Christopher A. Choquette-Choo

85 papers A* 28A 1B 2C 1Journal 50Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	IH-Challenge: A Training Dataset to Improve Instruction Hierarchy on Frontier LLMs. CoRR Chuan Guo, Juan Felipe Ceron Uribe, Sicheng Zhu, Christopher A. Choquette-Choo, Stephanie Lin, Nikhil Kandpal, Milad Nasr, Rai, Sam Toyer, Miles Wang, Yaodong Yu, Alex Beutel, Kai Xiao
2025	J	`jnl`	Correlated Noise Mechanisms for Differentially Private Learning. CoRR Krishna Pillutla, Jalaj Upadhyay, Christopher A. Choquette-Choo, Krishnamurthy Dvijotham, Arun Ganesh, Monika Henzinger, Jonathan Katz, Ryan McKenna, H. Brendan McMahan, Keith Rush, Thomas Steinke, Abhradeep Thakurta
2025	A*	`conf`	Efficient and Privacy-Preserving Soft Prompt Transfer for LLMs. ICML Xun Wang, Jing Xu, Franziska Boenisch, Michael Backes, Christopher A. Choquette-Choo, Adam Dziedzic
2025	J	`jnl`	Efficient and Privacy-Preserving Soft Prompt Transfer for LLMs. CoRR Xun Wang, Jing Xu, Franziska Boenisch, Michael Backes, Christopher A. Choquette-Choo, Adam Dziedzic
2025	A*	`conf`	Exploring and Mitigating Adversarial Manipulation of Voting-Based Leaderboards. ICML Yangsibo Huang, Milad Nasr, Anastasios Nikolas Angelopoulos, Nicholas Carlini, Wei-Lin Chiang, Christopher A. Choquette-Choo, Daphne Ippolito, Matthew Jagielski, Katherine Lee, Ken Liu, Ion Stoica, Florian Tramèr, Chiyuan Zhang
2025	J	`jnl`	Exploring and Mitigating Adversarial Manipulation of Voting-Based Leaderboards. CoRR Yangsibo Huang, Milad Nasr, Anastasios Angelopoulos, Nicholas Carlini, Wei-Lin Chiang, Christopher A. Choquette-Choo, Daphne Ippolito, Matthew Jagielski, Katherine Lee, Ken Ziyu Liu, Ion Stoica, Florian Tramèr, Chiyuan Zhang
2025	J	`jnl`	Extracting alignment data in open models. CoRR Federico Barbero, Xiangming Gu, Christopher A. Choquette-Choo, Chawin Sitawarin, Matthew Jagielski, Itay Yona, Petar Velickovic, Ilia Shumailov, Jamie Hayes
2025	J	`jnl`	LLMs unlock new paths to monetizing exploits. CoRR Nicholas Carlini, Milad Nasr, Edoardo Debenedetti, Barry Wang, Christopher A. Choquette-Choo, Daphne Ippolito, Florian Tramèr, Matthew Jagielski
2025	A*	`conf`	Language Models May Verbatim Complete Text They Were Not Explicitly Trained On. ICML Ken Liu, Christopher A. Choquette-Choo, Matthew Jagielski, Peter Kairouz, Sanmi Koyejo, Percy Liang, Nicolas Papernot
2025	J	`jnl`	Language Models May Verbatim Complete Text They Were Not Explicitly Trained On. CoRR Ken Ziyu Liu, Christopher A. Choquette-Choo, Matthew Jagielski, Peter Kairouz, Sanmi Koyejo, Percy Liang, Nicolas Papernot
2025	J	`jnl`	Lessons from Defending Gemini Against Indirect Prompt Injections. CoRR Chongyang Shi, Sharon Lin, Shuang Song, Jamie Hayes, Ilia Shumailov, Itay Yona, Juliette Pluto, Aneesh Pappu, Christopher A. Choquette-Choo, Milad Nasr, Chawin Sitawarin, Gena Gibson, Andreas Terzis, John Flynn
