Project Florida: Federated Learning Made Easy
Daniel Madrigal, Andre Manoel, Jialei Chen, Nalin Singal, Robert Sim
| July 2023
Publié par Microsoft
Return to Microsoft Research Lab – Redmond
Privacy in AI (PAI)
Publications
Publications par année
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Synthetic Text Generation with Differential Privacy: A Simple and Practical Recipe
Xiang Yue, Huseyin Inan, Xuechen Li, Girish Kumar, Julia McAnallen, Huan Sun, David Levitan, Robert Sim
ACL 2023 | July 2023
Federated Multilingual Models for Medical Transcript Analysis
Andre Manoel, Mirian Hipolito Garcia, Tal Baumel, Shize Su, Jialei Chen, Dan Miller, Danny Karmon, Robert Sim, Dimitrios Dimitriadis
Conference on Health, Inference, and Learning | June 2023
Distribution Inference Risks: Identifying and Mitigating Sources of Leakage
Valentin Hartmann, Leo Meynent, Maxime Peyrard, Dimitrios Dimitriadis, Shruti Tople, Robert West
IEEE Conference on Secure and Trustworthy Machine Learning (SatML) | February 2023
-
Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning
Yae Jee Cho, Andre Manoel, Gauri Joshi, Robert Sim, Dimitrios Dimitriadis
IJCAI-ECAI’22 | August 2022
dp-transformers: Training transformer models with differential privacy
Huseyin Inan, Andre Manoel, Lukas Wutschitz
July 2022
UserIdentifier: Implicit User Representations for Simple and Effective Personalized Sentiment Analysis
Fatemehsadat Mireshghallah, Vaishnavi Shrivastava, Milad Shokouhi, Taylor Berg-Kirkpatrick, Robert Sim, Dimitrios Dimitriadis
2022 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL’22) | July 2022
Privacy Leakage in Text Classification: A Data Extraction Approach
Adel Elmahdy, Huseyin Inan, Robert Sim
June 2022
Personalized Federated Learning with Adaptive Batchnorm for Healthcare
Wang Lu, Jindong Wang, Yiqiang Chen, Xin Qin, Renjun Xu, Dimitrios Dimitriadis, Tao Qin
IEEE Transactions on Big Data | May 2022
Differentially private fine-tuning of language models
Da Yu, Saurabh Naik, Arturs Backurs, Sivakanth Gopi, Huseyin Inan, Gautam Kamath, Janardhan (Jana) Kulkarni, Yin Tat Lee, Andre Manoel, Lukas Wutschitz, Sergey Yekhanin, Huishuai Zhang
ICLR 2022 | April 2022
FLUTE: A Scalable, Extensible Framework for High-Performance Federated Learning Simulations
Dimitrios Dimitriadis, Mirian Hipolito Garcia, Daniel Madrigal, Andre Manoel, Robert Sim
March 2022
-
A Review of Speaker Diarization: Recent Advances with Deep Learning
Tae Jin Park, Naoyuki Kanda, Dimitrios Dimitriadis, Kyu J. Han, Shinji Watanabe, Shrikanth Narayanan
Computer Speech & Language | November 2021, Vol 72
Tackling Dynamics in Federated Incremental Learning with Variational Embedding Rehearsal
Tae Jin Park, Kenichi Kumatani, Dimitrios Dimitriadis
October 2021
Membership Inference Attacks Against NLP Classification Models
Virat Shejwalkar, Huseyin Inan, Amir Houmansadr, Robert Sim
NeurIPS 2021 Workshop Privacy in Machine Learning | September 2021
One-Shot Voice Conversion with Speaker-Agnostic StarGAN
Sefik Emre Eskimez, Dimitrios Dimitriadis, Kenichi Kumatani, Robert Gmyr
INTERSPEECH 2022 | August 2021
Ensemble Combination between Different Time Segmentations
Jeremy Wong, Dimitrios Dimitriadis, Kenichi Kumatani, Yashesh Gaur, George Polovets, Partha Parthasarathy, Eric Sun, Jinyu Li, Yifan Gong
2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) | June 2021
Privacy Regularization: Joint Privacy-Utility Optimization in Language Models
