1 citations · 2 across the 2 of their papers we have counts for
3 papers · 1 filter
Regularizing Self-training for Unsupervised Domain Adaptation via Structural Constraints
Rajshekhar Das, Jonathan Francis, Sanket Vaibhav Mehta +3
Self-training based on pseudo-labels has emerged as a dominant approach for addressing conditional distribution shifts in unsupervised domain adaptation (UDA) for semantic segmenta…
Learning Expressive Prompting With Residuals for Vision Transformers
Rajshekhar Das, Yonatan Dukler, Avinash Ravichandran +1
Prompt learning is an efficient approach to adapt transformers by inserting learnable set of parameters into the input and intermediate representations of a pre-trained model. In t…
On the Importance of Distractors for Few-Shot Classification
Rajshekhar Das, Yu-Xiong Wang, JoséM. F. Moura
Few-shot classification aims at classifying categories of a novel task by learning from just a few (typically, 1 to 5) labelled examples. An effective approach to few-shot classifi…