Rajiv Mathews

According to our database, Rajiv Mathews authored at least 31 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Parameter-Efficient Transfer Learning under Federated Learning for Automatic Speech Recognition.

Xuan Kan, Yonghui Xiao, Tien-Ju Yang, Nanxin Chen, Rajiv Mathews

CoRR, 2024

Learning from straggler clients in federated learning.

Andrew Hard, Antonious M. Girgis, Ehsan Amid, Sean Augenstein, Lara McConnaughey, Rajiv Mathews, Rohan Anil

CoRR, 2024

Unintended Memorization in Large ASR Models, and How to Mitigate It.

Lun Wang, Om Thakkar, Rajiv Mathews

Proceedings of the IEEE International Conference on Acoustics, 2024

FedAQT: Accurate Quantized Training with Federated Learning.

Renkun Ni, Yonghui Xiao, Phoenix Meadowlark, Oleg Rybakov, Tom Goldstein, Ananda Theertha Suresh, Ignacio López-Moreno, Mingqing Chen, Rajiv Mathews

Proceedings of the IEEE International Conference on Acoustics, 2024

2023

Heterogeneous Federated Learning Using Knowledge Codistillation.

Jared Lichtarge, Ehsan Amid, Shankar Kumar, Tien-Ju Yang, Rohan Anil, Rajiv Mathews

CoRR, 2023

Online Model Compression for Federated Learning with Large Models.

Tien-Ju Yang, Yonghui Xiao, Giovanni Motta, Françoise Beaufays, Rajiv Mathews, Mingqing Chen

Proceedings of the IEEE International Conference on Acoustics, 2023

The Gift of Feedback: Improving ASR Model Quality by Learning from User Corrections Through Federated Learning.

Lillian Zhou, Yuxin Ding, Mingqing Chen, Harry Zhang, Rohit Prabhavalkar, Dhruv Guliani, Giovanni Motta, Rajiv Mathews

Proceedings of the IEEE Automatic Speech Recognition and Understanding Workshop, 2023

2022

Recycling Scraps: Improving Private Learning by Leveraging Intermediate Checkpoints.

Virat Shejwalkar, Arun Ganesh, Rajiv Mathews, Om Thakkar, Abhradeep Thakurta

CoRR, 2022

Large vocabulary speech recognition for languages of Africa: multilingual modeling and self-supervised learning.

Sandy Ritchie, You-Chi Cheng, Mingqing Chen, Rajiv Mathews, Daan van Esch, Bo Li, Khe Chai Sim

CoRR, 2022

Mixed Federated Learning: Joint Decentralized and Centralized Learning.

Sean Augenstein, Andrew Hard, Lin Ning, Karan Singhal, Satyen Kale, Kurt Partridge, Rajiv Mathews

CoRR, 2022

Scaling Language Model Size in Cross-Device Federated Learning.

Jae Hun Ro, Theresa Breiner, Lara McConnaughey, Mingqing Chen, Ananda Theertha Suresh, Shankar Kumar, Rajiv Mathews

CoRR, 2022

Detecting Unintended Memorization in Language-Model-Fused ASR.

W. Ronny Huang, Steve Chien, Om Dipakbhai Thakkar, Rajiv Mathews

Proceedings of the 23rd Annual Conference of the International Speech Communication Association, 2022

Production federated keyword spotting via distillation, filtering, and joint federated-centralized training.

Andrew Hard, Kurt Partridge, Neng Chen, Sean Augenstein, Aishanee Shah, Hyun Jin Park, Alex Park, Sara Ng, Jessica Nguyen, Ignacio López-Moreno, Rajiv Mathews, Françoise Beaufays

Proceedings of the 23rd Annual Conference of the International Speech Communication Association, 2022

UserLibri: A Dataset for ASR Personalization Using Only Text.

Theresa Breiner, Swaroop Ramaswamy, Ehsan Variani, Shefali Garg, Rajiv Mathews, Khe Chai Sim, Kilol Gupta, Mingqing Chen, Lara McConnaughey

Proceedings of the 23rd Annual Conference of the International Speech Communication Association, 2022

Extracting Targeted Training Data from ASR Models, and How to Mitigate It.

