Japkowicz, Zois Boukouvalas:
The Case for Latent Variable Vs Deep Learning Methods in Misinformation Detection: An Application to COVID-19. DS 2021: 422-432 - [c100]Roberto Corizzo, Michelangelo Ceci, Gianvito Pio, Paolo Mignone, Nathalie Japkowicz:
Spatially-Aware Autoencoders for Detecting Contextual Anomalies in Geo-Distributed Data. DS 2021: 461-471 - [c99]Bartosz Krawczyk, Colin Bellinger, Roberto Corizzo, Nathalie Japkowicz:
Undersampling with Support Vectors for Multi-Class Imbalanced Data Classification. IJCNN 2021: 1-7 - [c98]Nuno Moniz, Paula Branco, Luís Torgo, Nathalie Japkowicz, Michal Wozniak, Shuo Wang:
3rd Workshop on Learning with Imbalanced Domains: Preface. LIDTA@ECML/PKDD 2021: 1-6 - [e5]Nuno Moniz, Paula Branco, Luís Torgo, Nathalie Japkowicz, Michal Wozniak, Shuo Wang:
Third International Workshop on Learning with Imbalanced Domains: Theory and Applications, LIDTA 2021, Bilbao, Spain, September 17, 2021. Proceedings of Machine Learning Research 154, PMLR 2021 [contents] - [i5]Kushankur Ghosh, Colin Bellinger, Roberto Corizzo, Bartosz Krawczyk, Nathalie Japkowicz:
On the combined effect of class imbalance and concept complexity in deep learning. CoRR abs/2107.14194 (2021) - 2020
- [j36]Michelangelo Ceci, Roberto Corizzo, Nathalie Japkowicz, Paolo Mignone, Gianvito Pio:
ECHAD: Embedding-Based Change Detection From Multivariate Time Series in Smart Grids. IEEE Access 8: 156053-156066 (2020) - [j35]Roberto Corizzo, Michelangelo Ceci, Eftim Zdravevski, Nathalie Japkowicz:
Scalable auto-encoders for gravitational waves detection from time series data. Expert Syst. Appl. 151: 113378 (2020) - [j34]Zhen Liu, Nathalie Japkowicz, Ruoyu Wang, Yongming Cai, Deyu Tang, Xianfa Cai:
A statistical pattern based feature extraction method on system call traces for anomaly detection. Inf. Softw. Technol. 126: 106348 (2020) - [j33]Colin Bellinger, Shiven Sharma, Nathalie Japkowicz, Osmar R. Zaïane:
Framework for extreme imbalance classification: SWIM - sampling with the majority class. Knowl. Inf. Syst. 62(3): 841-866 (2020) - [j32]Zhen Liu, Nathalie Japkowicz, Ruoyu Wang, Li Liu:
A sub-concept-based feature selection method for one-class classification. Soft Comput. 24(10): 7047-7062 (2020) - [j31]Jing-Hao Xue, Zhanyu Ma, Manuel Roveri, Nathalie Japkowicz:
Guest Editorial Special Issue on Recent Advances in Theory, Methodology, and Applications of Imbalanced Learning. IEEE Trans. Neural Networks Learn. Syst. 31(8): 2688-2690 (2020) - [c97]Nicholas J. Denis, Danny French, Sébastien Gilbert, Nathalie Japkowicz:
A Cost Skew Aware Predictive System for Chest Drain Management. Canadian AI 2020: 170-176 - [c96]Jonathan Kaufmann, Kathryn Asalone, Roberto Corizzo, Colin Saldanha, John R. Bracht, Nathalie Japkowicz:
One-Class Ensembles for Rare Genomic Sequences Identification. DS 2020: 340-354 - [c95]Zhen Liu, Nathalie Japkowicz, Ruoyu Wang:
Subconcept Based One Class Classification Method with Cluster Updating. ICMLC 2020: 23-28 - [c94]Liming Zhang, Wenbin Zhang, Nathalie Japkowicz:
Conditional-UNet: A Condition-aware Deep Model for Coherent Human Activity Recognition From Wearables. ICPR 2020: 5889-5896 - [i4]Zois Boukouvalas, Christine Mallinson, Evan Crothers, Nathalie Japkowicz, Aritran Piplai, Sudip Mittal, Anupam Joshi, Tülay Adali:
Independent Component Analysis for Trustworthy Cyberspace during High Impact Events: An Application to Covid-19. CoRR abs/2006.01284 (2020) - [i3]Colin Bellinger, Roberto Corizzo, Nathalie Japkowicz:
ReMix: Calibrated Resampling for Class Imbalance in Deep learning. CoRR abs/2012.02312 (2020)
2010 – 2019
- 2019
- [j30]Roberto Corizzo, Michelangelo Ceci, Nathalie Japkowicz:
Anomaly Detection and Repair for Accurate Predictions in Geo-distributed Big Data. Big Data Res. 16: 18-35 (2019) - [j29]Zhen Liu, Nathalie Japkowicz, Ruoyu Wang, Deyu Tang:
Adaptive learning on mobile network traffic data. Connect. Sci. 31(2): 185-214 (2019) - [j28]Ameya Malondkar, Roberto Corizzo, Iluju Kiringa, Michelangelo Ceci, Nathalie Japkowicz:
Spark-GHSOM: Growing Hierarchical Self-Organizing Map for large scale mixed attribute datasets. Inf. Sci. 496: 572-591 (2019) - [j27]Zhen Liu, Ruoyu Wang, Nathalie Japkowicz, Yongming Cai, Deyu Tang, Xianfa Cai:
Mobile app traffic flow feature extraction and selection for improving classification robustness. J. Netw. Comput. Appl. 125: 190-208 (2019) - [c93]William Klement, Sébastien Gilbert, Donna E. Maziak, Andrew J. E. Seely, Farid M. Shamji, Sudhir R. Sundaresan, Patrick J. Villeneuve, Nathalie Japkowicz:
Chest Tube Management After Lung Resection Surgery using a Classifier. DSAA 2019: 432-441 - [c92]Li Liu, Nathalie Japkowicz, Dan Tao, Zhen Liu:
Learning with Drift Detection based on k Time Sub-concept Windows. ICCE-TW 2019: 1-2 - [c91]Sid Ryan, Roberto Corizzo, Iluju Kiringa, Nathalie Japkowicz:
Deep Learning Versus Conventional Learning in Data Streams with Concept Drifts. ICMLA 2019: 1306-1313 - [c90]Sid Ryan, Roberto Corizzo, Iluju Kiringa, Nathalie Japkowicz:
Pattern and Anomaly Localization in Complex and Dynamic Data. ICMLA 2019: 1756-1763 - [c89]Evan Crothers, Nathalie Japkowicz, Herna L. Viktor:
Towards Ethical Content-Based Detection Of Online Influence Campaigns. MLSP 2019: 1-6 - [i2]Richard Hugh Moulton, Herna L. Viktor, Nathalie Japkowicz, João Gama:
Contextual One-Class Classification in Data Streams. CoRR abs/1907.04233 (2019) - [i1]Evan Crothers, Nathalie Japkowicz, Herna L. Viktor:
Towards Ethical Content-Based Detection of Online Influence Campaigns. CoRR abs/1908.11030 (2019) - 2018
- [j26]Daniel Shapiro, Nathalie Japkowicz, Mathieu Lemay, Miodrag Bolic:
Fuzzy String Matching with a Deep Neural Network. Appl. Artif. Intell. 32(1): 1-12 (2018) - [j25]Yue Dong, Nathalie Japkowicz:
Threaded ensembles of autoencoders for stream learning. Comput. Intell. 34(1): 261-281 (2018) - [j24]Shiven Sharma, Anil Somayaji, Nathalie Japkowicz:
Learning over subconcepts: Strategies for 1-class classification. Comput. Intell. 34(2): 440-467 (2018) - [j23]Colin Bellinger, Shiven Sharma, Nathalie Japkowicz:
One-class classification - From theory to practice: A case-study in radioactive threat detection. Expert Syst. Appl. 108: 223-232 (2018) - [j22]Nathalie Japkowicz, Yuval Elovici:
Introduction to the Special Issue on Data Mining for Cybersecurity. IEEE Intell. Syst. 33(2): 3-4 (2018) - [j21]Adrian Taylor, Sylvain P. Leblanc, Nathalie Japkowicz:
Probing the Limits of Anomaly Detectors for Automobiles with a Cyberattack Framework. IEEE Intell. Syst. 33(2): 54-62 (2018) - [j20]Zhao Yang, Nathalie Japkowicz:
Anomaly behaviour detection based on the meta-Morisita index for large scale spatio-temporal data set. J. Big Data 5: 23 (2018) - [j19]Colin Bellinger, Christopher Drummond, Nathalie Japkowicz:
Manifold-based synthetic oversampling with manifold conformance estimation. Mach. Learn. 107(3): 605-637 (2018) - [c88]James Clark, Zhen Liu, Nathalie Japkowicz:
Adaptive Threshold for Outlier Detection on Data Streams. DSAA 2018: 41-49 - [c87]Shiven Sharma, Colin Bellinger, Bartosz Krawczyk, Osmar R. Zaïane, Nathalie Japkowicz:
Synthetic Oversampling with the Majority Class: A New Perspective on Handling Extreme Imbalance. ICDM 2018: 447-456 - [c86]Luís Torgo, Stan Matwin, Nathalie Japkowicz, Bartosz Krawczyk, Nuno Moniz, Paula Branco:
2nd Workshop on Learning with Imbalanced Domains: Preface. LIDTA@ECML/PKDD 2018: 1-7 - [c85]Richard Hugh Moulton, Herna L. Viktor, Nathalie Japkowicz, João Gama:
Clustering in the Presence of Concept Drift. ECML/PKDD (1) 2018: 339-355 - [e4]Michelangelo Ceci, Nathalie Japkowicz, Jiming Liu, George A. Papadopoulos, Zbigniew W. Ras:
Foundations of Intelligent Systems - 24th International Symposium, ISMIS 2018, Limassol, Cyprus, October 29-31, 2018, Proceedings. Lecture Notes in Computer Science 11177, Springer 2018, ISBN 978-3-030-01850-4 [contents] - 2017
- [j18]Nathalie Japkowicz, Stan Matwin:
Special issue on discovery science. Mach. Learn. 106(6): 741-743 (2017) - [c84]Mohsen Ghazel, Nathalie Japkowicz:
Improving Active Learning for One-Class Classification Using Dimensionality Reduction. Canadian AI 2017: 39-44 - [c83]Nathalie Japkowicz, Farzan Erlik Nowruzi, Robert Laganière:
Homography Estimation from Image Pairs with Hierarchical Convolutional Networks. ICCV Workshops 2017: 904-911 - [c82]Zhao Yang, Nathalie Japkowicz:
Meta-Morisita Index: Anomaly Behaviour Detection for Large Scale Tracking Data with Spatio-Temporal Marks. ICDM Workshops 2017: 675-682 - [c81]Colin Bellinger, Shiven Sharma, Osmar R. Zaïane, Nathalie Japkowicz:
Sampling a Longer Life: Binary versus One-class classification Revisited. LIDTA@PKDD/ECML 2017: 64-78 - 2016
- [c80]Yue Dong, Nathalie Japkowicz:
Threaded Ensembles of Supervised and Unsupervised Neural Networks for Stream Learning. Canadian AI 2016: 304-315 - [c79]Adrian Taylor, Sylvain P. Leblanc, Nathalie Japkowicz:
Anomaly Detection in Automobile Control Network Data with Long Short-Term Memory Networks. DSAA 2016: 130-139 - [c78]Colin Bellinger, Christopher Drummond, Nathalie Japkowicz:
Beyond the Boundaries of SMOTE - A Framework for Manifold-Based Synthetically Oversampling. ECML/PKDD (1) 2016: 248-263 - 2015
- [j17]Mohamed A. Ghadie, Nathalie Japkowicz, Theodore J. Perkins:
Gene selection for the reconstruction of stem cell differentiation trees: a linear programming approach. Bioinform. 31(16): 2676-2682 (2015) - [j16]Xuan Liu, Xiaoguang Wang, Stan Matwin, Nathalie Japkowicz:
Meta-MapReduce for scalable data mining. J. Big Data 2: 14 (2015) - [c77]Nathalie Japkowicz, Vincent Barnabe-Lortie, Shawn Horvatic, Jie Zhou:
Multi-class learning using data driven ECOC with deep search and re-balancing. DSAA 2015: 1-10 - [c76]Vincent Barnabe-Lortie, Colin Bellinger, Nathalie Japkowicz:
