Shuang Song - RankMe

48 papers A* 10A 4Journal 27Unranked 6

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Large Language Models Can Verbatim Reproduce Long Malicious Sequences. CoRR Sharon Lin, Krishnamurthy Dvijotham, Jamie Hayes, Chongyang Shi, Ilia Shumailov, Shuang Song
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	J	`jnl`	Recycling Scraps: Improving Private Learning by Leveraging Checkpoints]{Recycling Scraps: Improving Private Learning by Leveraging Checkpoints. Proc. Priv. Enhancing Technol. Virat Shejwalkar, Arun Ganesh, Rajiv Mathews, Yarong Mu, Shuang Song, Om Thakkar, Abhradeep Thakurta, Xinyi Zheng
2025	J	`jnl`	The Attacker Moves Second: Stronger Adaptive Attacks Bypass Defenses Against Llm Jailbreaks and Prompt Injections. CoRR Milad Nasr, Nicholas Carlini, Chawin Sitawarin, Sander V. Schulhoff, Jamie Hayes, Michael Ilie, Juliette Pluto, Shuang Song, Harsh Chaudhari, Ilia Shumailov, Abhradeep Thakurta, Kai Yuanqing Xiao, Andreas Terzis, Florian Tramèr
2024	A	`conf`	Private Learning with Public Features. AISTATS Walid Krichene, Nicolas Mayoraz, Steffen Rendle, Shuang Song, Abhradeep Thakurta, Li Zhang
2023	J	`jnl`	Challenges towards the Next Frontier in Privacy. CoRR Rachel Cummings, Damien Desfontaines, David Evans, Roxana Geambasu, Matthew Jagielski, Yangsibo Huang, Peter Kairouz, Gautam Kamath, Sewoong Oh, Olga Ohrimenko, Nicolas Papernot, Ryan Rogers, Milan Shen, Shuang Song, Weijie J. Su, Andreas Terzis, Abhradeep Thakurta, Sergei Vassilvitskii, Yu-Xiang Wang, Li Xiong, Sergey Yekhanin, Da Yu, Huanyu Zhang, Wanrong Zhang
2023	A*	`conf`	Measuring Forgetting of Memorized Training Examples. ICLR Matthew Jagielski, Om Thakkar, Florian Tramèr, Daphne Ippolito, Katherine Lee, Nicholas Carlini, Eric Wallace, Shuang Song, Abhradeep Guha Thakurta, Nicolas Papernot, Chiyuan Zhang
2023	A*	`conf`	Multi-Task Differential Privacy Under Distribution Skew. ICML Walid Krichene, Prateek Jain, Shuang Song, Mukund Sundararajan, Abhradeep Guha Thakurta, Li Zhang
2023	J	`jnl`	Multi-Task Differential Privacy Under Distribution Skew. CoRR Walid Krichene, Prateek Jain, Shuang Song, Mukund Sundararajan, Abhradeep Thakurta, Li Zhang
2023	J	`jnl`	Private Learning with Public Features. CoRR Walid Krichene, Nicolas Mayoraz, Steffen Rendle, Shuang Song, Abhradeep Thakurta, Li Zhang
2022	J	`jnl`	Debugging Differential Privacy: A Case Study for Privacy Auditing. CoRR Florian Tramèr, Andreas Terzis, Thomas Steinke, Shuang Song, Matthew Jagielski, Nicholas Carlini
2022	A	`conf`	EANA: Reducing Privacy Risk on Large-scale Recommendation Models. RecSys Lin Ning, Steve Chien, Shuang Song, Mei Chen, Yunqi Xue, Devora Berlowitz
2022	J	`jnl`	Measuring Forgetting of Memorized Training Examples. CoRR Matthew Jagielski, Om Thakkar, Florian Tramèr, Daphne Ippolito, Katherine Lee, Nicholas Carlini, Eric Wallace, Shuang Song, Abhradeep Thakurta, Nicolas Papernot, Chiyuan Zhang
2022	A*	`conf`	Membership Inference Attacks From First Principles. SP Nicholas Carlini, Steve Chien, Milad Nasr, Shuang Song, Andreas Terzis, Florian Tramèr
2022	A*	`conf`	Public Data-Assisted Mirror Descent for Private Model Training. ICML Ehsan Amid, Arun Ganesh, Rajiv Mathews, Swaroop Ramaswamy, Shuang Song, Thomas Steinke, Vinith M. Suriyakumar, Om Thakkar, Abhradeep Thakurta
2022	J	`jnl`	Toward Training at ImageNet Scale with Differential Privacy. CoRR Alexey Kurakin, Steve Chien, Shuang Song, Roxana Geambasu, Andreas Terzis, Abhradeep Thakurta
2021	A*	`conf`	Adversary Instantiation: Lower Bounds for Differentially Private Machine Learning. SP Milad Nasr, Shuang Song, Abhradeep Thakurta, Nicolas Papernot, Nicholas Carlini
