51 citations · 78 across the 16 of their papers we have counts for
26 papers
ADROIT: A Self-Supervised Framework for Learning Robust Representations for Active Learning
Soumya Banerjee, Vinay Kumar Verma
Active learning aims to select optimal samples for labeling, minimizing annotation costs. This paper introduces a unified representation learning framework tailored for active lear…
Meta-Learned Attribute Self-Interaction Network for Continual and Generalized Zero-Shot Learning
Vinay K Verma, Nikhil Mehta, Kevin J Liang +2
Zero-shot learning (ZSL) is a promising approach to generalizing a model to categories unseen during training by leveraging class attributes, but challenges remain. Recently, metho…
VERSE: Virtual-Gradient Aware Streaming Lifelong Learning with Anytime Inference
Soumya Banerjee, Vinay K. Verma, Avideep Mukherjee +3
Lifelong learning or continual learning is the problem of training an AI agent continuously while also preventing it from forgetting its previously acquired knowledge. Streaming li…
Exemplar-Free Continual Transformer with Convolutions
Anurag Roy, Vinay Kumar Verma, Sravan Voonna +3
Continual Learning (CL) involves training a machine learning model in a sequential manner to learn new information while retaining previously learned tasks without the presence of…
Streaming LifeLong Learning With Any-Time Inference
Soumya Banerjee, Vinay Kumar Verma, Vinay P. Namboodiri
Despite rapid advancements in lifelong learning (LLL) research, a large body of research mainly focuses on improving the performance in the existing \textit{static} continual learn…
Pushing the Efficiency Limit Using Structured Sparse Convolutions
Vinay Kumar Verma, Nikhil Mehta, Shijing Si +2
Weight pruning is among the most popular approaches for compressing deep convolutional neural networks. Recent work suggests that in a randomly initialized deep neural network, the…