2025	—	`conf`	Measuring memorization in language models via probabilistic extraction. NAACL (Long Papers) Jamie Hayes, Marika Swanberg, Harsh Chaudhari, Itay Yona, Ilia Shumailov, Milad Nasr, Christopher A. Choquette-Choo, Katherine Lee, A. Feder Cooper
2025	A*	`conf`	Near-Exact Privacy Amplification for Matrix Mechanisms. ICLR Christopher A. Choquette-Choo, Arun Ganesh, Saminul Haque, Thomas Steinke, Abhradeep Guha Thakurta
2025	B	`conf`	Near-Optimal Rates for O(1)-Smooth DP-SCO with a Single Epoch and Large Batches. ALT Christopher A. Choquette-Choo, Arun Ganesh, Abhradeep Guha Thakurta
2025	A*	`conf`	Privacy Auditing of Large Language Models. ICLR Ashwinee Panda, Xinyu Tang, Christopher A. Choquette-Choo, Milad Nasr, Prateek Mittal
2025	J	`jnl`	Privacy Auditing of Large Language Models. CoRR Ashwinee Panda, Xinyu Tang, Milad Nasr, Christopher A. Choquette-Choo, Prateek Mittal
2025	—	`conf`	Privacy Ripple Effects from Adding or Removing Personal Information in Language Model Training. ACL (Findings) Jaydeep Borkar, Matthew Jagielski, Katherine Lee, Niloofar Mireshghallah, David A. Smith, Christopher A. Choquette-Choo
2025	J	`jnl`	Privacy Ripple Effects from Adding or Removing Personal Information in Language Model Training. CoRR Jaydeep Borkar, Matthew Jagielski, Katherine Lee, Niloofar Mireshghallah, David A. Smith, Christopher A. Choquette-Choo
2025	A*	`conf`	Recite, Reconstruct, Recollect: Memorization in LMs as a Multifaceted Phenomenon. ICLR USVSN Sai Prashanth, Alvin Deng, Kyle O'Brien, Jyothir S. V, Mohammad Aflah Khan, Jaydeep Borkar, Christopher A. Choquette-Choo, Jacob Ray Fuehne, Stella Biderman, Tracy Ke, Katherine Lee, Naomi Saphra
2025	A*	`conf`	Scalable Extraction of Training Data from Aligned, Production Language Models. ICLR Milad Nasr, Javier Rando, Nicholas Carlini, Jonathan Hayase, Matthew Jagielski, A. Feder Cooper, Daphne Ippolito, Christopher A. Choquette-Choo, Florian Tramèr, Katherine Lee
2025	A*	`conf`	Scaling Laws for Differentially Private Language Models. ICML Ryan McKenna, Yangsibo Huang, Amer Sinha, Borja Balle, Zachary Charles, Christopher A. Choquette-Choo, Badih Ghazi, Georgios Kaissis, Ravi Kumar, Ruibo Liu, Da Yu, Chiyuan Zhang
2025	J	`jnl`	Scaling Laws for Differentially Private Language Models. CoRR Ryan McKenna, Yangsibo Huang, Amer Sinha, Borja Balle, Zachary Charles, Christopher A. Choquette-Choo, Badih Ghazi, Georgios Kaissis, Ravi Kumar, Ruibo Liu, Da Yu, Chiyuan Zhang
2025	J	`jnl`	Strong Membership Inference Attacks on Massive Datasets and (Moderately) Large Language Models. CoRR Jamie Hayes, Ilia Shumailov, Christopher A. Choquette-Choo, Matthew Jagielski, Georgios Kaissis, Katherine Lee, Milad Nasr, Sahra Ghalebikesabi, Niloofar Mireshghallah, Meenatchi Sundaram Mutu Selva Annamalai, Igor Shilov, Matthieu Meeus, Yves-Alexandre de Montjoye, Franziska Boenisch, Adam Dziedzic, A. Feder Cooper
