2 citations · 2 across the 4 of their papers we have counts for
4 papers
No Unique Minimizer, No Problem: On the Consistency of Robust Neural Classifiers
Subhabrata Majumdar, Anand Deo, Partha Pratim Saha +1
Neural network classifiers trained by cross-entropy minimization are highly sensitive to label noise and adversarial contamination. While robust alternatives offer bounded influenc…
rSDNet: Unified Robust Neural Learning against Label Noise and Adversarial Attacks
Suryasis Jana, Abhik Ghosh
Neural networks are central to modern artificial intelligence, yet their training remains highly sensitive to data contamination. Standard neural classifiers are trained by minimiz…
Exploring Citation Diversity in Scholarly Literature: An Entropy-Based Approach
Suchismita Banerjee, Abhik Ghosh, Banasri Basu
This study explores the citation diversity in scholarly literature, analyzing different patterns of citations observed within different countries and academic disciplines. We exami…
Robust and Efficient Parameter Estimation for Discretely Observed Stochastic Processes
Rohan Hore, Abhik Ghosh
In various practical situations, we encounter data from stochastic processes which can be efficiently modelled by an appropriate parametric model for subsequent statistical analyse…