Harsh Rangwani

most citedS

^{3}

VAADA: Submodular Subset Selection for Virtual Adversarial Active Domain Adaptation

1 citations · 1 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2021★ 1 cited

S $^{3}$ VAADA: 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…

cs.LG2021

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…

S3VAADA: Submodular Subset Selection for Virtual Adversarial Active Domain Adaptation

Class Balancing GAN with a Classifier in the Loop

S $^{3}$ VAADA: Submodular Subset Selection for Virtual Adversarial Active Domain Adaptation