Fatemehsadat Mireshghallah, Huseyin Inan, Marcello Hasegawa, Victor Rühle, Taylor Berg-Kirkpatrick, Robert Sim
2021 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2021) | June 2021
Training Data Leakage Analysis in Language Models
Huseyin A. Inan, Osman Ramadan, Lukas Wutschitz, Daniel Jones, Victor Rühle, James Withers, Robert Sim
February 2021
-
A Federated Approach in Training Acoustic Models
Dimitrios Dimitriadis, Kenichi Kumatani, Robert Gmyr, Yashesh Gaur, Sefik Emre Eskimez
INTERSPEECH 2020 | October 2020
GAN-based Data Generation for Speech Emotion Recognition
Sefik Emre Eskimez, Dimitrios Dimitriadis, Robert Gmyr, Kenichi Kumatani
INTERSPEECH 2020 | October 2020
Sequence-level self-learning with multi-task learning framework
Kenichi Kumatani, Dimitrios Dimitriadis, Yashesh Gaur, Robert Gmyr, Sefik Emre Eskimez, Jinyu Li, Michael Zeng
October 2020
Filtre par zone de recherche
-
Project Florida: Federated Learning Made Easy
Daniel Madrigal, Andre Manoel, Jialei Chen, Nalin Singal, Robert Sim
| July 2023
Publié par Microsoft
Synthetic Text Generation with Differential Privacy: A Simple and Practical Recipe
Xiang Yue, Huseyin Inan, Xuechen Li, Girish Kumar, Julia McAnallen, Huan Sun, David Levitan, Robert Sim
ACL 2023 | July 2023
Federated Multilingual Models for Medical Transcript Analysis
Andre Manoel, Mirian Hipolito Garcia, Tal Baumel, Shize Su, Jialei Chen, Dan Miller, Danny Karmon, Robert Sim, Dimitrios Dimitriadis
Conference on Health, Inference, and Learning | June 2023
Distribution Inference Risks: Identifying and Mitigating Sources of Leakage
Valentin Hartmann, Leo Meynent, Maxime Peyrard, Dimitrios Dimitriadis, Shruti Tople, Robert West
IEEE Conference on Secure and Trustworthy Machine Learning (SatML) | February 2023
Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning
Yae Jee Cho, Andre Manoel, Gauri Joshi, Robert Sim, Dimitrios Dimitriadis
IJCAI-ECAI’22 | August 2022
dp-transformers: Training transformer models with differential privacy
Huseyin Inan, Andre Manoel, Lukas Wutschitz
July 2022
UserIdentifier: Implicit User Representations for Simple and Effective Personalized Sentiment Analysis
Fatemehsadat Mireshghallah, Vaishnavi Shrivastava, Milad Shokouhi, Taylor Berg-Kirkpatrick, Robert Sim, Dimitrios Dimitriadis
2022 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL’22) | July 2022
Personalized Federated Learning with Adaptive Batchnorm for Healthcare
Wang Lu, Jindong Wang, Yiqiang Chen, Xin Qin, Renjun Xu, Dimitrios Dimitriadis, Tao Qin
IEEE Transactions on Big Data | May 2022
FLUTE: A Scalable, Extensible Framework for High-Performance Federated Learning Simulations
Dimitrios Dimitriadis, Mirian Hipolito Garcia, Daniel Madrigal, Andre Manoel, Robert Sim
March 2022
A Review of Speaker Diarization: Recent Advances with Deep Learning
Tae Jin Park, Naoyuki Kanda, Dimitrios Dimitriadis, Kyu J. Han, Shinji Watanabe, Shrikanth Narayanan
Computer Speech & Language | November 2021, Vol 72
Tackling Dynamics in Federated Incremental Learning with Variational Embedding Rehearsal
Tae Jin Park, Kenichi Kumatani, Dimitrios Dimitriadis
October 2021
Membership Inference Attacks Against NLP Classification Models
Virat Shejwalkar, Huseyin Inan, Amir Houmansadr, Robert Sim
NeurIPS 2021 Workshop Privacy in Machine Learning | September 2021
One-Shot Voice Conversion with Speaker-Agnostic StarGAN
Sefik Emre Eskimez, Dimitrios Dimitriadis, Kenichi Kumatani, Robert Gmyr
INTERSPEECH 2022 | August 2021
