1 citations · 1 across the 6 of their papers we have counts for
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Minimizing Layerwise Activation Norm Improves Generalization in Federated Learning
M Yashwanth, Gaurav Kumar Nayak, Harsh Rangwani +3
Federated Learning (FL) is an emerging machine learning framework that enables multiple clients (coordinated by a server) to collaboratively train a global model by aggregating the…
Learning from Limited and Imperfect Data
Harsh Rangwani
The distribution of data in the world (eg, internet, etc.) significantly differs from the well-curated datasets and is often over-populated with samples from common categories. The…
SVAADA: Submodular Subset Selection for Virtual Adversarial Active Domain Adaptation
Harsh Rangwani, Arihant Jain, Sumukh K Aithal +1
Unsupervised domain adaptation (DA) methods have focused on achieving maximal performance through aligning features from source and target domains without using labeled data in the…
Class Balancing GAN with a Classifier in the Loop
Harsh Rangwani, Konda Reddy Mopuri, R. Venkatesh Babu
Generative Adversarial Networks (GANs) have swiftly evolved to imitate increasingly complex image distributions. However, majority of the developments focus on performance of GANs…