2025	A*	`conf`	The Last Iterate Advantage: Empirical Auditing and Principled Heuristic Analysis of Differentially Private SGD. ICLR Milad Nasr, Thomas Steinke, Borja Balle, Christopher A. Choquette-Choo, Arun Ganesh, Matthew Jagielski, Jamie Hayes, Abhradeep Guha Thakurta, Adam Smith, Andreas Terzis
2025	J	`jnl`	VaultGemma: A Differentially Private Gemma Model. CoRR Amer Sinha, Thomas Mesnard, Ryan McKenna, Daogao Liu, Christopher A. Choquette-Choo, Yangsibo Huang, Da Yu, Georgios Kaissis, Zachary Charles, Ruibo Liu, Lynn Chua, Pritish Kamath, Pasin Manurangsi, Steve He, Chiyuan Zhang, Badih Ghazi, Borja de Balle Pigem, Prem Eruvbetine, Tris Warkentin, Armand Joulin, Ravi Kumar
2024	A*	`conf`	Auditing Private Prediction. ICML Karan Chadha, Matthew Jagielski, Nicolas Papernot, Christopher A. Choquette-Choo, Milad Nasr
2024	J	`jnl`	Auditing Private Prediction. CoRR Karan Chadha, Matthew Jagielski, Nicolas Papernot, Christopher A. Choquette-Choo, Milad Nasr
2024	J	`jnl`	CodeGemma: Open Code Models Based on Gemma. CoRR Heri Zhao, Jeffrey Hui, Joshua Howland, Nam Nguyen, Siqi Zuo, Andrea Hu, Christopher A. Choquette-Choo, Jingyue Shen, Joe Kelley, Kshitij Bansal, Luke Vilnis, Mateo Wirth, Paul Michel, Peter Choy, Pratik Joshi, Ravin Kumar, Sarmad Hashmi, Shubham Agrawal, Zhitao Gong, Jane Fine, Tris Warkentin, Ale Jakse Hartman, Bin Ni, Kathy Korevec, Kelly Schaefer, Scott Huffman
2024	A*	`conf`	Correlated Noise Provably Beats Independent Noise for Differentially Private Learning. ICLR Christopher A. Choquette-Choo, Krishnamurthy Dj Dvijotham, Krishna Pillutla, Arun Ganesh, Thomas Steinke, Abhradeep Guha Thakurta
2024	J	`jnl`	Machine Unlearning Doesn't Do What You Think: Lessons for Generative AI Policy, Research, and Practice. CoRR A. Feder Cooper, Christopher A. Choquette-Choo, Miranda Bogen, Matthew Jagielski, Katja Filippova, Ken Ziyu Liu, Alexandra Chouldechova, Jamie Hayes, Yangsibo Huang, Niloofar Mireshghallah, Ilia Shumailov, Eleni Triantafillou, Peter Kairouz, Nicole Mitchell, Percy Liang, Daniel E. Ho, Yejin Choi, Sanmi Koyejo, Fernando A. Delgado, James Grimmelmann, Vitaly Shmatikov, Christopher De Sa, Solon Barocas, Amy Cyphert, Mark A. Lemley, danah boyd, Jennifer Wortman Vaughan, Miles Brundage, David Bau, Seth Neel, Abigail Z. Jacobs, Andreas Terzis, Hanna M. Wallach, Nicolas Papernot, Katherine Lee
2024	J	`jnl`	Near Exact Privacy Amplification for Matrix Mechanisms. CoRR Christopher A. Choquette-Choo, Arun Ganesh, Saminul Haque, Thomas Steinke, Abhradeep Thakurta
2024	J	`jnl`	Optimal Rates for DP-SCO with a Single Epoch and Large Batches. CoRR Christopher A. Choquette-Choo, Arun Ganesh, Abhradeep Thakurta
2024	J	`jnl`	Phantom: General Trigger Attacks on Retrieval Augmented Language Generation. CoRR Harsh Chaudhari, Giorgio Severi, John Abascal, Matthew Jagielski, Christopher A. Choquette-Choo, Milad Nasr, Cristina Nita-Rotaru, Alina Oprea
2024	A*	`conf`	Poisoning Web-Scale Training Datasets is Practical. SP Nicholas Carlini, Matthew Jagielski, Christopher A. Choquette-Choo, Daniel Paleka, Will Pearce, Hyrum S. Anderson, Andreas Terzis, Kurt Thomas, Florian Tramèr
