42 citations · 95 across the 22 of their papers we have counts for
8 papers · 1 filter
Enhancing Imbalance Learning: A Novel Slack-Factor Fuzzy SVM Approach
M. Tanveer, Anushka Tiwari, Mushir Akhtar +1
In real-world applications, class-imbalanced datasets pose significant challenges for machine learning algorithms, such as support vector machines (SVMs), particularly in effective…
Flexi-Fuzz least squares SVM for Alzheimer's diagnosis: Tackling noise, outliers, and class imbalance
Mushir Akhtar, A. Quadir, M. Tanveer +1
Alzheimer's disease (AD) is a leading neurodegenerative condition and the primary cause of dementia, characterized by progressive cognitive decline and memory loss. Its progression…
Advancing RVFL networks: Robust classification with the HawkEye loss function
Mushir Akhtar, Ritik Mishra, M. Tanveer +1
Random vector functional link (RVFL), a variant of single-layer feedforward neural network (SLFN), has garnered significant attention due to its lower computational cost and robust…
Enhanced Feature Based Granular Ball Twin Support Vector Machine
A. Quadir, M. Sajid, M. Tanveer +1
In this paper, we propose enhanced feature based granular ball twin support vector machine (EF-GBTSVM). EF-GBTSVM employs the coarse granularity of granular balls (GBs) as input ra…
GL-TSVM: A robust and smooth twin support vector machine with guardian loss function
Mushir Akhtar, M. Tanveer, Mohd. Arshad
Twin support vector machine (TSVM), a variant of support vector machine (SVM), has garnered significant attention due to its times lower computational complexity compared to…
Enhancing Multiview Synergy: Robust Learning by Exploiting the Wave Loss Function with Consensus and Complementarity Principles
A. Quadir, Mushir Akhtar, M. Tanveer
Multiview learning (MvL) is an advancing domain in machine learning, leveraging multiple data perspectives to enhance model performance through view-consistency and view-discrepanc…
Advancing Supervised Learning with the Wave Loss Function: A Robust and Smooth Approach
Mushir Akhtar, M. Tanveer, Mohd. Arshad
Loss function plays a vital role in supervised learning frameworks. The selection of the appropriate loss function holds the potential to have a substantial impact on the proficien…
HawkEye: Advancing Robust Regression with Bounded, Smooth, and Insensitive Loss Function
Mushir Akhtar, M. Tanveer, Mohd. Arshad
Support vector regression (SVR) has garnered significant popularity over the past two decades owing to its wide range of applications across various fields. Despite its versatility…