Rajiv Mathews

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 45

Top Topics

Keyword Spotting

Top Venues

Publications

Andrew Hard, Antonious M. Girgis, Ehsan Amid, Sean Augenstein, Lara McConnaughey, Rajiv Mathews, Rohan Anil
Learning from straggler clients in federated learning. CoRR (2024)
Renkun Ni, Yonghui Xiao, Phoenix Meadowlark, Oleg Rybakov, Tom Goldstein, Ananda Theertha Suresh, Ignacio López-Moreno, Mingqing Chen, Rajiv Mathews
FedAQT: Accurate Quantized Training with Federated Learning. ICASSP (2024)
Lun Wang, Om Thakkar, Rajiv Mathews
Unintended Memorization in Large ASR Models, and How to Mitigate It. ICASSP (2024)
Lillian Zhou, Yuxin Ding, Mingqing Chen, Harry Zhang, Rohit Prabhavalkar, Dhruv Guliani, Giovanni Motta, Rajiv Mathews
The Gift of Feedback: Improving ASR Model Quality by Learning from User Corrections Through Federated Learning. ASRU (2023)
Lun Wang, Om Thakkar, Rajiv Mathews
Unintended Memorization in Large ASR Models, and How to Mitigate It. CoRR (2023)
Jared Lichtarge, Ehsan Amid, Shankar Kumar, Tien-Ju Yang, Rohan Anil, Rajiv Mathews
Heterogeneous Federated Learning Using Knowledge Codistillation. CoRR (2023)
Tien-Ju Yang, Yonghui Xiao, Giovanni Motta, Françoise Beaufays, Rajiv Mathews, Mingqing Chen
Online Model Compression for Federated Learning with Large Models. ICASSP (2023)
Lillian Zhou, Yuxin Ding, Mingqing Chen, Harry Zhang, Rohit Prabhavalkar, Dhruv Guliani, Giovanni Motta, Rajiv Mathews
The Gift of Feedback: Improving ASR Model Quality by Learning from User Corrections through Federated Learning. CoRR (2023)
Virat Shejwalkar, Arun Ganesh, Rajiv Mathews, Om Thakkar, Abhradeep Thakurta
Recycling Scraps: Improving Private Learning by Leveraging Intermediate Checkpoints. CoRR (2022)
Theresa Breiner, Swaroop Ramaswamy, Ehsan Variani, Shefali Garg, Rajiv Mathews, Khe Chai Sim, Kilol Gupta, Mingqing Chen, Lara McConnaughey
UserLibri: A Dataset for ASR Personalization Using Only Text. INTERSPEECH (2022)
Ehsan Amid, Om Thakkar, Arun Narayanan, Rajiv Mathews, Françoise Beaufays
Extracting Targeted Training Data from ASR Models, and How to Mitigate It. CoRR (2022)
W. Ronny Huang, Steve Chien, Om Dipakbhai Thakkar, Rajiv Mathews
Detecting Unintended Memorization in Language-Model-Fused ASR. INTERSPEECH (2022)
Sandy Ritchie, You-Chi Cheng, Mingqing Chen, Rajiv Mathews, Daan van Esch, Bo Li, Khe Chai Sim
Large vocabulary speech recognition for languages of Africa: multilingual modeling and self-supervised learning. CoRR (2022)
Trung Dang, Om Thakkar, Swaroop Ramaswamy, Rajiv Mathews, Peter Chin, Françoise Beaufays
A Method to Reveal Speaker Identity in Distributed ASR Training, and How to Counter IT. ICASSP (2022)
Hao Zhang, You-Chi Cheng, Shankar Kumar, W. Ronny Huang, Mingqing Chen, Rajiv Mathews
Capitalization Normalization for Language Modeling with an Accurate and Efficient Hierarchical RNN Model. CoRR (2022)
Ehsan Amid, Om Dipakbhai Thakkar, Arun Narayanan, Rajiv Mathews, Françoise Beaufays
Extracting Targeted Training Data from ASR Models, and How to Mitigate It. INTERSPEECH (2022)
Jae Hun Ro, Theresa Breiner, Lara McConnaughey, Mingqing Chen, Ananda Theertha Suresh, Shankar Kumar, Rajiv Mathews
Scaling Language Model Size in Cross-Device Federated Learning. CoRR (2022)
Andrew Hard, Kurt Partridge, Neng Chen, Sean Augenstein, Aishanee Shah, Hyun Jin Park, Alex Park, Sara Ng, Jessica Nguyen, Ignacio Lopez-Moreno, Rajiv Mathews, Françoise Beaufays
Production federated keyword spotting via distillation, filtering, and joint federated-centralized training. INTERSPEECH (2022)
Sean Augenstein, Andrew Hard, Lin Ning, Karan Singhal, Satyen Kale, Kurt Partridge, Rajiv Mathews
Mixed Federated Learning: Joint Decentralized and Centralized Learning. CoRR (2022)
Tien-Ju Yang, Yonghui Xiao, Giovanni Motta, Françoise Beaufays, Rajiv Mathews, Mingqing Chen
Online Model Compression for Federated Learning with Large Models. CoRR (2022)
W. Ronny Huang, Steve Chien, Om Thakkar, Rajiv Mathews
Detecting Unintended Memorization in Language-Model-Fused ASR. CoRR (2022)
Andrew Hard, Kurt Partridge, Neng Chen, Sean Augenstein, Aishanee Shah, Hyun Jin Park, Alex Park, Sara Ng, Jessica Nguyen, Ignacio Lopez-Moreno, Rajiv Mathews, Françoise Beaufays
