3 papers
cs.LG2026
Gradual Fine-Tuning for Flow Matching Models
Gudrun Thorkelsdottir, Arindam Banerjee
Fine-tuning flow matching models is a central challenge in settings with limited data, evolving distributions, or computational constraints. While recent work has produced signific…
math.AC2025
Defect Functions Between Filtrations of Ideals
Arindam Banerjee, Tai Huy Ha, Vivek Bhabani Lama
We introduce and study the defect function associated to a pair of filtrations of ideals, which generalizes the symbolic defect of ideals. Under the assumption that the Rees algebr…
cs.NE2024
Alternate Loss Functions for Classification and Robust Regression Can Improve the Accuracy of Artificial Neural Networks
Mathew Mithra Noel, Arindam Banerjee, Yug Oswal +2
All machine learning algorithms use a loss, cost, utility or reward function to encode the learning objective and oversee the learning process. This function that supervises learni…