Congzheng Song

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 33

Top Topics

Gaussian Process

Sensitive Attributes

Top Venues

IEEE Symposium on Security and Privacy

Publications

Tao Yu, Congzheng Song, Jianyu Wang, Mona Chitnis
Momentum Approximation in Asynchronous Private Federated Learning. CoRR (2024)
Filip Granqvist, Congzheng Song, Áine Cahill, Rogier C. van Dalen, Martin Pelikan, Yi Sheng Chan, Xiaojun Feng, Natarajan Krishnaswami, Vojta Jina, Mona Chitnis
pfl-research: simulation framework for accelerating research in Private Federated Learning. CoRR (2024)
Mingbin Xu, Congzheng Song, Ye Tian, Neha Agrawal, Filip Granqvist, Rogier C. van Dalen, Xiao Zhang, Arturo Argueta, Shiyi Han, Yaqiao Deng, Leo Liu, Anmol Walia, Alex Jin
Training Large-Vocabulary Neural Language Models by Private Federated Learning for Resource-Constrained Devices. ICASSP (2023)
Kunal Talwar, Shan Wang, Audra McMillan, Vojta Jina, Vitaly Feldman, Bailey Basile, Áine Cahill, Yi Sheng Chan, Mike Chatzidakis, Junye Chen, Oliver Chick, Mona Chitnis, Suman Ganta, Yusuf Goren, Filip Granqvist, Kristine Guo, Frederic Jacobs, Omid Javidbakht, Albert Liu, Richard Low, Dan Mascenik, Steve Myers, David Park, Wonhee Park, Gianni Parsa, Tommy Pauly, Christian Priebe, Rehan Rishi, Guy Rothblum, Michael Scaria, Linmao Song, Congzheng Song, Karl Tarbe, Sebastian Vogt, Luke Winstrom, Shundong Zhou
Samplable Anonymous Aggregation for Private Federated Data Analysis. CoRR (2023)
Tatsuki Koga, Congzheng Song, Martin Pelikan, Mona Chitnis
Population Expansion for Training Language Models with Private Federated Learning. CoRR (2023)
Eugene Bagdasaryan, Congzheng Song, Rogier C. van Dalen, Matt Seigel, Áine Cahill
Training a Tokenizer for Free with Private Federated Learning. CoRR (2022)
Congzheng Song, Filip Granqvist, Kunal Talwar
FLAIR: Federated Learning Annotated Image Repository. NeurIPS (2022)
Congzheng Song, Filip Granqvist, Kunal Talwar
FLAIR: Federated Learning Annotated Image Repository. CoRR (2022)
Audra McMillan, Omid Javidbakht, Kunal Talwar, Elliot Briggs, Mike Chatzidakis, Junye Chen, John C. Duchi, Vitaly Feldman, Yusuf Goren, Michael Hesse, Vojta Jina, Anil Katti, Albert Liu, Cheney Lyford, Joey Meyer, Alex Palmer, David Park, Wonhee Park, Gianni Parsa, Paul Pelzl, Rehan Rishi, Congzheng Song, Shan Wang, Shundong Zhou
Private Federated Statistics in an Interactive Setting. CoRR (2022)
Mingbin Xu, Congzheng Song, Ye Tian, Neha Agrawal, Filip Granqvist, Rogier C. van Dalen, Xiao Zhang, Arturo Argueta, Shiyi Han, Yaqiao Deng, Leo Liu, Anmol Walia, Alex Jin
Training Large-Vocabulary Neural Language Models by Private Federated Learning for Resource-Constrained Devices. CoRR (2022)
Roei Schuster, Congzheng Song, Eran Tromer, Vitaly Shmatikov
You Autocomplete Me: Poisoning Vulnerabilities in Neural Code Completion. USENIX Security Symposium (2021)
Congzheng Song, Alexander M. Rush, Vitaly Shmatikov
Adversarial Semantic Collisions. EMNLP (1) (2020)
Congzheng Song, Reza Shokri
Membership Encoding for Deep Learning. AsiaCCS (2020)
Congzheng Song, Ananth Raghunathan
Information Leakage in Embedding Models. CoRR (2020)
Congzheng Song, Vitaly Shmatikov
Overlearning Reveals Sensitive Attributes. ICLR (2020)
Congzheng Song, Shanghang Zhang, Najmeh Sadoughi, Pengtao Xie, Eric P. Xing
Generalized Zero-Shot Text Classification for ICD Coding. IJCAI (2020)
Roei Schuster, Congzheng Song, Eran Tromer, Vitaly Shmatikov
You Autocomplete Me: Poisoning Vulnerabilities in Neural Code Completion. CoRR (2020)
Congzheng Song, Ananth Raghunathan
Information Leakage in Embedding Models. CCS (2020)
Congzheng Song, Alexander M. Rush, Vitaly Shmatikov
Adversarial Semantic Collisions. CoRR (2020)
Congzheng Song, Vitaly Shmatikov
Overlearning Reveals Sensitive Attributes. CoRR (2019)
Luca Melis, Congzheng Song, Emiliano De Cristofaro, Vitaly Shmatikov
Exploiting Unintended Feature Leakage in Collaborative Learning. IEEE Symposium on Security and Privacy (2019)
Congzheng Song, Shanghang Zhang, Najmeh Sadoughi, Pengtao Xie, Eric P. Xing
Generalized Zero-shot ICD Coding. CoRR (2019)
Congzheng Song, Reza Shokri
Membership Encoding for Deep Learning. CoRR (2019)
Congzheng Song, Vitaly Shmatikov
Auditing Data Provenance in Text-Generation Models. KDD (2019)
Congzheng Song, Vitaly Shmatikov
The Natural Auditor: How To Tell If Someone Used Your Words To Train Their Model. CoRR (2018)
Tyler Hunt, Congzheng Song, Reza Shokri, Vitaly Shmatikov, Emmett Witchel
Chiron: Privacy-preserving Machine Learning as a Service. CoRR (2018)
Congzheng Song, Vitaly Shmatikov
Fooling OCR Systems with Adversarial Text Images. CoRR (2018)
Congzheng Song, Yiming Sun
Kernel Distillation for Gaussian Processes. CoRR (2018)
Luca Melis, Congzheng Song, Emiliano De Cristofaro, Vitaly Shmatikov
Inference Attacks Against Collaborative Learning. CoRR (2018)
Congzheng Song, Thomas Ristenpart, Vitaly Shmatikov
Machine Learning Models that Remember Too Much. CCS (2017)
Congzheng Song, Thomas Ristenpart, Vitaly Shmatikov
Machine Learning Models that Remember Too Much. CoRR (2017)
Reza Shokri, Marco Stronati, Congzheng Song, Vitaly Shmatikov
Membership Inference Attacks Against Machine Learning Models. IEEE Symposium on Security and Privacy (2017)
Safoora Yousefi, Congzheng Song, Nelson Nauata, Lee Cooper
Learning Genomic Representations to Predict Clinical Outcomes in Cancer. CoRR (2016)