Ensemble Combination between Different Time Segmentations
Jeremy Wong, Dimitrios Dimitriadis, Kenichi Kumatani, Yashesh Gaur, George Polovets, Partha Parthasarathy, Eric Sun, Jinyu Li, Yifan Gong
2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) | June 2021
Privacy Regularization: Joint Privacy-Utility Optimization in Language Models
Fatemehsadat Mireshghallah, Huseyin Inan, Marcello Hasegawa, Victor Rühle, Taylor Berg-Kirkpatrick, Robert Sim
2021 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2021) | June 2021
Training Data Leakage Analysis in Language Models
Huseyin A. Inan, Osman Ramadan, Lukas Wutschitz, Daniel Jones, Victor Rühle, James Withers, Robert Sim
February 2021
Sequence-level self-learning with multi-task learning framework
Kenichi Kumatani, Dimitrios Dimitriadis, Yashesh Gaur, Robert Gmyr, Sefik Emre Eskimez, Jinyu Li, Michael Zeng
October 2020
GAN-based Data Generation for Speech Emotion Recognition
Sefik Emre Eskimez, Dimitrios Dimitriadis, Robert Gmyr, Kenichi Kumatani
INTERSPEECH 2020 | October 2020
A Federated Approach in Training Acoustic Models
Dimitrios Dimitriadis, Kenichi Kumatani, Robert Gmyr, Yashesh Gaur, Sefik Emre Eskimez
INTERSPEECH 2020 | October 2020
-
Federated Multilingual Models for Medical Transcript Analysis
Andre Manoel, Mirian Hipolito Garcia, Tal Baumel, Shize Su, Jialei Chen, Dan Miller, Danny Karmon, Robert Sim, Dimitrios Dimitriadis
Conference on Health, Inference, and Learning | June 2023
-
Synthetic Text Generation with Differential Privacy: A Simple and Practical Recipe
Xiang Yue, Huseyin Inan, Xuechen Li, Girish Kumar, Julia McAnallen, Huan Sun, David Levitan, Robert Sim
ACL 2023 | July 2023
Distribution Inference Risks: Identifying and Mitigating Sources of Leakage
Valentin Hartmann, Leo Meynent, Maxime Peyrard, Dimitrios Dimitriadis, Shruti Tople, Robert West
IEEE Conference on Secure and Trustworthy Machine Learning (SatML) | February 2023
dp-transformers: Training transformer models with differential privacy
Huseyin Inan, Andre Manoel, Lukas Wutschitz
July 2022
Privacy Leakage in Text Classification: A Data Extraction Approach
Adel Elmahdy, Huseyin Inan, Robert Sim
June 2022
FLUTE: A Scalable, Extensible Framework for High-Performance Federated Learning Simulations
Dimitrios Dimitriadis, Mirian Hipolito Garcia, Daniel Madrigal, Andre Manoel, Robert Sim
March 2022
Privacy Regularization: Joint Privacy-Utility Optimization in Language Models
Fatemehsadat Mireshghallah, Huseyin Inan, Marcello Hasegawa, Victor Rühle, Taylor Berg-Kirkpatrick, Robert Sim
2021 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2021) | June 2021
Training Data Leakage Analysis in Language Models
Huseyin A. Inan, Osman Ramadan, Lukas Wutschitz, Daniel Jones, Victor Rühle, James Withers, Robert Sim
February 2021
-
Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning
Yae Jee Cho, Andre Manoel, Gauri Joshi, Robert Sim, Dimitrios Dimitriadis
IJCAI-ECAI’22 | August 2022
Differentially private fine-tuning of language models
Da Yu, Saurabh Naik, Arturs Backurs, Sivakanth Gopi, Huseyin Inan, Gautam Kamath, Janardhan (Jana) Kulkarni, Yin Tat Lee, Andre Manoel, Lukas Wutschitz, Sergey Yekhanin, Huishuai Zhang
ICLR 2022 | April 2022
Tackling Dynamics in Federated Incremental Learning with Variational Embedding Rehearsal
Tae Jin Park, Kenichi Kumatani, Dimitrios Dimitriadis
October 2021
Sequence-level self-learning with multi-task learning framework
