42 citations · 84 across the 10 of their papers we have counts for
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Bounded Adjustment with Reliability-Guided Embedding for Imbalanced Learning with Noisy Labels
Mushir Akhtar, Akarsh J., M. Tanveer +1
Class-balanced learning and label noise create a coupled failure mode: frequency correction prevents majority classes from dominating the decision rule, but can amplify incorrectly…
Robust Broad Learning System with Wave Loss for Classification under Data Uncertainty
Mushir Akhtar, A. Varshney, A. Quadir +3
Broad Learning System (BLS) offers an efficient alternative to deep architectures by enabling fast learning through randomized feature mapping and closed-form solutions. However, i…
Residual-Guided Randomized Neural Networks
Mushir Akhtar, M. Tanveer, Mohd. Arshad
Randomized neural networks enable fast and analytically tractable training by fixing the input to hidden layer parameters at random and learning the output weights in closed form;…
CAWI: Copula-Aligned Weight Initialization for Randomized Neural Networks
Mushir Akhtar, M. Tanveer, Mohd. Arshad
Randomized neural networks (RdNNs) enable efficient, backpropagation-free training by freezing randomly initialized input-to-hidden weights, which permits a closed-form solution fo…
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…
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…
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…
RoBoSS: A Robust, Bounded, Sparse, and Smooth Loss Function for Supervised Learning
Mushir Akhtar, M. Tanveer, Mohd. Arshad
In the domain of machine learning, the significance of the loss function is paramount, especially in supervised learning tasks. It serves as a fundamental pillar that profoundly in…