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Herna L. Viktor

Herna Lydia Viktor

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affiliation: University of Ottawa, School of Electrical Engineering and Computer Science, ON, Canada
affiliation (former): University of Pretoria, Department of Informatics, South Africa
affiliation (PhD 1999): Stellenbosch University, South Africa

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2020 – today

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2024
[j27]
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Mohammed Awal Kassim, Herna L. Viktor, Wojtek Michalowski:
Multi-Label Lifelong Machine Learning: A Scoping Review of Algorithms, Techniques, and Applications. IEEE Access 12: 74539-74557 (2024)
[j26]
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Pouya Khodaee, Herna L. Viktor, Wojtek Michalowski:
Knowledge transfer in lifelong machine learning: a systematic literature review. Artif. Intell. Rev. 57(8): 217 (2024)
[j25]
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Paul Kiyambu Mvula, Paula Branco, Guy-Vincent Jourdan, Herna Lydia Viktor:
A Survey on the Applications of Semi-supervised Learning to Cyber-security. ACM Comput. Surv. 56(10): 253 (2024)
[j24]
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Kenniy Olorunnimbe, Herna L. Viktor:
Ensemble of temporal Transformers for financial time series. J. Intell. Inf. Syst. 62(4): 1087-1111 (2024)
[c83]
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Kenniy Olorunnimbe, Herna L. Viktor:
Enhancing Temporal Transformers for Financial Time Series via Local Surrogate Interpretability. ISMIS 2024: 149-159
2023
[j23]
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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)
[j22]
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Kenniy Olorunnimbe, Herna L. Viktor:
Deep learning in the stock market - a systematic survey of practice, backtesting, and applications. Artif. Intell. Rev. 56(3): 2057-2109 (2023)
[j21]
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Farnaz Sadeghi, Herna L. Viktor, Parsa Vafaie:
DynaQ: online learning from imbalanced multi-class streams through dynamic sampling. Appl. Intell. 53(21): 24908-24930 (2023)
[j20]
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Eric Paquet, Herna L. Viktor, Kamel Madi, Junzheng Wu:
Deformable Protein Shape Classification Based on Deep Learning, and the Fractional Fokker-Planck and Kähler-Dirac Equations. IEEE Trans. Pattern Anal. Mach. Intell. 45(1): 391-407 (2023)
[c82]
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Paul Kiyambu Mvula, Paula Branco, Guy-Vincent Jourdan, Herna L. Viktor:
HEART: Heterogeneous Log Anomaly Detection Using Robust Transformers. DS 2023: 673-687
[c81]
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Eric Paquet, Herna L. Viktor, Wojtek Michalowski, Gabriel St-Pierre Lemieux:
ProVolOne - Protein Volume Prediction Using a Multi-attention, Multi-resolution Deep Neural Network and Finite Element Analysis. LOD (1) 2023: 274-287
[c80]
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  - conf/techdebt/AikenMBJSV23
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William Aiken, Paul Kiyambu Mvula, Paula Branco, Guy-Vincent Jourdan, Mehrdad Sabetzadeh, Herna L. Viktor:
Measuring Improvement of F1-Scores in Detection of Self-Admitted Technical Debt. TechDebt@ICSE 2023: 37-41
[i9]
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  - journals/corr/abs-2301-05402
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Evan Crothers, Herna L. Viktor, Nathalie Japkowicz:
In BLOOM: Creativity and Affinity in Artificial Lyrics and Art. CoRR abs/2301.05402 (2023)
[i8]
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  - journals/corr/abs-2303-09617
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William Aiken, Paul Kiyambu Mvula, Paula Branco, Guy-Vincent Jourdan, Mehrdad Sabetzadeh, Herna L. Viktor:
Measuring Improvement of F₁-Scores in Detection of Self-Admitted Technical Debt. CoRR abs/2303.09617 (2023)
[i7]
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  - journals/corr/abs-2308-06795
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Evan Crothers, Herna L. Viktor, Nathalie Japkowicz:
Faithful to Whom? Questioning Interpretability Measures in NLP. CoRR abs/2308.06795 (2023)
2022
[j19]
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Gabriel St-Pierre Lemieux, Eric Paquet, Herna L. Viktor, Wojtek Michalowski:
Geometric Deep Learning for Protein-Protein Interaction Predictions. IEEE Access 10: 90045-90055 (2022)
[j18]
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  - journals/displays/PaquetVL22
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Eric Paquet, Herna L. Viktor, Gabriel St-Pierre Lemieux:
Exact shape flattening by means of Weitzenböck geometry and teleparallel distance. Displays 75: 102323 (2022)
[j17]
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  - journals/eswa/MvulaBJV22
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Paul Kiyambu Mvula, Paula Branco, Guy-Vincent Jourdan, Herna L. Viktor:
COVID-19 malicious domain names classification. Expert Syst. Appl. 204: 117553 (2022)
[c79]
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Farnaz Sadeghi, Herna L. Viktor:
MQ-OFL: Multi-sensitive Queue-based Online Fair Learning. DS 2022: 271-285
[c78]
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  - conf/ijcnn/CrothersJVB22
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Evan Crothers, Nathalie Japkowicz, Herna L. Viktor, Paula Branco:
Adversarial Robustness of Neural-Statistical Features in Detection of Generative Transformers. IJCNN 2022: 1-8
[c77]
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Kenniy Olorunnimbe, Herna L. Viktor:
Similarity Embedded Temporal Transformers: Enhancing Stock Predictions with Historically Similar Trends. ISMIS 2022: 388-398
[c76]
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  - conf/mod/WuPVM22
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Junzheng Wu, Eric Paquet, Herna L. Viktor, Wojtek Michalowski:
Adapting to Complexity: Deep Learnable Architecture for Protein-protein Interaction Predictions. LOD (1) 2022: 528-542
[i6]
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  - journals/corr/abs-2203-07983
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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)
[i5]
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  - journals/corr/abs-2210-07321
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Evan Crothers, Nathalie Japkowicz, Herna L. Viktor:
Machine Generated Text: A Comprehensive Survey of Threat Models and Detection Methods. CoRR abs/2210.07321 (2022)
2021
[j16]
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  - journals/eswa/AlabdulrahmanV21
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Rabaa Alabdulrahman, Herna L. Viktor:
Catering for unique tastes: Targeting grey-sheep users recommender systems through one-class machine learning. Expert Syst. Appl. 166: 114061 (2021)
[c75]
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  - conf/csonet/CrothersVJ21
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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
[c74]
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  - conf/fps/ChhabraBJV21
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Anubhav Chhabra, Paula Branco, Guy-Vincent Jourdan, Herna L. Viktor:
An Extensive Comparison of Systems for Entity Extraction from Log Files. FPS 2021: 376-392
[c73]
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Junzheng Wu, Eric Paquet, Herna L. Viktor, Wojtek Michalowski:
Paying Attention: Using a Siamese Pyramid Network for the Prediction of Protein-Protein Interactions with Folding and Self-Binding Primary Sequences. IJCNN 2021: 1-8
[c72]
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  - conf/lidta/SadeghiV21
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Farnaz Sadeghi, Herna L. Viktor:
Online-MC-Queue: Learning from Imbalanced Multi-Class Streams. LIDTA@ECML/PKDD 2021: 21-34
[c71]
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  - conf/mod/VafaieVPM21
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Parsa Vafaie, Herna L. Viktor, Eric Paquet, Wojtek Michalowski:
Online Semi-supervised Learning from Evolving Data Streams with Meta-features and Deep Reinforcement Learning. LOD 2021: 70-85
2020
[c70]
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  - conf/ic3k/AbdulrahmanV20
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Rabaa Abdulrahman, Herna L. Viktor:
Personalised Recommendation Systems and the Impact of COVID-19: Perspectives, Opportunities and Challenges. KDIR 2020: 295-301
[c69]
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  - conf/icdm/VafaieVM20
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Parsa Vafaie, Herna L. Viktor, Wojtek Michalowski:
Multi-class imbalanced semi-supervised learning from streams through online ensembles. ICDM (Workshops) 2020: 867-874

