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Herna L. 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
- 2024
- [j27]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]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]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]Kenniy Olorunnimbe, Herna L. Viktor:
Ensemble of temporal Transformers for financial time series. J. Intell. Inf. Syst. 62(4): 1087-1111 (2024) - [c83]Kenniy Olorunnimbe, Herna L. Viktor:
Enhancing Temporal Transformers for Financial Time Series via Local Surrogate Interpretability. ISMIS 2024: 149-159 - 2023
- [j23]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]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]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]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]Paul Kiyambu Mvula, Paula Branco, Guy-Vincent Jourdan, Herna L. Viktor:
HEART: Heterogeneous Log Anomaly Detection Using Robust Transformers. DS 2023: 673-687 - [c81]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]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]Evan Crothers, Herna L. Viktor, Nathalie Japkowicz:
In BLOOM: Creativity and Affinity in Artificial Lyrics and Art. CoRR abs/2301.05402 (2023) - [i8]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]Evan Crothers, Herna L. Viktor, Nathalie Japkowicz:
Faithful to Whom? Questioning Interpretability Measures in NLP. CoRR abs/2308.06795 (2023) - 2022
- [j19]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]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]Paul Kiyambu Mvula, Paula Branco, Guy-Vincent Jourdan, Herna L. Viktor:
COVID-19 malicious domain names classification. Expert Syst. Appl. 204: 117553 (2022) - [c79]Farnaz Sadeghi, Herna L. Viktor:
MQ-OFL: Multi-sensitive Queue-based Online Fair Learning. DS 2022: 271-285 - [c78]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]Kenniy Olorunnimbe, Herna L. Viktor:
Similarity Embedded Temporal Transformers: Enhancing Stock Predictions with Historically Similar Trends. ISMIS 2022: 388-398 - [c76]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]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]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]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]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]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]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]Farnaz Sadeghi, Herna L. Viktor:
Online-MC-Queue: Learning from Imbalanced Multi-Class Streams. LIDTA@ECML/PKDD 2021: 21-34 - [c71]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]Rabaa Abdulrahman, Herna L. Viktor:
Personalised Recommendation Systems and the Impact of COVID-19: Perspectives, Opportunities and Challenges. KDIR 2020: 295-301 - [c69]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
- 2019
- [c68]Erik G. Selin, Herna L. Viktor:
Improved Programming-Language Independent MapReduce on Shared-Memory Systems. DaWaK 2019: 206-220 - [c67]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]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]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]Evan Crothers, Nathalie Japkowicz, Herna L. Viktor:
Towards Ethical Content-Based Detection Of Online Influence Campaigns. MLSP 2019: 1-6 - [c63]Sean L. A. Floyd, Herna L. Viktor:
Soft Voting Windowing Ensembles for Learning from Partially Labelled Streams. NFMCP@PKDD/ECML 2019: 85-99 - [i4]Richard Hugh Moulton, Herna L. Viktor, Nathalie Japkowicz, João Gama:
Contextual One-Class Classification in Data Streams. CoRR abs/1907.04233 (2019) - [i3]Evan Crothers, Nathalie Japkowicz, Herna L. Viktor:
Towards Ethical Content-Based Detection of Online Influence Campaigns. CoRR abs/1908.11030 (2019) - 2018
- [j15]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]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]Erik G. Selin, Herna L. Viktor:
XRT: Programming-Language Independent MapReduce on Shared-Memory Systems. BigData Congress 2018: 182-189 - [c61]Rabaa Alabdulrahman, Herna L. Viktor, Eric Paquet:
HCC-Learn Framework for Hybrid Learning in Recommender Systems. IC3K 2018: 25-49 - [c60]Rabaa Alabdulrahman, Herna L. Viktor, Eric Paquet:
Beyond k-NN: Combining Cluster Analysis and Classification for Recommender Systems. KDIR 2018: 80-89 - [c59]Ali Pesaranghader, Herna L. Viktor, Eric Paquet:
McDiarmid Drift Detection Methods for Evolving Data Streams. IJCNN 2018: 1-9 - [c58]Olubukola M. Olaitan, Herna L. Viktor:
SCUT-DS: Learning from Multi-class Imbalanced Canadian Weather Data. ISMIS 2018: 291-301 - [c57]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]Sarah D'Ettorre, Herna L. Viktor, Eric Paquet:
Context-Based Abrupt Change Detection and Adaptation for Categorical Data Streams. DS 2017: 3-17 - [c55]Sahil Saroop, Herna L. Viktor, Patrick McCurdy, Eric Paquet:
Exploring Mediatoil Imagery: A Content-based Approach. KDIR 2017: 246-254 - [c54]Andrei Belcin, Sean Floyd, Areej Asiri, Herna L. Viktor:
An Exploratory Study of Oral and Dental Health in Canada. ICMLA 2017: 1114-1119 - [i2]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]Ali Pesaranghader, Herna L. Viktor, Eric Paquet:
McDiarmid Drift Detection Methods for Evolving Data Streams. CoRR abs/1710.02030 (2017) - 2016
- [j13]Daniel K. Antwi, Herna L. Viktor:
Dynamic Materialization for Building Personalized Smart Cubes. Trans. Large Scale Data Knowl. Centered Syst. 26: 61-88 (2016) - [c53]Ali Pesaranghader, Herna L. Viktor, Eric Paquet:
A Framework for Classification in Data Streams Using Multi-strategy Learning. DS 2016: 341-355 - [c52]Rabaa Alabdulrahman, Herna L. Viktor, Eric Paquet:
An Active Learning Approach for Ensemble-based Data Stream Mining. KDIR 2016: 275-282 - [c51]Ali Pesaranghader, Herna L. Viktor:
Fast Hoeffding Drift Detection Method for Evolving Data Streams. ECML/PKDD (2) 2016: 96-111 - 2015
- [c50]Joanna Ng, Frank Dehne, Stan Matwin, Herna L. Viktor, Olga Baysal:
Data science workshop: experience driven analytics. CASCON 2015: 344-346 - [c49]Astha Agrawal, Herna L. Viktor, Eric Paquet:
SCUT: Multi-Class Imbalanced Data Classification using SMOTE and Cluster-based Undersampling. KDIR 2015: 226-234 - [c48]Colin Bellinger, Ali Amid, Nathalie Japkowicz, Herna L. Viktor:
Multi-label Classification of Anemia Patients. ICMLA 2015: 825-830 - [c47]Muhammed K. Olorunnimbe, Herna L. Viktor:
Tweets as a Vote: Exploring Political Sentiments on Twitter for Opinion Mining. ISMIS 2015: 180-185 - [c46]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
- [c45]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 - [c44]Daniel K. Antwi, Herna L. Viktor:
Building Smart Cubes for Reliable and Faster Access to Data. DaWaK 2014: 254-265 - [c43]Hamid Hadavi, Herna L. Viktor, Eric Paquet:
A Quantum Particle Swarm Optimization and Genetic Algorithm approach to the correspondence problem. INISTA 2014: 226-233 - [c42]Parinaz Sobhani, Herna L. Viktor, Stan Matwin:
Learning from Imbalanced Data Using Ensemble Methods and Cluster-Based Undersampling. NFMCP 2014: 69-83 - 2013
- [j12]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) - [c41]Dela De Youngster, Eric Paquet, Herna L. Viktor, Emil M. Petriu:
An isometry-invariant spectral approach for protein-protein docking. BIBE 2013: 1-6 - [c40]Eric Paquet, Herna Lydia Viktor:
Isometrically Invariant Description of Deformable Objects Based on the Fractional Heat Equation. CAIP (2) 2013: 135-143 - [c39]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 - [c38]Herna L. Viktor, Eric Paquet, Jing Zhao:
Artificial neural networks for predicting 3D protein shapes from amino acid sequences. IJCNN 2013: 1-8 - [c37]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
- [j11]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) - [c36]Daniel K. Antwi, Herna L. Viktor, Nathalie Japkowicz:
The PerfSim Algorithm for Concept Drift Detection in Imbalanced Data. ICDM Workshops 2012: 619-628 - [c35]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 - [c34]Eric Paquet, Herna Lydia Viktor, Hongyu Guo:
Learning in the Presence of Large Fluctuations: A Study of Aggregation and Correlation. NFMCP 2012: 49-63 - [c33]Yasser Jafer, Herna L. Viktor, Eric Paquet:
Aggregation and privacy in multi-relational databases. PST 2012: 67-74 - 2011
- [j10]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) - [c32]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]Hongyu Guo, Herna L. Viktor, Eric Paquet:
Privacy leakage in multi-relational learning via unwanted classification models. CASCON 2011: 45-59 - [c30]Nadia Farhanaz Azam, Herna L. Viktor:
A Comparative Evaluation of Proximity Measures for Spectral Clustering. KDIR 2011: 30-41 - [c29]Nadia Farhanaz Azam, Herna L. Viktor:
Spectral Clustering: An Explorative Study of Proximity Measures. IC3K 2011: 60-78 - [c28]Eric Paquet, Herna L. Viktor, Hongyu Guo:
To Aggregate or Not to Aggregate: That is the Question. KDIR 2011: 354-357 - [c27]Eric Paquet, Herna L. Viktor:
Multimodal Representations, Indexing, Unexpectedness and Proteins. IEA/AIE (1) 2011: 85-94 - 2010
- [c26]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 - [c25]Herna L. Viktor, Bo Wang, Eric Paquet, Julie Doyle:
Preserving object-relational databases for the next generations. ICDIM 2010: 11-18 - [c24]Hongyu Guo, Herna L. Viktor, Eric Paquet:
Identifying and Preventing Data Leakage in Multi-relational Classification. ICDM Workshops 2010: 458-465
2000 – 2009
- 2009
- [j9]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) - [c23]Isis Peña, Herna L. Viktor, Eric Paquet:
Finding Clothing That Fit through Cluster Analysis and Objective Interestingness Measures. DaWaK 2009: 216-228 - [c22]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 - [c21]Isis Peña, Herna Lydia Viktor, Eric Paquet:
Explorative Data Mining for the Sizing of Population Groups. KDIR 2009: 152-159 - [r1]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]Hongyu Guo, Herna L. Viktor:
Learning from Skewed Class Multi-relational Databases. Fundam. Informaticae 89(1): 69-94 (2008) - [j7]Hongyu Guo, Herna L. Viktor:
Multirelational classification: a multiple view approach. Knowl. Inf. Syst. 17(3): 287-312 (2008) - [j6]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) - [c20]Julie Doyle, Herna L. Viktor, Eric Paquet:
Preservation metadata - a framework for 3D data based on the Semantic Web. ICDIM 2008: 925-927 - 2007
- [j5]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]Julie Doyle, Herna L. Viktor, Eric Paquet:
Long term digital preservation - An end user's perspective. ICDIM 2007: 146-151 - [c18]Hongyu Guo, Herna L. Viktor, Eric Paquet:
Pruning Relations for Substructure Discovery of Multi-relational Databases. PKDD 2007: 462-470 - 2006
- [c17]Hongyu Guo, Herna L. Viktor:
Multi-view ANNs for Multi-relational Classification. IJCNN 2006: 5259-5266 - [c16]Hongyu Guo, Herna L. Viktor:
Mining relational data through correlation-based multiple view validation. KDD 2006: 567-573 - [c15]Herna L. Viktor, Eric Paquet, Hongyu Guo:
Measuring to Fit: Virtual Tailoring Through Cluster Analysis and Classification. PKDD 2006: 395-406 - 2005
- [j4]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]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]Hongyu Guo, Herna L. Viktor:
Boosting with Data Generation: Improving the Classification of Hard to Learn Examples. IEA/AIE 2004: 1082-1091 - [c13]Herna L. Viktor, Hongyu Guo:
Multiple Classifier Prediction Improvements against Imbalanced Datasets through Added Synthetic Examples. SSPR/SPR 2004: 974-982 - 2003
- [c12]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
- [c11]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]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]Herna L. Viktor, Heidi Arndt, Mauritz Oberholzer:
Enhancing Government Decision Making Through Knowledge Discovery from Data. ECIS 2000: 266-273 - [c9]Herna L. Viktor:
Cooperating to Learn: Knowledge Discovery through Intelligent Learning Agents. ICMAS 2000: 453-454 - [c8]Herna L. Viktor:
Generating New Patterns for Information Gain and Improved Neural Network Learning. IJCNN (4) 2000: 529-534 - [c7]Heidi Arndt, Herna L. Viktor:
Dynamic knowledge-base construction through knowledge discovery. IRMA Conference 2000: 934-935
1990 – 1999
- 1999
- [c6]J. F. Francois Weilbach, Herna L. Viktor:
The Development of a Data Warehouse for Policy Making: A Case Study. HICSS 1999 - [c5]Herna L. Viktor, Ian Cloete:
Improved generalisation using cooperative learning and rule extraction. IJCNN 1999: 1345-1349 - [c4]Andries P. Engelbrecht, Herna L. Viktor:
Rule Improvement Through Decision Boundary Detection Using Sensitivity Analysis. IWANN (2) 1999: 78-84 - 1998
- [j1]Herna L. Viktor, Ian Cloete:
Inductive Learning with a Computational Network. J. Intell. Robotic Syst. 21(2): 131-141 (1998) - 1997
- [c3]Herna L. Viktor, Ian Cloete:
Learning by Co-operation: Combining Multiple Computationally Intelligent Programs into a Computational Network. ICANNGA 1997: 543-546 - 1995
- [c2]Herna L. Viktor, Andries P. Engelbrecht, Ian Cloete:
Reduction of symbolic rules from artificial neural networks using sensitivity analysis. ICNN 1995: 1788-1793 - [c1]Herna L. Viktor, Ian Cloete:
Extracting DNF Rules from Artificial Neural Networks. IWANN 1995: 611-618
Coauthor Index
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