Machine Learning & Statistical Inference Lab
The "MLSI-LAB" serves as a dedicated research facility specializing in Machine Learning, led by Dr. Reshma Rastogi at South Asian University.
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Showing 10 of 16 repositories
- SADGSC Public
- AMGCF Public
- Variants-of-Unsupervised-Feature-Selection Public Forked from Era-Aich/Project_MSC
Implementation of "Entropy Dependency-based Unsupervised Feature Selection" and " Entropy Based Embedded Unsupervised Feature Selection" Papers
- AGMLGS Public
- UniTSVM Public
- Time-efficient-variants-of-Twin-Extreme-Learning-Machine Public
In this paper, we propose two novel time-efficient formulations of the Twin Extreme Learning Machine, which only require the solution of systems of linear equations for obtaining the final classifier. In this sense, they can combine the benefits of the Twin Support Vector Machine and standard Extreme Learning Machine in the true sense.
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