25 citations · 64 across the 20 of their papers we have counts for
4 papers · 1 filter
Towards Realistic Mechanisms That Incentivize Federated Participation and Contribution
Marco Bornstein, Amrit Singh Bedi, Anit Kumar Sahu +2
Edge device participation in federating learning (FL) is typically studied through the lens of device-server communication (e.g., device dropout) and assumes an undying desire from…
Federated Representation Learning for Automatic Speech Recognition
Guruprasad V Ramesh, Gopinath Chennupati, Milind Rao +3
Federated Learning (FL) is a privacy-preserving paradigm, allowing edge devices to learn collaboratively without sharing data. Edge devices like Alexa and Siri are prospective sour…
Performance Scaling via Optimal Transport: Enabling Data Selection from Partially Revealed Sources
Feiyang Kang, Hoang Anh Just, Anit Kumar Sahu +1
Traditionally, data selection has been studied in settings where all samples from prospective sources are fully revealed to a machine learning developer. However, in practical data…
Learning When to Trust Which Teacher for Weakly Supervised ASR
Aakriti Agrawal, Milind Rao, Anit Kumar Sahu +2
Automatic speech recognition (ASR) training can utilize multiple experts as teacher models, each trained on a specific domain or accent. Teacher models may be opaque in nature sinc…