Federated Learning for Mobile Keyboard Prediction. - Andrew Hard; Kanishka Rao; Rajiv Mathews; Françoise Beaufays; Sean Augenstein; Hubert Eichner; Chloé Kiddon; Daniel Ramage (CoRR, 2018)

Federated Learning of N-Gram Language Models. - Mingqing Chen; Ananda Theertha Suresh; Rajiv Mathews; Adeline Wong; Cyril Allauzen; Françoise Beaufays; Michael Riley 001 (CoNLL, 2019)

Federated Learning Of Out-Of-Vocabulary Words. - Mingqing Chen; Rajiv Mathews; Tom Ouyang; Françoise Beaufays (CoRR, 2019)

Federated Learning for Emoji Prediction in a Mobile Keyboard. - Swaroop Ramaswamy; Rajiv Mathews; Kanishka Rao; Françoise Beaufays (CoRR, 2019)

Federated Evaluation of On-device Personalization. - Kangkang Wang; Rajiv Mathews; Chloé Kiddon; Hubert Eichner; Françoise Beaufays; Daniel Ramage (CoRR, 2019)

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 (ICLR, 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 (INTERSPEECH, 2020)

Understanding Unintended Memorization in Federated Learning. - Om Thakkar 001; Swaroop Ramaswamy; Rajiv Mathews; Françoise Beaufays (CoRR, 2020)

Training Production Language Models without Memorizing User Data. - Swaroop Ramaswamy; Om Thakkar 001; Rajiv Mathews; Galen Andrew; H. Brendan McMahan; Françoise Beaufays (CoRR, 2020)

Communication-Efficient Agnostic Federated Averaging. - Jae Ro; Mingqing Chen; Rajiv Mathews; Mehryar Mohri; Ananda Theertha Suresh (Interspeech, 2021)

Revealing and Protecting Labels in Distributed Training. - Trung Dang 002; Om Thakkar 001; Swaroop Ramaswamy; Rajiv Mathews; Peter Chin 001; Françoise Beaufays (NeurIPS, 2021)

Position-Invariant Truecasing with a Word-and-Character Hierarchical Recurrent Neural Network. - Hao Zhang 010; You-Chi Cheng; Shankar Kumar; Mingqing Chen; Rajiv Mathews (CoRR, 2021)

Jointly Learning from Decentralized (Federated) and Centralized Data to Mitigate Distribution Shift. - Sean Augenstein; Andrew Hard; Kurt Partridge; Rajiv Mathews (CoRR, 2021)

A Method to Reveal Speaker Identity in Distributed ASR Training, and How to Counter IT. - Trung Dang 002; Om Thakkar 001; Swaroop Ramaswamy; Rajiv Mathews; Peter Chin 001; Françoise Beaufays (ICASSP, 2022)

Capitalization Normalization for Language Modeling with an Accurate and Efficient Hierarchical RNN Model. - Hao Zhang 010; You-Chi Cheng; Shankar Kumar; W. Ronny Huang; Mingqing Chen; Rajiv Mathews (ICASSP, 2022)

Public Data-Assisted Mirror Descent for Private Model Training. - Ehsan Amid; Arun Ganesh; Rajiv Mathews; Swaroop Ramaswamy; Shuang Song 001; Thomas Steinke 002; Vinith M. Suriyakumar; Om Thakkar 001; Abhradeep Thakurta (ICML, 2022)

Extracting Targeted Training Data from ASR Models, and How to Mitigate It. - Ehsan Amid; Om Dipakbhai Thakkar; Arun Narayanan; Rajiv Mathews; Françoise Beaufays (INTERSPEECH, 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 (INTERSPEECH, 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 001; Sara Ng; Jessica Nguyen; Ignacio López-Moreno; Rajiv Mathews; Françoise Beaufays (INTERSPEECH, 2022)

Detecting Unintended Memorization in Language-Model-Fused ASR. - W. Ronny Huang; Steve Chien; Om Dipakbhai Thakkar; Rajiv Mathews (INTERSPEECH, 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)

Mixed Federated Learning: Joint Decentralized and Centralized Learning. - Sean Augenstein; Andrew Hard; Lin Ning 001; Karan Singhal; Satyen Kale; Kurt Partridge; Rajiv Mathews (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 028; Khe Chai Sim (CoRR, 2022)

Recycling Scraps: Improving Private Learning by Leveraging Intermediate Checkpoints. - Virat Shejwalkar; Arun Ganesh; Rajiv Mathews; Om Thakkar 001; Abhradeep Thakurta (CoRR, 2022)

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 (ASRU, 2023)

Online Model Compression for Federated Learning with Large Models. - Tien-Ju Yang; Yonghui Xiao; Giovanni Motta; Françoise Beaufays; Rajiv Mathews; Mingqing Chen (ICASSP, 2023)

Heterogeneous Federated Learning Using Knowledge Codistillation. - Jared Lichtarge; Ehsan Amid; Shankar Kumar; Tien-Ju Yang; Rohan Anil; Rajiv Mathews (CoRR, 2023)

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 (ICASSP, 2024)

Unintended Memorization in Large ASR Models, and How to Mitigate It. - Lun Wang 001; Om Thakkar 001; Rajiv Mathews (ICASSP, 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)

Parameter-Efficient Transfer Learning under Federated Learning for Automatic Speech Recognition. - Xuan Kan; Yonghui Xiao; Tien-Ju Yang; Nanxin Chen; Rajiv Mathews (CoRR, 2024)

Recycling Scraps: Improving Private Learning by Leveraging Checkpoints]{Recycling Scraps: Improving Private Learning by Leveraging Checkpoints. - Virat Shejwalkar; Arun Ganesh; Rajiv Mathews; Yarong Mu; Shuang Song 001; Om Thakkar 001; Abhradeep Thakurta; Xinyi Zheng (Proc. Priv. Enhancing Technol., 2025)

Attacker's Noise Can Manipulate Your Audio-based LLM in the Real World. - Vinu Sankar Sadasivan; Soheil Feizi; Rajiv Mathews; Lun Wang (CoRR, 2025)