2024	A*	`conf`	Privacy Amplification for Matrix Mechanisms. ICLR Christopher A. Choquette-Choo, Arun Ganesh, Thomas Steinke, Abhradeep Guha Thakurta
2024	A*	`conf`	Privacy Side Channels in Machine Learning Systems. USENIX Security Symposium Edoardo Debenedetti, Giorgio Severi, Milad Nasr, Christopher A. Choquette-Choo, Matthew Jagielski, Eric Wallace, Nicholas Carlini, Florian Tramèr
2024	J	`jnl`	Recite, Reconstruct, Recollect: Memorization in LMs as a Multifaceted Phenomenon. CoRR USVSN Sai Prashanth, Alvin Deng, Kyle O'Brien, Jyothir S. V, Mohammad Aflah Khan, Jaydeep Borkar, Christopher A. Choquette-Choo, Jacob Ray Fuehne, Stella Biderman, Tracy Ke, Katherine Lee, Naomi Saphra
2024	A*	`conf`	Teach LLMs to Phish: Stealing Private Information from Language Models. ICLR Ashwinee Panda, Christopher A. Choquette-Choo, Zhengming Zhang, Yaoqing Yang, Prateek Mittal
2024	J	`jnl`	Teach LLMs to Phish: Stealing Private Information from Language Models. CoRR Ashwinee Panda, Christopher A. Choquette-Choo, Zhengming Zhang, Yaoqing Yang, Prateek Mittal
2024	J	`jnl`	The Last Iterate Advantage: Empirical Auditing and Principled Heuristic Analysis of Differentially Private SGD. CoRR Thomas Steinke, Milad Nasr, Arun Ganesh, Borja Balle, Christopher A. Choquette-Choo, Matthew Jagielski, Jamie Hayes, Abhradeep Guha Thakurta, Adam Smith, Andreas Terzis
2024	A*	`conf`	User Inference Attacks on Large Language Models. EMNLP Nikhil Kandpal, Krishna Pillutla, Alina Oprea, Peter Kairouz, Christopher A. Choquette-Choo, Zheng Xu
2023	A*	`conf`	(Amplified) Banded Matrix Factorization: A unified approach to private training. NeurIPS Christopher A. Choquette-Choo, Arun Ganesh, Ryan McKenna, H. Brendan McMahan, John Rush, Abhradeep Guha Thakurta, Zheng Xu
2023	J	`jnl`	(Amplified) Banded Matrix Factorization: A unified approach to private training. CoRR Christopher A. Choquette-Choo, Arun Ganesh, Ryan McKenna, H. Brendan McMahan, Keith Rush, Abhradeep Guha Thakurta, Zheng Xu
2023	A*	`conf`	Are aligned neural networks adversarially aligned? NeurIPS Nicholas Carlini, Milad Nasr, Christopher A. Choquette-Choo, Matthew Jagielski, Irena Gao, Pang Wei Koh, Daphne Ippolito, Florian Tramèr, Ludwig Schmidt
2023	J	`jnl`	Are aligned neural networks adversarially aligned? CoRR Nicholas Carlini, Milad Nasr, Christopher A. Choquette-Choo, Matthew Jagielski, Irena Gao, Anas Awadalla, Pang Wei Koh, Daphne Ippolito, Katherine Lee, Florian Tramèr, Ludwig Schmidt
2023	J	`jnl`	Correlated Noise Provably Beats Independent Noise for Differentially Private Learning. CoRR Christopher A. Choquette-Choo, Krishnamurthy Dvijotham, Krishna Pillutla, Arun Ganesh, Thomas Steinke, Abhradeep Thakurta
2023	—	`conf`	Federated Learning of Gboard Language Models with Differential Privacy. ACL (industry) Zheng Xu, Yanxiang Zhang, Galen Andrew, Christopher A. Choquette-Choo, Peter Kairouz, H. Brendan McMahan, Jesse Rosenstock, Yuanbo Zhang