Active Learning for One-Class Classification. ICMLA 2015: 390-395 - [c75]Colin Bellinger, Ali Amid, Nathalie Japkowicz, Herna L. Viktor:
Multi-label Classification of Anemia Patients. ICMLA 2015: 825-830 - [c74]Colin Bellinger, Nathalie Japkowicz, Christopher Drummond:
Synthetic Oversampling for Advanced Radioactive Threat Detection. ICMLA 2015: 948-953 - [c73]Adrian Taylor, Nathalie Japkowicz, Sylvain P. Leblanc:
Frequency-based anomaly detection for the automotive CAN bus. WCICSS 2015: 45-49 - [e3]Nathalie Japkowicz, Stan Matwin:
Discovery Science - 18th International Conference, DS 2015, Banff, AB, Canada, October 4-6, 2015, Proceedings. Lecture Notes in Computer Science 9356, Springer 2015, ISBN 978-3-319-24281-1 [contents] - 2014
- [j15]Xiaoguang Wang, Xuan Liu, Nathalie Japkowicz, Stan Matwin:
Automated Approach To Classification Of Mine-Like Objects Using Multiple-Aspect Sonar Images. J. Artif. Intell. Soft Comput. Res. 4(2): 133-148 (2014) - [c72]Xiaoguang Wang, Xuan Liu, Nathalie Japkowicz, Stan Matwin:
Ensemble of Multiple Kernel SVM Classifiers. Canadian AI 2014: 239-250 - [c71]Xiaoguang Wang, Xuan Liu, Stan Matwin, Nathalie Japkowicz, Hongyu Guo:
A multi-view two-level classification method for generalized multi-instance problems. IEEE BigData 2014: 104-111 - [c70]Xiaoguang Wang, Xuan Liu, Stan Matwin, Nathalie Japkowicz:
Applying instance-weighted support vector machines to class imbalanced datasets. IEEE BigData 2014: 112-118 - [c69]Hang Shao, Nathalie Japkowicz, Rami S. Abielmona, Rafael Falcon:
Vessel track correlation and association using fuzzy logic and Echo State Networks. IEEE Congress on Evolutionary Computation 2014: 2322-2329 - [c68]Xiaoguang Wang, Xuan Liu, Nathalie Japkowicz, Stan Matwin, Bao Nguyen:
Automatic Target Recognition using multiple-aspect sonar images. IEEE Congress on Evolutionary Computation 2014: 2330-2337 - [c67]Vincent Barnabe-Lortie, Colin Bellinger, Nathalie Japkowicz:
Smoothing gamma ray spectra to improve outlier detection. CISDA 2014: 1-8 - [c66]Hang Shao, Nathalie Japkowicz:
Explicit feature mapping via multi-layer perceptron and its application to Mine-Like Objects detection. IJCNN 2014: 1055-1062 - 2013
- [c65]Xiaoguang Wang, Stan Matwin, Nathalie Japkowicz, Xuan Liu:
Cost-Sensitive Boosting Algorithms for Imbalanced Multi-instance Datasets. Canadian AI 2013: 174-186 - [c64]Xuan Liu, Xiaoguang Wang, Nathalie Japkowicz, Stan Matwin:
An Ensemble Method Based on AdaBoost and Meta-Learning. Canadian AI 2013: 278-285 - [c63]Reva Freedman, Nathalie Japkowicz:
On the Benefits (or Not) of a Clustering Algorithm in Student Tracking. AIED 2013: 840-843 - [c62]Xuan Liu, Xiaoguang Wang, Stan Matwin, Nathalie Japkowicz:
Meta-learning for large scale machine learning with MapReduce. IEEE BigData 2013: 105-110 - [c61]Xiaoguang Wang, Xuan Liu, Nathalie Japkowicz, Stan Matwin:
Resampling and Cost-Sensitive Methods for Imbalanced Multi-instance Learning. ICDM Workshops 2013: 808-816 - [c60]Houman Abbasian, Chris Drummond, Nathalie Japkowicz, Stan Matwin:
Inner Ensembles: Using Ensemble Methods Inside the Learning Algorithm. ECML/PKDD (3) 2013: 33-48 - 2012
- [c59]Hang Shao, Nathalie Japkowicz:
Applying Least Angle Regression to ELM. Canadian AI 2012: 170-180 - [c58]Shiven Sharma, Colin Bellinger, Nathalie Japkowicz:
Clustering Based One-Class Classification for Compliance Verification of the Comprehensive Nuclear-Test-Ban Treaty. Canadian AI 2012: 181-193 - [c57]Nathalie Japkowicz:
Mining the Hidden Structure of Inductive Learning Data Sets. Canadian AI 2012: 318-324 - [c56]Guichong Li, Nathalie Japkowicz, Lian Yang:
Anomaly Detection via Coupled Gaussian Kernels. Canadian AI 2012: 343-349 - [c55]Shiven Sharma, Colin Bellinger, Nathalie Japkowicz, Rodney Berg, R. Kurt Ungar:
Anomaly detection in gamma ray spectra: A machine learning perspective. CISDA 2012: 1-8 - [c54]Kenton White, Guichong Li, Nathalie Japkowicz:
Sampling Online Social Networks Using Coupling from the Past. ICDM Workshops 2012: 266-272 - [c53]Daniel K. Antwi, Herna L. Viktor, Nathalie Japkowicz:
The PerfSim Algorithm for Concept Drift Detection in Imbalanced Data. ICDM Workshops 2012: 619-628 - [c52]Xiaoguang Wang, Hang Shao, Nathalie Japkowicz, Stan Matwin, Xuan Liu, Alex Bourque, Bao Nguyen:
Using SVM with Adaptively Asymmetric MisClassification Costs for Mine-Like Objects Detection. ICMLA (2) 2012: 78-82 - [c51]Colin Bellinger, Shiven Sharma, Nathalie Japkowicz:
One-Class versus Binary Classification: Which and When? ICMLA (2) 2012: 102-106 - 2011
- [c50]Lisa Gaudette, Nathalie Japkowicz:
Compact Features for Sentiment Analysis. Canadian AI 2011: 146-157 - [c49]Colin Bellinger, Nathalie Japkowicz:
Motivating the inclusion of meteorological indicators in the CTBT feature-space. CISDA 2011: 88-95 - [c48]William Klement, Peter A. Flach, Nathalie Japkowicz, Stan Matwin:
Smooth Receiver Operating Characteristics (smROC) Curves. ECML/PKDD (2) 2011: 193-208 - [e2]Nathalie Japkowicz, Mohak Shah:
Evaluating Learning Algorithms: A Classification Perspective. Cambridge University Press 2011, ISBN 9780521196000 - 2010
- [j14]Chris Drummond, Nathalie Japkowicz:
Warning: statistical benchmarking is addictive. Kicking the habit in machine learning. J. Exp. Theor. Artif. Intell. 22(1): 67-80 (2010) - [j13]Benjamin X. Wang, Nathalie Japkowicz:
Boosting support vector machines for imbalanced data sets. Knowl. Inf. Syst. 25(1): 1-20 (2010) - [c47]Guichong Li, Nathalie Japkowicz, Trevor J. Stocki, R. Kurt Ungar:
Cascading Customized Naïve Bayes Couple. Canadian AI 2010: 147-160 - [c46]Houman Abbasian, Chris Drummond, Nathalie Japkowicz, Stan Matwin:
Robustness of Classifiers to Changing Environments. Canadian AI 2010: 232-243 - [c45]Alexandre Kouznetsov, Nathalie Japkowicz:
Using Classifier Performance Visualization to Improve Collective Ranking Techniques for Biomedical Abstracts Classification. Canadian AI 2010: 299-303 - [c44]Farid Seifi, Chris Drummond, Nathalie Japkowicz, Stan Matwin:
Improving Bayesian Learning Using Public Knowledge. Canadian AI 2010: 348-351
2000 – 2009
- 2009
- [j12]Robert Moskovitch, Dima Stopel, Clint Feher, Nir Nissim, Nathalie Japkowicz, Yuval Elovici:
Unknown malcode detection and the imbalance problem. J. Comput. Virol. 5(4): 295-308 (2009) - [c43]Guichong Li, Nathalie Japkowicz, Trevor J. Stocki, R. Kurt Ungar:
Instance Selection by Border Sampling in Multi-class Domains. ADMA 2009: 209-221 - [c42]William Klement, Peter A. Flach, Nathalie Japkowicz, Stan Matwin:
Cost-Based Sampling of Individual Instances. Canadian AI 2009: 86-97 - [c41]Lisa Gaudette, Nathalie Japkowicz:
Evaluation Methods for Ordinal Classification. Canadian AI 2009: 207-210 - [c40]Chris Drummond, Nathalie Japkowicz, William Klement, Sofus A. Macskassy:
Workshop summary: The fourth workshop on evaluation methods for machine learning. ICML 2009: 7 - [e1]Yong Gao, Nathalie Japkowicz:
Advances in Artificial Intelligence, 22nd Canadian Conference on Artificial Intelligence, Canadian AI 2009, Kelowna, Canada, May 25-27, 2009, Proceedings. Lecture Notes in Computer Science 5549, Springer 2009, ISBN 978-3-642-01817-6 [contents] - 2008
- [c39]Rocío Alaíz-Rodríguez, Nathalie Japkowicz:
Assessing the Impact of Changing Environments on Classifier Performance. Canadian AI 2008: 13-24 - [c38]Guichong Li, Nathalie Japkowicz, Trevor J. Stocki, R. Kurt Ungar:
Full Border Identification for Reduction of Training Sets. Canadian AI 2008: 203-215 - [c37]Reuben Smith, Nathalie Japkowicz, Maxwell G. Dondo, Peter Mason:
Using Unsupervised Learning for Network Alert Correlation. Canadian AI 2008: 308-319 - [c36]Guichong Li, Nathalie Japkowicz, Trevor J. Stocki, R. Kurt Ungar:
Border Sampling through Coupling Markov Chain Monte Carlo. ICDM 2008: 393-402 - [c35]Rocío Alaíz-Rodríguez, Nathalie Japkowicz, Peter E. Tischer:
Visualizing Classifier Performance on Different Domains. ICTAI (2) 2008: 3-10 - [c34]Nathalie Japkowicz, Pritika Sanghi, Peter E. Tischer:
Classifier Utility Visualization by Distance-Preserving Projection of High Dimensional Performance D. ISAIM 2008 - [c33]Benjamin X. Wang, Nathalie Japkowicz:
Boosting Support Vector Machines for Imbalanced Data Sets. ISMIS 2008: 38-47 - [c32]Nathalie Japkowicz, Pritika Sanghi, Peter E. Tischer:
A Projection-Based Framework for Classifier Performance Evaluation. ECML/PKDD (1) 2008: 548-563 - [c31]Rocío Alaíz-Rodríguez, Nathalie Japkowicz, Peter E. Tischer:
A Visualization-Based Exploratory Technique for Classifier Comparison with Respect to Multiple Metrics and Multiple Domains. ECML/PKDD (2) 2008: 660-665 - 2007
- [j11]Sarabjot Singh Anand, Daniel Bahls, Catherina Burghart, Mark H. Burstein, Huajun Chen, John Collins, Thomas G. Dietterich, Jon Doyle, Chris Drummond, William Elazmeh, Christopher W. Geib, Judy Goldsmith, Hans W. Guesgen, Jim Hendler, Dietmar Jannach, Nathalie Japkowicz, Ulrich Junker, Gal A. Kaminka, Alfred Kobsa, Jérôme Lang, David B. Leake, Lundy Lewis, Gerard Ligozat, Sofus A. Macskassy, Drew V. McDermott, Ted Metzler, Bamshad Mobasher, Ullas Nambiar, Zaiqing Nie, Klas Orsvärn, Barry O'Sullivan, David V. Pynadath, Jochen Renz, Rita V. Rodríguez, Thomas Roth-Berghofer, Stefan Schulz, Rudi Studer, Yimin Wang, Michael P. Wellman:
AAAI-07 Workshop Reports. AI Mag. 28(4): 119-128 (2007) - [j10]Wangzhong Lu, Jeannette C. M. Janssen, Evangelos E. Milios, Nathalie Japkowicz, Yongzheng Zhang:
Node similarity in the citation graph. Knowl. Inf. Syst. 11(1): 105-129 (2007) - [c30]Yuval Marom, Ingrid Zukerman, Nathalie Japkowicz:
A Meta-learning Approach for Selecting between Response Automation Strategies in a Help-desk Domain. AAAI 2007: 907-912 - [c29]Maxwell G. Dondo, Peter Mason, Nathalie Japkowicz, Reuben Smith:
AutoCorrel II: a neural network event correlation approach. Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security 2007: 65700H - [c28]Christina George, Nathalie Japkowicz:
A Unified Framework for Relative Clause Simplification and Relative Pronoun Correction. IC-AI 2007: 602-608 - 2006
- [j9]Wolfgang Achtner, Esma Aïmeur, Sarabjot Singh Anand, Douglas E. Appelt, Naveen Ashish, Tiffany Barnes, Joseph E. Beck, M. Bernardine Dias, Prashant Doshi, Chris Drummond, William Elazmeh, Ariel Felner, Dayne Freitag, Hector Geffner, Christopher W. Geib, Richard Goodwin, Robert C. Holte, Frank Hutter, Fair Isaac, Nathalie Japkowicz, Gal A. Kaminka, Sven Koenig, Michail G. Lagoudakis, David B. Leake, Lundy Lewis, Hugo Liu, Ted Metzler, Rada Mihalcea, Bamshad Mobasher, Pascal Poupart, David V. Pynadath, Thomas Roth-Berghofer, Wheeler Ruml, Stefan Schulz, Sven Schwarz, Stephanie Seneff, Amit P. Sheth, Ron Sun, Michael Thielscher, Afzal Upal, Jason D. Williams, Steve J. Young, Dmitry Zelenko:
Reports on the Twenty-First National Conference on Artificial Intelligence (AAAI-06) Workshop Program. AI Mag. 27(4): 92-102 (2006) - [j8]Jerffeson Teixeira de Souza, Stan Matwin, Nathalie Japkowicz:
Parallelizing Feature Selection. Algorithmica 45(3): 433-456 (2006) - [c27]Marina Sokolova, Nathalie Japkowicz, Stan Szpakowicz:
Beyond Accuracy, F-Score and ROC: A Family of Discriminant Measures for Performance Evaluation. Australian Conference on Artificial Intelligence 2006: 1015-1021 - [c26]Maxwell G. Dondo, Nathalie Japkowicz, Reuben Smith:
AutoCorrel: a neural network event correlation approach. Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security 2006: 62410N - [c25]William Elazmeh, Nathalie Japkowicz, Stan Matwin:
Evaluating Misclassifications in Imbalanced Data. ECML 2006: 126-137 - [c24]Olivier Henchiri, Nathalie Japkowicz:
A Feature Selection and Evaluation Scheme for Computer Virus Detection. ICDM 2006: 891-895 - [c23]Taeho Jo, Nathalie Japkowicz:
Three and Four Phase Scenarios for Dynamic Document Organization. SMC 2006: 2228-2233 - 2005
- [c22]Quintin Armour, William Elazmeh, Nour El-Kadri, Nathalie Japkowicz, Stan Matwin:
Privacy Compliance Enforcement in Email. Canadian AI 2005: 194-204 - [c21]Hui Li, Nathalie Japkowicz, Caroline Barrière:
English to Chinese Translation of Prepositions. Canadian AI 2005: 412-416 - [c20]Narjès Boufaden, William Elazmeh, Yimin Ma, Stan Matwin, Nour El-Kadri, Nathalie Japkowicz:
PEEP- An Information Extraction base approach for Privacy Protection in Email. CEAS 2005 - [c19]Reuben Smith, Nathalie Japkowicz, Maxwell G. Dondo:
Clustering using an Autoassociator: A Case Study in Network Event Correlation. IASTED PDCS 2005: 613-618 - [c18]Jerffeson Teixeira de Souza, Nathalie Japkowicz, Stan Matwin:
STochFS: A Framework for Combining Feature Selection Outcomes Through a Stochastic Process. PKDD 2005: 667-674 - [c17]Narjès Boufaden, William Elazmeh, Stan Matwin, Nathalie Japkowicz:
PEEP- Privacy Enforcement in Email Project. PST 2005 - 2004
- [j7]Andrew Estabrooks, Taeho Jo, Nathalie Japkowicz:
A Multiple Resampling Method for Learning from Imbalanced Data Sets. Comput. Intell. 20(1): 18-36 (2004) - [j6]Nitesh V. Chawla, Nathalie Japkowicz, Aleksander Kotcz:
Editorial: special issue on learning from imbalanced data sets. SIGKDD Explor. 6(1): 1-6 (2004) - [j5]Taeho Jo, Nathalie Japkowicz:
Class imbalances versus small disjuncts. SIGKDD Explor. 6(1): 40-49 (2004) - [c16]Loïs Rigouste, Stan Szpakowicz, Nathalie Japkowicz, Terry Copeck:
An Automatic Evaluation Framework for Improving a Configurable Text Summarizer. Canadian AI 2004: 529-533 - [c15]Rehan Akbani, Stephen Kwek, Nathalie Japkowicz:
Applying Support Vector Machines to Imbalanced Datasets. ECML 2004: 39-50 - [c14]Justin Zhijun Zhan, Stan Matwin, Nathalie Japkowicz, LiWu Chang:
Privacy-Preserving Collaborative Association Rule Mining. ICEB 2004: 1172-1178 - 2003
- [c13]Marvin Zaluski, Nathalie Japkowicz, Stan Matwin:
Case Authoring from Text and Historical Experiences. AI 2003: 222-236 - 2002
- [j4]Nathalie Japkowicz, Shaju Stephen:
The class imbalance problem: A systematic study. Intell. Data Anal. 6(5): 429-449 (2002) - [c12]Terry Copeck, Nathalie Japkowicz, Stan Szpakowicz:
Text Summarization as Controlled Search. AI 2002: 268-280 - [c11]Marina Sokolova, Mario Marchand, Nathalie Japkowicz, John Shawe-Taylor:
The Decision List Machine. NIPS 2002: 921-928 - 2001
- [j3]Yves Lespérance, Gerd Wagner, William P. Birmingham, Kurt D. Bollacker, Alexander Nareyek, J. Paul Walser, David W. Aha, Timothy W. Finin, Benjamin N. Grosof, Nathalie Japkowicz, Robert Holte, Lise Getoor, Carla P. Gomes, Holger H. Hoos, Alan C. Schultz, Miroslav Kubat, Tom M. Mitchell, Jörg Denzinger, Yolanda Gil, Karen L. Myers, Claudio Bettini, Angelo Montanari:
AAAI 2000 Workshop Reports. AI Mag. 22(1): 127-136 (2001) - [j2]Nathalie Japkowicz:
Supervised Versus Unsupervised Binary-Learning by Feedforward Neural Networks. Mach. Learn. 42(1/2): 97-122 (2001) - [c10]Nathalie Japkowicz:
Concept-Learning in the Presence of Between-Class and Within-Class Imbalances. AI 2001: 67-77 - [c9]Adam Nickerson, Nathalie Japkowicz, Evangelos E. Milios:
Using Unsupervised Learning to Guide Resampling in Imbalanced Data Sets. AISTATS 2001: 224-228 - [c8]Wangzhong Lu, Jeannette C. M. Janssen, Evangelos E. Milios, Nathalie Japkowicz:
Node similarity in networked information spaces. CASCON 2001: 11 - [c7]Andrew Estabrooks, Nathalie Japkowicz:
A mixture-of-experts framework for text classification. CoNLL 2001 - [c6]Andrew Estabrooks, Nathalie Japkowicz:
A Mixture-of-Experts Framework for Learning from Imbalanced Data Sets. IDA 2001: 34-43 - 2000
- [j1]Nathalie Japkowicz, Stephen Jose Hanson, Mark A. Gluck:
Nonlinear Autoassociation Is Not Equivalent to PCA. Neural Comput. 12(3): 531-545 (2000) - [c5]Todd Eavis, Nathalie Japkowicz:
A Recognition-Based Alternative to Discrimination-Based Multi-layer Perceptrons. AI 2000: 280-292
1990 – 1999
- 1999
- [c4]Nathalie Japkowicz, Stephen Jose Hanson:
Adaptability of the backpropagation procedure. IJCNN 1999: 1710-1715 - 1995
- [c3]Nathalie Japkowicz, Catherine Myers, Mark A. Gluck:
A Novelty Detection Approach to Classification. IJCAI 1995: 518-523 - 1994
- [c2]Haym Hirsh, Nathalie Japkowicz:
Bootstrapping Training-Data Representations for Inductive Learning: A Case Study in Molecular Biology. AAAI 1994: 639-644 - 1991
- [c1]Nathalie Japkowicz, Janyce Wiebe:
A System for Translating Locative Prepositions from English into French. ACL 1991: 153-160
Coauthor Index
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