Kenichi Kumatani, Dimitrios Dimitriadis, Yashesh Gaur, Robert Gmyr, Sefik Emre Eskimez, Jinyu Li, Michael Zeng
October 2020
-
UserIdentifier: Implicit User Representations for Simple and Effective Personalized Sentiment Analysis
Fatemehsadat Mireshghallah, Vaishnavi Shrivastava, Milad Shokouhi, Taylor Berg-Kirkpatrick, Robert Sim, Dimitrios Dimitriadis
2022 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL’22) | July 2022
A Review of Speaker Diarization: Recent Advances with Deep Learning
Tae Jin Park, Naoyuki Kanda, Dimitrios Dimitriadis, Kyu J. Han, Shinji Watanabe, Shrikanth Narayanan
Computer Speech & Language | November 2021, Vol 72
Ensemble Combination between Different Time Segmentations
Jeremy Wong, Dimitrios Dimitriadis, Kenichi Kumatani, Yashesh Gaur, George Polovets, Partha Parthasarathy, Eric Sun, Jinyu Li, Yifan Gong
2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) | June 2021
Privacy Regularization: Joint Privacy-Utility Optimization in Language Models
Fatemehsadat Mireshghallah, Huseyin Inan, Marcello Hasegawa, Victor Rühle, Taylor Berg-Kirkpatrick, Robert Sim
2021 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2021) | June 2021
Training Data Leakage Analysis in Language Models
Huseyin A. Inan, Osman Ramadan, Lukas Wutschitz, Daniel Jones, Victor Rühle, James Withers, Robert Sim
February 2021
-
A Review of Speaker Diarization: Recent Advances with Deep Learning
Tae Jin Park, Naoyuki Kanda, Dimitrios Dimitriadis, Kyu J. Han, Shinji Watanabe, Shrikanth Narayanan
Computer Speech & Language | November 2021, Vol 72
Ensemble Combination between Different Time Segmentations
Jeremy Wong, Dimitrios Dimitriadis, Kenichi Kumatani, Yashesh Gaur, George Polovets, Partha Parthasarathy, Eric Sun, Jinyu Li, Yifan Gong
2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) | June 2021
-
Ensemble Combination between Different Time Segmentations
Jeremy Wong, Dimitrios Dimitriadis, Kenichi Kumatani, Yashesh Gaur, George Polovets, Partha Parthasarathy, Eric Sun, Jinyu Li, Yifan Gong
2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) | June 2021
Sequence-level self-learning with multi-task learning framework
Kenichi Kumatani, Dimitrios Dimitriadis, Yashesh Gaur, Robert Gmyr, Sefik Emre Eskimez, Jinyu Li, Michael Zeng
October 2020
GAN-based Data Generation for Speech Emotion Recognition
Sefik Emre Eskimez, Dimitrios Dimitriadis, Robert Gmyr, Kenichi Kumatani
INTERSPEECH 2020 | October 2020
A Federated Approach in Training Acoustic Models
Dimitrios Dimitriadis, Kenichi Kumatani, Robert Gmyr, Yashesh Gaur, Sefik Emre Eskimez
INTERSPEECH 2020 | October 2020
-
A Federated Approach in Training Acoustic Models
Dimitrios Dimitriadis, Kenichi Kumatani, Robert Gmyr, Yashesh Gaur, Sefik Emre Eskimez
INTERSPEECH 2020 | October 2020
Publication Type
-
Project Florida: Federated Learning Made Easy
Daniel Madrigal, Andre Manoel, Jialei Chen, Nalin Singal, Robert Sim
| July 2023
Publié par Microsoft
-
Synthetic Text Generation with Differential Privacy: A Simple and Practical Recipe
Xiang Yue, Huseyin Inan, Xuechen Li, Girish Kumar, Julia McAnallen, Huan Sun, David Levitan, Robert Sim
ACL 2023 | July 2023
Federated Multilingual Models for Medical Transcript Analysis
Andre Manoel, Mirian Hipolito Garcia, Tal Baumel, Shize Su, Jialei Chen, Dan Miller, Danny Karmon, Robert Sim, Dimitrios Dimitriadis
Conference on Health, Inference, and Learning | June 2023
Distribution Inference Risks: Identifying and Mitigating Sources of Leakage