2023	J	`jnl`	Federated Learning of Gboard Language Models with Differential Privacy. CoRR Zheng Xu, Yanxiang Zhang, Galen Andrew, Christopher A. Choquette-Choo, Peter Kairouz, H. Brendan McMahan, Jesse Rosenstock, Yuanbo Zhang
2023	J	`jnl`	MADLAD-400: A Multilingual And Document-Level Large Audited Dataset. CoRR Sneha Kudugunta, Isaac Caswell, Biao Zhang, Xavier Garcia, Christopher A. Choquette-Choo, Katherine Lee, Derrick Xin, Aditya Kusupati, Romi Stella, Ankur Bapna, Orhan Firat
2023	A*	`conf`	Multi-Epoch Matrix Factorization Mechanisms for Private Machine Learning. ICML Christopher A. Choquette-Choo, Hugh Brendan McMahan, J. Keith Rush, Abhradeep Guha Thakurta
2023	J	`jnl`	PaLM 2 Technical Report. CoRR Rohan Anil, Andrew M. Dai, Orhan Firat, Melvin Johnson, Dmitry Lepikhin, Alexandre Passos, Siamak Shakeri, Emanuel Taropa, Paige Bailey, Zhifeng Chen, Eric Chu, Jonathan H. Clark, Laurent El Shafey, Yanping Huang, Kathy Meier-Hellstern, Gaurav Mishra, Erica Moreira, Mark Omernick, Kevin Robinson, Sebastian Ruder, Yi Tay, Kefan Xiao, Yuanzhong Xu, Yujing Zhang, Gustavo Hernández Ábrego, Junwhan Ahn, Jacob Austin, Paul Barham, Jan A. Botha, James Bradbury, Siddhartha Brahma, Kevin Brooks, Michele Catasta, Yong Cheng, Colin Cherry, Christopher A. Choquette-Choo, Aakanksha Chowdhery, Clément Crepy, Shachi Dave, Mostafa Dehghani, Sunipa Dev, Jacob Devlin, Mark Díaz, Nan Du, Ethan Dyer, Vladimir Feinberg, Fangxiaoyu Feng, Vlad Fienber, Markus Freitag, Xavier Garcia, Sebastian Gehrmann, Lucas Gonzalez, et al.
2023	J	`jnl`	Poisoning Web-Scale Training Datasets is Practical. CoRR Nicholas Carlini, Matthew Jagielski, Christopher A. Choquette-Choo, Daniel Paleka, Will Pearce, Hyrum S. Anderson, Andreas Terzis, Kurt Thomas, Florian Tramèr
2023	B	`conf`	Preventing Generation of Verbatim Memorization in Language Models Gives a False Sense of Privacy. INLG Daphne Ippolito, Florian Tramèr, Milad Nasr, Chiyuan Zhang, Matthew Jagielski, Katherine Lee, Christopher A. Choquette-Choo, Nicholas Carlini
2023	J	`jnl`	Privacy Amplification for Matrix Mechanisms. CoRR Christopher A. Choquette-Choo, Arun Ganesh, Thomas Steinke, Abhradeep Thakurta
2023	J	`jnl`	Privacy Side Channels in Machine Learning Systems. CoRR Edoardo Debenedetti, Giorgio Severi, Nicholas Carlini, Christopher A. Choquette-Choo, Matthew Jagielski, Milad Nasr, Eric Wallace, Florian Tramèr
2023	A*	`conf`	Private Federated Learning with Autotuned Compression. ICML Enayat Ullah, Christopher A. Choquette-Choo, Peter Kairouz, Sewoong Oh
2023	J	`jnl`	Private Federated Learning with Autotuned Compression. CoRR Enayat Ullah, Christopher A. Choquette-Choo, Peter Kairouz, Sewoong Oh
2023	J	`jnl`	Private Multi-Winner Voting for Machine Learning. Proc. Priv. Enhancing Technol. Adam Dziedzic, Christopher A. Choquette-Choo, Natalie Dullerud, Vinith M. Suriyakumar, Ali Shahin Shamsabadi, Muhammad Ahmad Kaleem, Somesh Jha, Nicolas Papernot, Xiao Wang
