Sweta Sharma

Orcid: 0000-0001-8696-1221

According to our database1, Sweta Sharma authored at least 14 papers between 2016 and 2021.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2021
Large-Scale Twin Parametric Support Vector Machine Using Pinball Loss Function.
IEEE Trans. Syst. Man Cybern. Syst., 2021

Ternary tree-based structural twin support tensor machine for clustering.
Pattern Anal. Appl., 2021

Sparse support vector machine with pinball loss.
Trans. Emerg. Telecommun. Technol., 2021

Stochastic Quasi-Newton Minimum Complexity Machine for Pattern Classification.
Proceedings of the Pattern Recognition and Machine Intelligence, 2021

2019
Fast Laplacian twin support vector machine with active learning for pattern classification.
Appl. Soft Comput., 2019

A Unified Multi-label Relationship Learning.
Proceedings of the 14th International Conference on Computer Science & Education, 2019

2018
Robust Parametric Twin Support Vector Machine for Pattern Classification.
Neural Process. Lett., 2018

Maximum Margin Minimum Variance Twin Support Vector Machine.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2018

Insensitive Zone based Pinball Loss Twin Support Vector Machine for Pattern Classification.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2018

Exploring Data Reduction Techniques for Time Efficient Support Vector Machine Classifiers.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2018

Stochastic Conjugate Gradient Descent Twin Support Vector Machine for Large Scale Pattern Classification.
Proceedings of the AI 2018: Advances in Artificial Intelligence, 2018

2017
Tree-Based Structural Twin Support Tensor Clustering with Square Loss Function.
Proceedings of the Pattern Recognition and Machine Intelligence, 2017

2016
Robust least squares twin support vector machine for human activity recognition.
Appl. Soft Comput., 2016

Robust Parametric Twin Support Vector Machine and Its Application in Human Activity Recognition.
Proceedings of International Conference on Computer Vision and Image Processing, 2016


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