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Shabnam Nazmi
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2020 – today
- 2022
- [j5]Xuyang Yan
, Shabnam Nazmi, Biniam Gebru, Mohd Anwar, Abdollah Homaifar
, Mrinmoy Sarkar, Kishor Datta Gupta
:
A clustering-based active learning method to query informative and representative samples. Appl. Intell. 52(11): 13250-13267 (2022) - [i4]Xuyang Yan, Shabnam Nazmi, Biniam Gebru, Mohd Anwar, Abdollah Homaifar, Mrinmoy Sarkar, Kishor Datta Gupta:
Mitigating shortage of labeled data using clustering-based active learning with diversity exploration. CoRR abs/2207.02964 (2022) - 2021
- [j4]Shabnam Nazmi, Xuyang Yan
, Abdollah Homaifar
, Mohd Anwar
:
Multi-label classification with local pairwise and high-order label correlations using graph partitioning. Knowl. Based Syst. 233: 107414 (2021) - [c8]Shabnam Nazmi, Abdollah Homaifar, Mohd Anwar:
An effective action covering for multi-label learning classifier systems: a graph-theoretic approach. GECCO 2021: 340-348 - [c7]Xuyang Yan
, Mrinmoy Sarkar, Biniam Gebru, Shabnam Nazmi, Abdollah Homaifar:
A Supervised Feature Selection Method For Mixed-Type Data using Density-based Feature Clustering. SMC 2021: 1900-1905 - [i3]Xuyang Yan, Mrinmoy Sarkar, Biniam Gebru, Shabnam Nazmi, Abdollah Homaifar:
A Supervised Feature Selection Method For Mixed-Type Data using Density-based Feature Clustering. CoRR abs/2111.08169 (2021) - [i2]Abdollah Homaifar, Ali Karimoddini, Mike Heiges, Mubbashar Altaf Khan, Berat A. Erol, Shabnam Nazmi:
A Software Tool for Evaluating Unmanned Autonomous Systems. CoRR abs/2111.10871 (2021) - 2020
- [j3]Shabnam Nazmi, Xuyang Yan
, Abdollah Homaifar, Emily A. Doucette:
Evolving multi-label classification rules by exploiting high-order label correlations. Neurocomputing 417: 176-186 (2020) - [j2]Xuyang Yan
, Shabnam Nazmi, Berat A. Erol, Abdollah Homaifar
, Biniam Gebru, Edward W. Tunstel:
An efficient unsupervised feature selection procedure through feature clustering. Pattern Recognit. Lett. 131: 277-284 (2020) - [i1]Shabnam Nazmi, Xuyang Yan, Abdollah Homaifar, Emily A. Doucette:
Evolving Multi-label Classification Rules by Exploiting High-order Label Correlation. CoRR abs/2007.11609 (2020)
2010 – 2019
- 2018
- [j1]Mohammad Razeghi-Jahromi, Shabnam Nazmi, Abdollah Homaifar:
Two-Step Markov Update Algorithm for Accuracy-Based Learning Classifier Systems. Complex Syst. 27(1) (2018) - [c6]Shabnam Nazmi, Abdollah Homaifar:
Possibility Rule-Based Classification Using Function Approximation. SMC 2018: 668-674 - [c5]Shabnam Nazmi, Xuyang Yan
, Abdollah Homaifar:
Multi-label Classification Using Genetic-Based Machine Learning. SMC 2018: 675-680 - [c4]Gabriel Awogbami, Norbert A. Agana, Shabnam Nazmi, Xuyang Yan, Abdollah Homaifar:
An Evidence Theory Based Multi Sensor Data Fusion for Multiclass Classification. SMC 2018: 1755-1760 - 2017
- [c3]Shabnam Nazmi, Mohammad Razeghi-Jahromi, Abdollah Homaifar:
Multilabel Classification with Weighted Labels Using Learning Classifier Systems. ICMLA 2017: 275-280 - [c2]Xuyang Yan
, Abdollah Homaifar, Shabnam Nazmi, Mohammad Razeghi-Jahromi:
A novel clustering algorithm based on fitness proportionate sharing. SMC 2017: 1960-1965 - 2015
- [c1]Shabnam Nazmi, Reza Mohajerpoor
, Hamid Abdi, Saeid Nahavandi:
Functional observer design with application to pre-compensated multi-variable systems. CCA 2015: 620-625
Coauthor Index
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