2023	A	`conf`	Proof-of-Learning is Currently More Broken Than You Think. EuroS&P Congyu Fang, Hengrui Jia, Anvith Thudi, Mohammad Yaghini, Christopher A. Choquette-Choo, Natalie Dullerud, Varun Chandrasekaran, Nicolas Papernot
2023	J	`jnl`	Report of the 1st Workshop on Generative AI and Law. CoRR A. Feder Cooper, Katherine Lee, James Grimmelmann, Daphne Ippolito, Christopher Callison-Burch, Christopher A. Choquette-Choo, Niloofar Mireshghallah, Miles Brundage, David Mimno, Madiha Zahrah Choksi, Jack M. Balkin, Nicholas Carlini, Christopher De Sa, Jonathan Frankle, Deep Ganguli, Bryant Gipson, Andres Guadamuz, Swee Leng Harris, Abigail Z. Jacobs, Elizabeth Joh, Gautam Kamath, Mark A. Lemley, Cass Matthews, Christine McLeavey, Corynne McSherry, Milad Nasr, Paul Ohm, Adam Roberts, Tom Rubin, Pamela Samuelson, Ludwig Schubert, Kristen Vaccaro, Luis Villa, Felix Wu, Elana Zeide
2023	A*	`conf`	Robust and Actively Secure Serverless Collaborative Learning. NeurIPS Nicholas Franzese, Adam Dziedzic, Christopher A. Choquette-Choo, Mark R. Thomas, Muhammad Ahmad Kaleem, Stephan Rabanser, Congyu Fang, Somesh Jha, Nicolas Papernot, Xiao Wang
2023	J	`jnl`	Robust and Actively Secure Serverless Collaborative Learning. CoRR Olive Franzese, Adam Dziedzic, Christopher A. Choquette-Choo, Mark R. Thomas, Muhammad Ahmad Kaleem, Stephan Rabanser, Congyu Fang, Somesh Jha, Nicolas Papernot, Xiao Wang
2023	J	`jnl`	Scalable Extraction of Training Data from (Production) Language Models. CoRR Milad Nasr, Nicholas Carlini, Jonathan Hayase, Matthew Jagielski, A. Feder Cooper, Daphne Ippolito, Christopher A. Choquette-Choo, Eric Wallace, Florian Tramèr, Katherine Lee
2023	A*	`conf`	Students Parrot Their Teachers: Membership Inference on Model Distillation. NeurIPS Matthew Jagielski, Milad Nasr, Katherine Lee, Christopher A. Choquette-Choo, Nicholas Carlini, Florian Tramèr
2023	J	`jnl`	Students Parrot Their Teachers: Membership Inference on Model Distillation. CoRR Matthew Jagielski, Milad Nasr, Christopher A. Choquette-Choo, Katherine Lee, Nicholas Carlini
2023	J	`jnl`	User Inference Attacks on Large Language Models. CoRR Nikhil Kandpal, Krishna Pillutla, Alina Oprea, Peter Kairouz, Christopher A. Choquette-Choo, Zheng Xu
2022	J	`jnl`	Fine-Tuning with Differential Privacy Necessitates an Additional Hyperparameter Search. CoRR Yannis Cattan, Christopher A. Choquette-Choo, Nicolas Papernot, Abhradeep Thakurta
2022	J	`jnl`	Multi-Epoch Matrix Factorization Mechanisms for Private Machine Learning. CoRR Christopher A. Choquette-Choo, H. Brendan McMahan, Keith Rush, Abhradeep Thakurta
2022	J	`jnl`	On the Fundamental Limits of Formally (Dis)Proving Robustness in Proof-of-Learning. CoRR Congyu Fang, Hengrui Jia, Anvith Thudi, Mohammad Yaghini, Christopher A. Choquette-Choo, Natalie Dullerud, Varun Chandrasekaran, Nicolas Papernot
