activity
20232026
most citedRoBoSS: A Robust, Bounded, Sparse, and Smooth Loss Function for Supervised Learning

42 citations · 84 across the 10 of their papers we have counts for

collaborators

11 papers

cs.CV2026

Beyond Benchmark Scores: Auditing Medical Vision-Language Models for Chest X-Ray Tuberculosis Screening

Mushir Akhtar, M. Tanveer, Mohd. Arshad

A medical model's benchmark score does not establish that the same conclusion holds under a different evaluation. This study tests whether claims about model ranking, score reliabi…

cs.LG2026

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…

cs.LG2026

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…

cs.LG2026

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;…

cs.LG2026

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…

cs.LG2024

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…

cs.LG2024★ 1 cited

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…

cs.LG2024★ 1 cited

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…

cs.LG2024★ 38 cited

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…

cs.LG2024★ 2 cited

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…

cs.LG2023★ 42 cited

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…