default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDRajiv Mathews
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
[c16]Lun Wang, Om Thakkar, Rajiv Mathews:
Unintended Memorization in Large ASR Models, and How to Mitigate It. ICASSP 2024: 4655-4659- [c15]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: 6100-6104 - [i30]Andrew Hard, Antonious M. Girgis, Ehsan Amid, Sean Augenstein, Lara McConnaughey, Rajiv Mathews, Rohan Anil:
Learning from straggler clients in federated learning. CoRR abs/2403.09086 (2024) - [i29]Xuan Kan, Yonghui Xiao, Tien-Ju Yang, Nanxin Chen, Rajiv Mathews:
Parameter-Efficient Transfer Learning under Federated Learning for Automatic Speech Recognition. CoRR abs/2408.11873 (2024) - 2023
- [c14]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: 1-7 - [c13]Tien-Ju Yang, Yonghui Xiao, Giovanni Motta, Françoise Beaufays, Rajiv Mathews, Mingqing Chen:
Online Model Compression for Federated Learning with Large Models. ICASSP 2023: 1-5 - [i28]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 abs/2310.00141 (2023) - [i27]Jared Lichtarge, Ehsan Amid, Shankar Kumar, Tien-Ju Yang, Rohan Anil, Rajiv Mathews:
Heterogeneous Federated Learning Using Knowledge Codistillation. CoRR abs/2310.02549 (2023) - [i26]Lun Wang, Om Thakkar, Rajiv Mathews:
Unintended Memorization in Large ASR Models, and How to Mitigate It. CoRR abs/2310.11739 (2023) - 2022
- [c12]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: 4338-4342 - [c11]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: 6097-6101 - [c10]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: 517-535 - [c9]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:
Production federated keyword spotting via distillation, filtering, and joint federated-centralized training. INTERSPEECH 2022: 76-80 - [c8]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: 694-698 - [c7]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: 2803-2807 - [c6]W. Ronny Huang, Steve Chien, Om Dipakbhai Thakkar, Rajiv Mathews:
Detecting Unintended Memorization in Language-Model-Fused ASR. INTERSPEECH 2022: 2808-2812 - [i25]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 abs/2202.08171 (2022) - [i24]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:
Production federated keyword spotting via distillation, filtering, and joint federated-centralized training. CoRR abs/2204.06322 (2022) - [i23]Ehsan Amid, Om Thakkar, Arun Narayanan, Rajiv Mathews, Françoise Beaufays:
Extracting Targeted Training Data from ASR Models, and How to Mitigate It. CoRR abs/2204.08345 (2022) - [i22]W. Ronny Huang, Steve Chien, Om Thakkar, Rajiv Mathews:
Detecting Unintended Memorization in Language-Model-Fused ASR. CoRR abs/2204.09606 (2022) - [i21]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 abs/2204.09715 (2022) - [i20]Tien-Ju Yang, Yonghui Xiao, Giovanni Motta, Françoise Beaufays, Rajiv Mathews, Mingqing Chen:
Online Model Compression for Federated Learning with Large Models. CoRR abs/2205.03494 (2022) - [i19]Sean Augenstein, Andrew Hard, Lin Ning, Karan Singhal, Satyen Kale, Kurt Partridge, Rajiv Mathews:
Mixed Federated Learning: Joint Decentralized and Centralized Learning. CoRR abs/2205.13655 (2022) - [i18]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 abs/2207.00706 (2022) - [i17]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 abs/2208.03067 (2022) - [i16]Virat Shejwalkar, Arun Ganesh, Rajiv Mathews, Om Thakkar, Abhradeep Thakurta:
Recycling Scraps: Improving Private Learning by Leveraging Intermediate Checkpoints. CoRR abs/2210.01864 (2022) - 2021
- [c5]Jae Ro, Mingqing Chen, Rajiv Mathews, Mehryar Mohri, Ananda Theertha Suresh:
Communication-Efficient Agnostic Federated Averaging. Interspeech 2021: 871-875 - [c4]Trung Dang, Om Thakkar, Swaroop Ramaswamy, Rajiv Mathews, Peter Chin, Françoise Beaufays:
Revealing and Protecting Labels in Distributed Training. NeurIPS 2021: 1727-1738 - [i15]Jae Ro, Mingqing Chen, Rajiv Mathews, Mehryar Mohri, Ananda Theertha Suresh:
Communication-Efficient Agnostic Federated Averaging. CoRR abs/2104.02748 (2021) - [i14]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 abs/2104.07815 (2021) - [i13]Hao Zhang, You-Chi Cheng, Shankar Kumar, Mingqing Chen, Rajiv Mathews:
Position-Invariant Truecasing with a Word-and-Character Hierarchical Recurrent Neural Network. CoRR abs/2108.11943 (2021) - [i12]Trung Dang, Om Thakkar, Swaroop Ramaswamy, Rajiv Mathews, Peter Chin, Françoise Beaufays:
Revealing and Protecting Labels in Distributed Training. CoRR abs/2111.00556 (2021) - [i11]Sean Augenstein, Andrew Hard, Kurt Partridge, Rajiv Mathews:
Jointly Learning from Decentralized (Federated) and Centralized Data to Mitigate Distribution Shift. CoRR abs/2111.12150 (2021) - [i10]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 abs/2112.00193 (2021) - 2020
- [c3]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 - [c2]Andrew Hard, Kurt Partridge, Cameron Nguyen, Niranjan Subrahmanya, Aishanee Shah, Pai Zhu, Ignacio López-Moreno, Rajiv Mathews:
Training Keyword Spotting Models on Non-IID Data with Federated Learning. INTERSPEECH 2020: 4343-4347 - [i9]Andrew Hard, Kurt Partridge, Cameron Nguyen, Niranjan Subrahmanya, Aishanee Shah, Pai Zhu, Ignacio López-Moreno, Rajiv Mathews:
Training Keyword Spotting Models on Non-IID Data with Federated Learning. CoRR abs/2005.10406 (2020) - [i8]Om Thakkar, Swaroop Ramaswamy, Rajiv Mathews, Françoise Beaufays:
Understanding Unintended Memorization in Federated Learning. CoRR abs/2006.07490 (2020) - [i7]Swaroop Ramaswamy, Om Thakkar, Rajiv Mathews, Galen Andrew, H. Brendan McMahan, Françoise Beaufays:
Training Production Language Models without Memorizing User Data. CoRR abs/2009.10031 (2020)
2010 – 2019
- 2019
- [c1]Mingqing Chen, Ananda Theertha Suresh, Rajiv Mathews, Adeline Wong, Cyril Allauzen, Françoise Beaufays, Michael Riley:
Federated Learning of N-Gram Language Models. CoNLL 2019: 121-130 - [i6]Mingqing Chen, Rajiv Mathews, Tom Ouyang, Françoise Beaufays:
Federated Learning Of Out-Of-Vocabulary Words. CoRR abs/1903.10635 (2019) - [i5]Swaroop Ramaswamy, Rajiv Mathews, Kanishka Rao, Françoise Beaufays:
Federated Learning for Emoji Prediction in a Mobile Keyboard. CoRR abs/1906.04329 (2019) - [i4]Mingqing Chen, Ananda Theertha Suresh, Rajiv Mathews, Adeline Wong, Cyril Allauzen, Françoise Beaufays, Michael Riley:
Federated Learning of N-gram Language Models. CoRR abs/1910.03432 (2019) - [i3]Kangkang Wang, Rajiv Mathews, Chloé Kiddon, Hubert Eichner, Françoise Beaufays, Daniel Ramage:
Federated Evaluation of On-device Personalization. CoRR abs/1910.10252 (2019) - [i2]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 abs/1911.06679 (2019) - 2018
- [i1]Andrew Hard, Kanishka Rao, Rajiv Mathews, Françoise Beaufays, Sean Augenstein, Hubert Eichner, Chloé Kiddon, Daniel Ramage:
Federated Learning for Mobile Keyboard Prediction. CoRR abs/1811.03604 (2018)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-09-30 00:07 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
