4 papers · 1 filter
Leveraging Data Symmetries to Select an Optimal Subset of Training Data under Label Noise
Kumar Shubham, Pavan Karjol, Kiran M K +1
The performance of machine learning models often relies on large labeled datasets; however, data collected from diverse sources can contain label noise. Recent work has shown that,…
Spectral Discovery of Continuous Symmetries via Generalized Fourier Transforms
Pavan Karjol, Kumar Shubham, Prathosh AP
Continuous symmetries are fundamental to many scientific and learning problems, yet they are often unknown a priori. Existing symmetry discovery approaches typically search directl…
AdaKD: Dynamic Knowledge Distillation of ASR models using Adaptive Loss Weighting
Shreyan Ganguly, Roshan Nayak, Rakshith Rao +2
Knowledge distillation, a widely used model compression technique, works on the basis of transferring knowledge from a cumbersome teacher model to a lightweight student model. The…
WISER: Weak supervISion and supErvised Representation learning to improve drug response prediction in cancer
Kumar Shubham, Aishwarya Jayagopal, Syed Mohammed Danish +2
Cancer, a leading cause of death globally, occurs due to genomic changes and manifests heterogeneously across patients. To advance research on personalized treatment strategies, th…