2022	J	`jnl`	Preventing Verbatim Memorization in Language Models Gives a False Sense of Privacy. CoRR Daphne Ippolito, Florian Tramèr, Milad Nasr, Chiyuan Zhang, Matthew Jagielski, Katherine Lee, Christopher A. Choquette-Choo, Nicholas Carlini
2022	J	`jnl`	Private Multi-Winner Voting for Machine Learning. CoRR Adam Dziedzic, Christopher A. Choquette-Choo, Natalie Dullerud, Vinith Menon Suriyakumar, Ali Shahin Shamsabadi, Muhammad Ahmad Kaleem, Somesh Jha, Nicolas Papernot, Xiao Wang
2022	A*	`conf`	The Fundamental Price of Secure Aggregation in Differentially Private Federated Learning. ICML Wei-Ning Chen, Christopher A. Choquette-Choo, Peter Kairouz, Ananda Theertha Suresh
2022	J	`jnl`	The Fundamental Price of Secure Aggregation in Differentially Private Federated Learning. CoRR Wei-Ning Chen, Christopher A. Choquette-Choo, Peter Kairouz, Ananda Theertha Suresh
2021	A*	`conf`	CaPC Learning: Confidential and Private Collaborative Learning. ICLR Christopher A. Choquette-Choo, Natalie Dullerud, Adam Dziedzic, Yunxiang Zhang, Somesh Jha, Nicolas Papernot, Xiao Wang
2021	J	`jnl`	CaPC Learning: Confidential and Private Collaborative Learning. CoRR Christopher A. Choquette-Choo, Natalie Dullerud, Adam Dziedzic, Yunxiang Zhang, Somesh Jha, Nicolas Papernot, Xiao Wang
2021	A*	`conf`	Entangled Watermarks as a Defense against Model Extraction. USENIX Security Symposium Hengrui Jia, Christopher A. Choquette-Choo, Varun Chandrasekaran, Nicolas Papernot
2021	A*	`conf`	Label-Only Membership Inference Attacks. ICML Christopher A. Choquette-Choo, Florian Tramèr, Nicholas Carlini, Nicolas Papernot
2021	A*	`conf`	Machine Unlearning. SP Lucas Bourtoule, Varun Chandrasekaran, Christopher A. Choquette-Choo, Hengrui Jia, Adelin Travers, Baiwu Zhang, David Lie, Nicolas Papernot
2021	A*	`conf`	Proof-of-Learning: Definitions and Practice. SP Hengrui Jia, Mohammad Yaghini, Christopher A. Choquette-Choo, Natalie Dullerud, Anvith Thudi, Varun Chandrasekaran, Nicolas Papernot
2021	J	`jnl`	Proof-of-Learning: Definitions and Practice. CoRR Hengrui Jia, Mohammad Yaghini, Christopher A. Choquette-Choo, Natalie Dullerud, Anvith Thudi, Varun Chandrasekaran, Nicolas Papernot
2020	J	`jnl`	Entangled Watermarks as a Defense against Model Extraction. CoRR Hengrui Jia, Christopher A. Choquette-Choo, Nicolas Papernot
2020	J	`jnl`	Label-Only Membership Inference Attacks. CoRR Christopher A. Choquette-Choo, Florian Tramèr, Nicholas Carlini, Nicolas Papernot
2019	C	`conf`	A Multi-label, Dual-Output Deep Neural Network for Automated Bug Triaging. ICMLA Christopher A. Choquette-Choo, David Sheldon, Jonny Proppe, John Alphonso-Gibbs, Harsha Gupta
2019	J	`jnl`	A multi-label, dual-output deep neural network for automated bug triaging. CoRR Christopher A. Choquette-Choo, David Sheldon, Jonny Proppe, John Alphonso-Gibbs, Harsha Gupta
2019	J	`jnl`	Machine Unlearning. CoRR Lucas Bourtoule, Varun Chandrasekaran, Christopher A. Choquette-Choo, Hengrui Jia, Adelin Travers, Baiwu Zhang, David Lie, Nicolas Papernot