Valentin Hartmann, Leo Meynent, Maxime Peyrard, Dimitrios Dimitriadis, Shruti Tople, Robert West
IEEE Conference on Secure and Trustworthy Machine Learning (SatML) | February 2023
Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning
Yae Jee Cho, Andre Manoel, Gauri Joshi, Robert Sim, Dimitrios Dimitriadis
IJCAI-ECAI’22 | August 2022
UserIdentifier: Implicit User Representations for Simple and Effective Personalized Sentiment Analysis
Fatemehsadat Mireshghallah, Vaishnavi Shrivastava, Milad Shokouhi, Taylor Berg-Kirkpatrick, Robert Sim, Dimitrios Dimitriadis
2022 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL’22) | July 2022
Differentially private fine-tuning of language models
Da Yu, Saurabh Naik, Arturs Backurs, Sivakanth Gopi, Huseyin Inan, Gautam Kamath, Janardhan (Jana) Kulkarni, Yin Tat Lee, Andre Manoel, Lukas Wutschitz, Sergey Yekhanin, Huishuai Zhang
ICLR 2022 | April 2022
Membership Inference Attacks Against NLP Classification Models
Virat Shejwalkar, Huseyin Inan, Amir Houmansadr, Robert Sim
NeurIPS 2021 Workshop Privacy in Machine Learning | September 2021
One-Shot Voice Conversion with Speaker-Agnostic StarGAN
Sefik Emre Eskimez, Dimitrios Dimitriadis, Kenichi Kumatani, Robert Gmyr
INTERSPEECH 2022 | August 2021
Ensemble Combination between Different Time Segmentations
Jeremy Wong, Dimitrios Dimitriadis, Kenichi Kumatani, Yashesh Gaur, George Polovets, Partha Parthasarathy, Eric Sun, Jinyu Li, Yifan Gong
2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) | June 2021
Privacy Regularization: Joint Privacy-Utility Optimization in Language Models
Fatemehsadat Mireshghallah, Huseyin Inan, Marcello Hasegawa, Victor Rühle, Taylor Berg-Kirkpatrick, Robert Sim
2021 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2021) | June 2021
GAN-based Data Generation for Speech Emotion Recognition
Sefik Emre Eskimez, Dimitrios Dimitriadis, Robert Gmyr, Kenichi Kumatani
INTERSPEECH 2020 | October 2020
A Federated Approach in Training Acoustic Models
Dimitrios Dimitriadis, Kenichi Kumatani, Robert Gmyr, Yashesh Gaur, Sefik Emre Eskimez
INTERSPEECH 2020 | October 2020
-
dp-transformers: Training transformer models with differential privacy
Huseyin Inan, Andre Manoel, Lukas Wutschitz
July 2022
Training Data Leakage Analysis in Language Models
Huseyin A. Inan, Osman Ramadan, Lukas Wutschitz, Daniel Jones, Victor Rühle, James Withers, Robert Sim
February 2021
Sequence-level self-learning with multi-task learning framework
Kenichi Kumatani, Dimitrios Dimitriadis, Yashesh Gaur, Robert Gmyr, Sefik Emre Eskimez, Jinyu Li, Michael Zeng
October 2020
-
Privacy Leakage in Text Classification: A Data Extraction Approach
Adel Elmahdy, Huseyin Inan, Robert Sim
June 2022
FLUTE: A Scalable, Extensible Framework for High-Performance Federated Learning Simulations
Dimitrios Dimitriadis, Mirian Hipolito Garcia, Daniel Madrigal, Andre Manoel, Robert Sim
March 2022
Tackling Dynamics in Federated Incremental Learning with Variational Embedding Rehearsal
Tae Jin Park, Kenichi Kumatani, Dimitrios Dimitriadis
October 2021
-
Personalized Federated Learning with Adaptive Batchnorm for Healthcare
Wang Lu, Jindong Wang, Yiqiang Chen, Xin Qin, Renjun Xu, Dimitrios Dimitriadis, Tao Qin
IEEE Transactions on Big Data | May 2022
A Review of Speaker Diarization: Recent Advances with Deep Learning
Tae Jin Park, Naoyuki Kanda, Dimitrios Dimitriadis, Kyu J. Han, Shinji Watanabe, Shrikanth Narayanan
Computer Speech & Language | November 2021, Vol 72