3 papers
cs.LG2026
Matching High-Dimensional Geometric Quantiles for Test-Time Adaptation of Transformers and Convolutional Networks Alike
Sravan Danda, Aditya Challa, Shlok Mehendale +1
Test-time adaptation (TTA) refers to adapting a classifier for the test data when the probability distribution of the test data slightly differs from that of the training data of t…
cs.LG2024
A Granger-Causal Perspective on Gradient Descent with Application to Pruning
Aditya Shah, Aditya Challa, Sravan Danda +2
Stochastic Gradient Descent (SGD) is the main approach to optimizing neural networks. Several generalization properties of deep networks, such as convergence to a flatter minima, a…
cs.LG2024
A Novel Approach to Regularising 1NN classifier for Improved Generalization
Aditya Challa, Sravan Danda, Laurent Najman
In this paper, we propose a class of non-parametric classifiers, that learn arbitrary boundaries and generalize well. Our approach is based on a novel way to regularize 1NN classif…