2010 – 2019

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2019
[c68]
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  - conf/dawak/SelinV19
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Erik G. Selin, Herna L. Viktor:
Improved Programming-Language Independent MapReduce on Shared-Memory Systems. DaWaK 2019: 206-220
[c67]
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  - conf/globecom/QuintalKSKV19
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Kyle Quintal, Ertugrul Kara, Murat Simsek, Burak Kantarci, Herna L. Viktor:
Sensory Data-Driven Modeling of Adversaries in Mobile Crowdsensing Platforms. GLOBECOM 2019: 1-6
[c66]
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Rabaa Alabdulrahman, Herna L. Viktor, Eric Paquet:
Active Learning and Deep Learning for the Cold-Start Problem in Recommendation System: A Comparative Study. IC3K 2019: 24-53
[c65]
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Rabaa Alabdulrahman, Herna L. Viktor, Eric Paquet:
Active Learning and User Segmentation for the Cold-start Problem in Recommendation Systems. KDIR 2019: 113-123
[c64]
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  - conf/mlsp/CrothersJV19
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Evan Crothers, Nathalie Japkowicz, Herna L. Viktor:
Towards Ethical Content-Based Detection Of Online Influence Campaigns. MLSP 2019: 1-6
[c63]
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  - conf/pkdd/FloydV19
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Sean L. A. Floyd, Herna L. Viktor:
Soft Voting Windowing Ensembles for Learning from Partially Labelled Streams. NFMCP@PKDD/ECML 2019: 85-99
[i4]
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  - journals/corr/abs-1907-04233
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Richard Hugh Moulton, Herna L. Viktor, Nathalie Japkowicz, João Gama:
Contextual One-Class Classification in Data Streams. CoRR abs/1907.04233 (2019)
[i3]
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  - journals/corr/abs-1908-11030
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Evan Crothers, Nathalie Japkowicz, Herna L. Viktor:
Towards Ethical Content-Based Detection of Online Influence Campaigns. CoRR abs/1908.11030 (2019)
2018
[j15]
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M. Kehinde Olorunnimbe, Herna L. Viktor, Eric Paquet:
Dynamic adaptation of online ensembles for drifting data streams. J. Intell. Inf. Syst. 50(2): 291-313 (2018)
[j14]
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Ali Pesaranghader, Herna L. Viktor, Eric Paquet:
Reservoir of diverse adaptive learners and stacking fast hoeffding drift detection methods for evolving data streams. Mach. Learn. 107(11): 1711-1743 (2018)
[c62]
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Erik G. Selin, Herna L. Viktor:
XRT: Programming-Language Independent MapReduce on Shared-Memory Systems. BigData Congress 2018: 182-189
[c61]
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Rabaa Alabdulrahman, Herna L. Viktor, Eric Paquet:
HCC-Learn Framework for Hybrid Learning in Recommender Systems. IC3K 2018: 25-49
[c60]
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Rabaa Alabdulrahman, Herna L. Viktor, Eric Paquet:
Beyond k-NN: Combining Cluster Analysis and Classification for Recommender Systems. KDIR 2018: 80-89
[c59]
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Ali Pesaranghader, Herna L. Viktor, Eric Paquet:
McDiarmid Drift Detection Methods for Evolving Data Streams. IJCNN 2018: 1-9
[c58]
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Olubukola M. Olaitan, Herna L. Viktor:
SCUT-DS: Learning from Multi-class Imbalanced Canadian Weather Data. ISMIS 2018: 291-301
[c57]
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Richard Hugh Moulton, Herna L. Viktor, Nathalie Japkowicz, João Gama:
Clustering in the Presence of Concept Drift. ECML/PKDD (1) 2018: 339-355
2017
[c56]
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Sarah D'Ettorre, Herna L. Viktor, Eric Paquet:
Context-Based Abrupt Change Detection and Adaptation for Categorical Data Streams. DS 2017: 3-17
[c55]
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Sahil Saroop, Herna L. Viktor, Patrick McCurdy, Eric Paquet:
Exploring Mediatoil Imagery: A Content-based Approach. KDIR 2017: 246-254
[c54]
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Andrei Belcin, Sean Floyd, Areej Asiri, Herna L. Viktor:
An Exploratory Study of Oral and Dental Health in Canada. ICMLA 2017: 1114-1119
[i2]
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  - journals/corr/abs-1709-02457
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Ali Pesaranghader, Herna L. Viktor, Eric Paquet:
Reservoir of Diverse Adaptive Learners and Stacking Fast Hoeffding Drift Detection Methods for Evolving Data Streams. CoRR abs/1709.02457 (2017)
[i1]
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Ali Pesaranghader, Herna L. Viktor, Eric Paquet:
McDiarmid Drift Detection Methods for Evolving Data Streams. CoRR abs/1710.02030 (2017)
2016
[j13]
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Daniel K. Antwi, Herna L. Viktor:
Dynamic Materialization for Building Personalized Smart Cubes. Trans. Large Scale Data Knowl. Centered Syst. 26: 61-88 (2016)
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Ali Pesaranghader, Herna L. Viktor, Eric Paquet:
A Framework for Classification in Data Streams Using Multi-strategy Learning. DS 2016: 341-355
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Rabaa Alabdulrahman, Herna L. Viktor, Eric Paquet:
An Active Learning Approach for Ensemble-based Data Stream Mining. KDIR 2016: 275-282
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Ali Pesaranghader, Herna L. Viktor:
Fast Hoeffding Drift Detection Method for Evolving Data Streams. ECML/PKDD (2) 2016: 96-111
2015
[c50]
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Joanna Ng, Frank Dehne, Stan Matwin, Herna L. Viktor, Olga Baysal:
Data science workshop: experience driven analytics. CASCON 2015: 344-346
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Astha Agrawal, Herna L. Viktor, Eric Paquet:
SCUT: Multi-Class Imbalanced Data Classification using SMOTE and Cluster-based Undersampling. KDIR 2015: 226-234
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Colin Bellinger, Ali Amid, Nathalie Japkowicz, Herna L. Viktor:
Multi-label Classification of Anemia Patients. ICMLA 2015: 825-830
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Muhammed K. Olorunnimbe, Herna L. Viktor:
Tweets as a Vote: Exploring Political Sentiments on Twitter for Opinion Mining. ISMIS 2015: 180-185
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M. Kehinde Olorunnimbe, Herna L. Viktor, Eric Paquet:
Intelligent Adaptive Ensembles for Data Stream Mining: A High Return on Investment Approach. NFMCP 2015: 61-75
2014
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Eric Paquet, Dela De Youngster, Herna L. Viktor, Emil M. Petriu:
Physics-based measurements, reflective measurements and meta-measurements for nonrigid and deformable shapes with application to structural proteomics and macromolecular docking. CIVEMSA 2014: 112-117
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Daniel K. Antwi, Herna L. Viktor:
Building Smart Cubes for Reliable and Faster Access to Data. DaWaK 2014: 254-265
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Hamid Hadavi, Herna L. Viktor, Eric Paquet:
A Quantum Particle Swarm Optimization and Genetic Algorithm approach to the correspondence problem. INISTA 2014: 226-233
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Parinaz Sobhani, Herna L. Viktor, Stan Matwin:
Learning from Imbalanced Data Using Ensemble Methods and Cluster-Based Undersampling. NFMCP 2014: 69-83
2013
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Hongyu Guo, Herna L. Viktor, Eric Paquet:
Reducing the size of databases for multirelational classification: a subgraph-based approach. J. Intell. Inf. Syst. 40(2): 349-374 (2013)
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Dela De Youngster, Eric Paquet, Herna L. Viktor, Emil M. Petriu:
An isometry-invariant spectral approach for protein-protein docking. BIBE 2013: 1-6
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Eric Paquet, Herna Lydia Viktor:
Isometrically Invariant Description of Deformable Objects Based on the Fractional Heat Equation. CAIP (2) 2013: 135-143
[c39]
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Salvador Valencia Rodríguez, Herna Lydia Viktor:
A Personalized Location Aware Multi-Criteria Recommender System Based on Context-Aware User Preference Models. AIAI 2013: 30-39
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Herna L. Viktor, Eric Paquet, Jing Zhao:
Artificial neural networks for predicting 3D protein shapes from amino acid sequences. IJCNN 2013: 1-8
[c37]
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Joshua Weissbock, Herna L. Viktor, Diana Inkpen:
Use of Performance Metrics to Forecast Success in the National Hockey League. MLSA@PKDD/ECML 2013: 39-48
2012
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Herna L. Viktor, Isis Peña, Eric Paquet:
Who are our clients: consumer segmentation through explorative data mining. Int. J. Data Min. Model. Manag. 4(3): 286-308 (2012)
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Daniel K. Antwi, Herna L. Viktor, Nathalie Japkowicz:
The PerfSim Algorithm for Concept Drift Detection in Imbalanced Data. ICDM Workshops 2012: 619-628
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Michelangelo Ceci, Annalisa Appice, Herna L. Viktor, Donato Malerba, Eric Paquet, Hongyu Guo:
Transductive Relational Classification in the Co-training Paradigm. MLDM 2012: 11-25
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Eric Paquet, Herna Lydia Viktor, Hongyu Guo:
Learning in the Presence of Large Fluctuations: A Study of Aggregation and Correlation. NFMCP 2012: 49-63
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Yasser Jafer, Herna L. Viktor, Eric Paquet:
Aggregation and privacy in multi-relational databases. PST 2012: 67-74
2011
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Hongyu Guo, Herna L. Viktor, Eric Paquet:
Privacy Disclosure and Preservation in Learning with Multi-Relational Databases. J. Comput. Sci. Eng. 5(3): 183-196 (2011)
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Eric Paquet, Herna L. Viktor:
Probability distributions from Riemannian geometry, generalized hybrid Monte Carlo sampling, and path integrals. Three-Dimensional Imaging, Interaction, and Measurement 2011: 78640X
[c31]
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Hongyu Guo, Herna L. Viktor, Eric Paquet:
Privacy leakage in multi-relational learning via unwanted classification models. CASCON 2011: 45-59
[c30]
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Nadia Farhanaz Azam, Herna L. Viktor:
A Comparative Evaluation of Proximity Measures for Spectral Clustering. KDIR 2011: 30-41
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Nadia Farhanaz Azam, Herna L. Viktor:
Spectral Clustering: An Explorative Study of Proximity Measures. IC3K 2011: 60-78
[c28]
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Eric Paquet, Herna L. Viktor, Hongyu Guo:
To Aggregate or Not to Aggregate: That is the Question. KDIR 2011: 354-357
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Eric Paquet, Herna L. Viktor:
Multimodal Representations, Indexing, Unexpectedness and Proteins. IEA/AIE (1) 2011: 85-94
2010
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Eric Paquet, Herna L. Viktor:
Index spaces for 3D retrieval: toward a better understanding of their geometry and distribution. Three-Dimensional Image Processing (3DIP) and Applications 2010: 75260J
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Herna L. Viktor, Bo Wang, Eric Paquet, Julie Doyle:
Preserving object-relational databases for the next generations. ICDIM 2010: 11-18
[c24]
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Hongyu Guo, Herna L. Viktor, Eric Paquet:
Identifying and Preventing Data Leakage in Multi-relational Classification. ICDM Workshops 2010: 458-465

