27 citations · 46 across the 17 of their papers we have counts for
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cs.LG2025
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…
cs.CV2025
DynamicEval: Rethinking Evaluation for Dynamic Text-to-Video Synthesis
Nithin C. Babu, Aniruddha Mahapatra, Harsh Rangwani +2
Existing text-to-video (T2V) evaluation benchmarks, such as VBench and EvalCrafter, suffer from two limitations. (i) While the emphasis is on subject-centric prompts or static came…
cs.LG2025
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…