Production federated keyword spotting via distillation, filtering, and joint federated-centralized training. CoRR (2022)
Ehsan Amid, Arun Ganesh, Rajiv Mathews, Swaroop Ramaswamy, Shuang Song, Thomas Steinke, Vinith M. Suriyakumar, Om Thakkar, Abhradeep Thakurta
Public Data-Assisted Mirror Descent for Private Model Training. ICML (2022)
Theresa Breiner, Swaroop Ramaswamy, Ehsan Variani, Shefali Garg, Rajiv Mathews, Khe Chai Sim, Kilol Gupta, Mingqing Chen, Lara McConnaughey
UserLibri: A Dataset for ASR Personalization Using Only Text. CoRR (2022)
Hao Zhang, You-Chi Cheng, Shankar Kumar, W. Ronny Huang, Mingqing Chen, Rajiv Mathews
Capitalization Normalization for Language Modeling with an Accurate and Efficient Hierarchical RNN Model. ICASSP (2022)
Jae Ro, Mingqing Chen, Rajiv Mathews, Mehryar Mohri, Ananda Theertha Suresh
Communication-Efficient Agnostic Federated Averaging. Interspeech (2021)
Sean Augenstein, Andrew Hard, Kurt Partridge, Rajiv Mathews
Jointly Learning from Decentralized (Federated) and Centralized Data to Mitigate Distribution Shift. CoRR (2021)
Trung Dang, Om Thakkar, Swaroop Ramaswamy, Rajiv Mathews, Peter Chin, Françoise Beaufays
Revealing and Protecting Labels in Distributed Training. CoRR (2021)
Trung Dang, Om Thakkar, Swaroop Ramaswamy, Rajiv Mathews, Peter Chin, Françoise Beaufays
Revealing and Protecting Labels in Distributed Training. NeurIPS (2021)
Trung Dang, Om Thakkar, Swaroop Ramaswamy, Rajiv Mathews, Peter Chin, Françoise Beaufays
A Method to Reveal Speaker Identity in Distributed ASR Training, and How to Counter It. CoRR (2021)
Hao Zhang, You-Chi Cheng, Shankar Kumar, Mingqing Chen, Rajiv Mathews
Position-Invariant Truecasing with a Word-and-Character Hierarchical Recurrent Neural Network. CoRR (2021)
Jae Ro, Mingqing Chen, Rajiv Mathews, Mehryar Mohri, Ananda Theertha Suresh
Communication-Efficient Agnostic Federated Averaging. CoRR (2021)
Ehsan Amid, Arun Ganesh, Rajiv Mathews, Swaroop Ramaswamy, Shuang Song, Thomas Steinke, Vinith M. Suriyakumar, Om Thakkar, Abhradeep Thakurta
Public Data-Assisted Mirror Descent for Private Model Training. CoRR (2021)
Andrew Hard, Kurt Partridge, Cameron Nguyen, Niranjan Subrahmanya, Aishanee Shah, Pai Zhu, Ignacio Lopez-Moreno, Rajiv Mathews
Training Keyword Spotting Models on Non-IID Data with Federated Learning. INTERSPEECH (2020)
Andrew Hard, Kurt Partridge, Cameron Nguyen, Niranjan Subrahmanya, Aishanee Shah, Pai Zhu, Ignacio Lopez-Moreno, Rajiv Mathews
Training Keyword Spotting Models on Non-IID Data with Federated Learning. CoRR (2020)
Swaroop Ramaswamy, Om Thakkar, Rajiv Mathews, Galen Andrew, H. Brendan McMahan, Françoise Beaufays
Training Production Language Models without Memorizing User Data. CoRR (2020)
Om Thakkar, Swaroop Ramaswamy, Rajiv Mathews, Françoise Beaufays
Understanding Unintended Memorization in Federated Learning. CoRR (2020)
Sean Augenstein, H. Brendan McMahan, Daniel Ramage, Swaroop Ramaswamy, Peter Kairouz, Mingqing Chen, Rajiv Mathews, Blaise Agüera y Arcas
Generative Models for Effective ML on Private, Decentralized Datasets. ICLR (2020)
Mingqing Chen, Ananda Theertha Suresh, Rajiv Mathews, Adeline Wong, Cyril Allauzen, Françoise Beaufays, Michael Riley
Federated Learning of N-gram Language Models. CoRR (2019)
Mingqing Chen, Ananda Theertha Suresh, Rajiv Mathews, Adeline Wong, Cyril Allauzen, Françoise Beaufays, Michael Riley
Federated Learning of N-Gram Language Models. CoNLL (2019)
Mingqing Chen, Rajiv Mathews, Tom Ouyang, Françoise Beaufays
Federated Learning Of Out-Of-Vocabulary Words. CoRR (2019)
Sean Augenstein, H. Brendan McMahan, Daniel Ramage, Swaroop Ramaswamy, Peter Kairouz, Mingqing Chen, Rajiv Mathews, Blaise Agüera y Arcas
Generative Models for Effective ML on Private, Decentralized Datasets. CoRR (2019)
Swaroop Ramaswamy, Rajiv Mathews, Kanishka Rao, Françoise Beaufays
Federated Learning for Emoji Prediction in a Mobile Keyboard. CoRR (2019)
Kangkang Wang, Rajiv Mathews, Chloé Kiddon, Hubert Eichner, Françoise Beaufays, Daniel Ramage
Federated Evaluation of On-device Personalization. CoRR (2019)
Andrew Hard, Kanishka Rao, Rajiv Mathews, Françoise Beaufays, Sean Augenstein, Hubert Eichner, Chloé Kiddon, Daniel Ramage
Federated Learning for Mobile Keyboard Prediction. CoRR (2018)