2000 – 2009

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What is the meaning of the colors in the publication lists?

2009
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Julie Doyle, Herna L. Viktor, Eric Paquet:
Long-term digital preservation: preserving authenticity and usability of 3-D data. Int. J. Digit. Libr. 10(1): 33-47 (2009)
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Isis Peña, Herna L. Viktor, Eric Paquet:
Finding Clothing That Fit through Cluster Analysis and Objective Interestingness Measures. DaWaK 2009: 216-228
[c22]
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Eric Paquet, Herna Lydia Viktor:
Finding Protein Family Similarities in Real Time through Multiple 3D and 2D Representations, Indexing and Exhaustive Searching. KDIR 2009: 127-133
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Isis Peña, Herna Lydia Viktor, Eric Paquet:
Explorative Data Mining for the Sizing of Population Groups. KDIR 2009: 152-159
[r1]
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Herna L. Viktor, Eric Paquet:
Visual Data Mining from Visualization to Visual Information Mining. Encyclopedia of Data Warehousing and Mining 2009: 2056-2061
2008
[j8]
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Hongyu Guo, Herna L. Viktor:
Learning from Skewed Class Multi-relational Databases. Fundam. Informaticae 89(1): 69-94 (2008)
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Hongyu Guo, Herna L. Viktor:
Multirelational classification: a multiple view approach. Knowl. Inf. Syst. 17(3): 287-312 (2008)
[j6]
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Eric Paquet, Herna L. Viktor:
Capri/MR: exploring protein databases from a structural and physicochemical point of view. Proc. VLDB Endow. 1(2): 1504-1507 (2008)
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Julie Doyle, Herna L. Viktor, Eric Paquet:
Preservation metadata - a framework for 3D data based on the Semantic Web. ICDIM 2008: 925-927
2007
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Eric Paquet, Herna L. Viktor:
Adjustment of Virtual Mannequins Through Anthropometric Measurements, Cluster Analysis, and Content-Based Retrieval of 3-D Body Scans. IEEE Trans. Instrum. Meas. 56(5): 1924-1929 (2007)
[c19]
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Julie Doyle, Herna L. Viktor, Eric Paquet:
Long term digital preservation - An end user's perspective. ICDIM 2007: 146-151
[c18]
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Hongyu Guo, Herna L. Viktor, Eric Paquet:
Pruning Relations for Substructure Discovery of Multi-relational Databases. PKDD 2007: 462-470
2006
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Hongyu Guo, Herna L. Viktor:
Multi-view ANNs for Multi-relational Classification. IJCNN 2006: 5259-5266
[c16]
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Hongyu Guo, Herna L. Viktor:
Mining relational data through correlation-based multiple view validation. KDD 2006: 567-573
[c15]
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Herna L. Viktor, Eric Paquet, Hongyu Guo:
Measuring to Fit: Virtual Tailoring Through Cluster Analysis and Classification. PKDD 2006: 395-406
2005
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Eric Paquet, Herna L. Viktor:
On the application of 3D technologies to the framework of cultural heritage. Ann. des Télécommunications 60(11-12): 1379-1393 (2005)
2004
[j3]
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Hongyu Guo, Herna L. Viktor:
Learning from imbalanced data sets with boosting and data generation: the DataBoost-IM approach. SIGKDD Explor. 6(1): 30-39 (2004)
[c14]
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Hongyu Guo, Herna L. Viktor:
Boosting with Data Generation: Improving the Classification of Hard to Learn Examples. IEA/AIE 2004: 1082-1091
[c13]
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Herna L. Viktor, Hongyu Guo:
Multiple Classifier Prediction Improvements against Imbalanced Datasets through Added Synthetic Examples. SSPR/SPR 2004: 974-982
2003
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Sabry F. El-Hakim, Lorenzo Gonzo, Michel Picard, Stefano Girardi, Andrea Simoni, Eric Paquet, Herna L. Viktor, Claus Brenner:
Visualisation of Highly Textured Surfaces. VAST 2003: 203-212
2002
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Eric Paquet, Herna L. Viktor, Shawn Peter:
The Virtual Boutique: a Synergic Approach to Virtualization, Content-based Management of 3D Information, 3D Data Mining an Virtual Reality for E-commerce. 3DPVT 2002: 268-276
2000
[j2]
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Herna L. Viktor, Heidi Arndt:
Data mining in practice: from data to knowledge using a hybrid mining approach. Int. J. Comput. Syst. Signals 1(2): 139-153 (2000)
[c10]
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Herna L. Viktor, Heidi Arndt, Mauritz Oberholzer:
Enhancing Government Decision Making Through Knowledge Discovery from Data. ECIS 2000: 266-273
[c9]
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Herna L. Viktor:
Cooperating to Learn: Knowledge Discovery through Intelligent Learning Agents. ICMAS 2000: 453-454
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Herna L. Viktor:
Generating New Patterns for Information Gain and Improved Neural Network Learning. IJCNN (4) 2000: 529-534
[c7]
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Heidi Arndt, Herna L. Viktor:
Dynamic knowledge-base construction through knowledge discovery. IRMA Conference 2000: 934-935

1990 – 1999

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1999
[c6]
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J. F. Francois Weilbach, Herna L. Viktor:
The Development of a Data Warehouse for Policy Making: A Case Study. HICSS 1999
[c5]
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Herna L. Viktor, Ian Cloete:
Improved generalisation using cooperative learning and rule extraction. IJCNN 1999: 1345-1349
[c4]
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Andries P. Engelbrecht, Herna L. Viktor:
Rule Improvement Through Decision Boundary Detection Using Sensitivity Analysis. IWANN (2) 1999: 78-84
1998
[j1]
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Herna L. Viktor, Ian Cloete:
Inductive Learning with a Computational Network. J. Intell. Robotic Syst. 21(2): 131-141 (1998)
1997
[c3]
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Herna L. Viktor, Ian Cloete:
Learning by Co-operation: Combining Multiple Computationally Intelligent Programs into a Computational Network. ICANNGA 1997: 543-546
1995
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Herna L. Viktor, Andries P. Engelbrecht, Ian Cloete:
Reduction of symbolic rules from artificial neural networks using sensitivity analysis. ICNN 1995: 1788-1793
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Herna L. Viktor, Ian Cloete:
Extracting DNF Rules from Artificial Neural Networks. IWANN 1995: 611-618

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