Ehsan Amid, Om Dipakbhai Thakkar, Arun Narayanan, Rajiv Mathews, Françoise Beaufays

Proceedings of the 23rd Annual Conference of the International Speech Communication Association, 2022

Public Data-Assisted Mirror Descent for Private Model Training.

Ehsan Amid, Arun Ganesh, Rajiv Mathews, Swaroop Ramaswamy, Shuang Song, Thomas Steinke, Vinith M. Suriyakumar, Om Thakkar, Abhradeep Thakurta

Proceedings of the International Conference on Machine Learning, 2022

Capitalization Normalization for Language Modeling with an Accurate and Efficient Hierarchical RNN Model.

Hao Zhang, You-Chi Cheng, Shankar Kumar, W. Ronny Huang, Mingqing Chen, Rajiv Mathews

Proceedings of the IEEE International Conference on Acoustics, 2022

A Method to Reveal Speaker Identity in Distributed ASR Training, and How to Counter IT.

Trung Dang, Om Thakkar, Swaroop Ramaswamy, Rajiv Mathews, Peter Chin, Françoise Beaufays

Proceedings of the IEEE International Conference on Acoustics, 2022

2021

Jointly Learning from Decentralized (Federated) and Centralized Data to Mitigate Distribution Shift.

Sean Augenstein, Andrew Hard, Kurt Partridge, Rajiv Mathews

CoRR, 2021

Position-Invariant Truecasing with a Word-and-Character Hierarchical Recurrent Neural Network.

Hao Zhang, You-Chi Cheng, Shankar Kumar, Mingqing Chen, Rajiv Mathews

CoRR, 2021

Revealing and Protecting Labels in Distributed Training.

Trung Dang, Om Thakkar, Swaroop Ramaswamy, Rajiv Mathews, Peter Chin, Françoise Beaufays

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Communication-Efficient Agnostic Federated Averaging.

Jae Ro, Mingqing Chen, Rajiv Mathews, Mehryar Mohri, Ananda Theertha Suresh

Proceedings of the 22nd Annual Conference of the International Speech Communication Association, Interspeech 2021, Brno, Czechia, August 30, 2021

2020

Training Production Language Models without Memorizing User Data.

Swaroop Ramaswamy, Om Thakkar, Rajiv Mathews, Galen Andrew, H. Brendan McMahan, Françoise Beaufays

CoRR, 2020

Understanding Unintended Memorization in Federated Learning.

Om Thakkar, Swaroop Ramaswamy, Rajiv Mathews, Françoise Beaufays

CoRR, 2020

Training Keyword Spotting Models on Non-IID Data with Federated Learning.

Andrew Hard, Kurt Partridge, Cameron Nguyen, Niranjan Subrahmanya, Aishanee Shah, Pai Zhu, Ignacio López-Moreno, Rajiv Mathews

Proceedings of the 21st Annual Conference of the International Speech Communication Association, 2020

Generative Models for Effective ML on Private, Decentralized Datasets.

Sean Augenstein, H. Brendan McMahan, Daniel Ramage, Swaroop Ramaswamy, Peter Kairouz, Mingqing Chen, Rajiv Mathews, Blaise Agüera y Arcas

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Federated Evaluation of On-device Personalization.

Kangkang Wang, Rajiv Mathews, Chloé Kiddon, Hubert Eichner, Françoise Beaufays, Daniel Ramage

CoRR, 2019

Federated Learning for Emoji Prediction in a Mobile Keyboard.

Swaroop Ramaswamy, Rajiv Mathews, Kanishka Rao, Françoise Beaufays

CoRR, 2019

Federated Learning Of Out-Of-Vocabulary Words.

Mingqing Chen, Rajiv Mathews, Tom Ouyang, Françoise Beaufays

CoRR, 2019

Federated Learning of N-Gram Language Models.

Mingqing Chen, Ananda Theertha Suresh, Rajiv Mathews, Adeline Wong, Cyril Allauzen, Françoise Beaufays, Michael Riley

Proceedings of the 23rd Conference on Computational Natural Language Learning, 2019

2018

Federated Learning for Mobile Keyboard Prediction.

Andrew Hard, Kanishka Rao, Rajiv Mathews, Françoise Beaufays, Sean Augenstein, Hubert Eichner, Chloé Kiddon, Daniel Ramage

CoRR, 2018