2021	J	`jnl`	Adversary Instantiation: Lower Bounds for Differentially Private Machine Learning. CoRR Milad Nasr, Shuang Song, Abhradeep Thakurta, Nicolas Papernot, Nicholas Carlini
2021	A*	`conf`	Differentially Private Model Personalization. NeurIPS Prateek Jain, John Rush, Adam D. Smith, Shuang Song, Abhradeep Guha Thakurta
2021	A	`conf`	Evading the Curse of Dimensionality in Unconstrained Private GLMs. AISTATS Shuang Song, Thomas Steinke, Om Thakkar, Abhradeep Thakurta
2021	J	`jnl`	Membership Inference Attacks From First Principles. CoRR Nicholas Carlini, Steve Chien, Milad Nasr, Shuang Song, Andreas Terzis, Florian Tramèr
2021	A*	`conf`	Practical and Private (Deep) Learning Without Sampling or Shuffling. ICML Peter Kairouz, Brendan McMahan, Shuang Song, Om Thakkar, Abhradeep Thakurta, Zheng Xu
2021	J	`jnl`	Practical and Private (Deep) Learning without Sampling or Shuffling. CoRR Peter Kairouz, Brendan McMahan, Shuang Song, Om Thakkar, Abhradeep Thakurta, Zheng Xu
2021	A*	`conf`	Private Alternating Least Squares: Practical Private Matrix Completion with Tighter Rates. ICML Steve Chien, Prateek Jain, Walid Krichene, Steffen Rendle, Shuang Song, Abhradeep Thakurta, Li Zhang
2021	J	`jnl`	Private Alternating Least Squares: Practical Private Matrix Completion with Tighter Rates. CoRR Steve Chien, Prateek Jain, Walid Krichene, Steffen Rendle, Shuang Song, Abhradeep Thakurta, Li Zhang
2021	J	`jnl`	Public Data-Assisted Mirror Descent for Private Model Training. CoRR Ehsan Amid, Arun Ganesh, Rajiv Mathews, Swaroop Ramaswamy, Shuang Song, Thomas Steinke, Vinith M. Suriyakumar, Om Thakkar, Abhradeep Thakurta
2021	A*	`conf`	Tempered Sigmoid Activations for Deep Learning with Differential Privacy. AAAI Nicolas Papernot, Abhradeep Thakurta, Shuang Song, Steve Chien, Úlfar Erlingsson
2020	J	`jnl`	An Attack on InstaHide: Is Private Learning Possible with Instance Encoding? CoRR Nicholas Carlini, Samuel Deng, Sanjam Garg, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody, Shuang Song, Abhradeep Thakurta, Florian Tramèr
2020	J	`jnl`	Characterizing Private Clipped Gradient Descent on Convex Generalized Linear Problems. CoRR Shuang Song, Om Thakkar, Abhradeep Thakurta
2020	J	`jnl`	Encode, Shuffle, Analyze Privacy Revisited: Formalizations and Empirical Evaluation. CoRR Úlfar Erlingsson, Vitaly Feldman, Ilya Mironov, Ananth Raghunathan, Shuang Song, Kunal Talwar, Abhradeep Thakurta
2020	J	`jnl`	Tempered Sigmoid Activations for Deep Learning with Differential Privacy. CoRR Nicolas Papernot, Abhradeep Thakurta, Shuang Song, Steve Chien, Úlfar Erlingsson
2020	A*	`conf`	The Flajolet-Martin Sketch Itself Preserves Differential Privacy: Private Counting with Minimal Space. NeurIPS Adam D. Smith, Shuang Song, Abhradeep Thakurta
2019	J	`jnl`	That which we call private. CoRR Úlfar Erlingsson, Ilya Mironov, Ananth Raghunathan, Shuang Song
2018	J	`jnl`	Differentially Private Continual Release of Graph Statistics. CoRR Shuang Song, Susan Little, Sanjay Mehta, Staal Amund Vinterbo, Kamalika Chaudhuri
2018	—	`—`	Privacy-Preserving Algorithms for Machine Learning. Shuang Song
2018	—	`conf`	Scalable Private Learning with PATE. ICLR Nicolas Papernot, Shuang Song, Ilya Mironov, Ananth Raghunathan, Kunal Talwar, Úlfar Erlingsson
2018	J	`jnl`	Scalable Private Learning with PATE. CoRR Nicolas Papernot, Shuang Song, Ilya Mironov, Ananth Raghunathan, Kunal Talwar, Úlfar Erlingsson
2017	J	`jnl`	Composition Properties of Inferential Privacy for Time-Series Data. CoRR Shuang Song, Kamalika Chaudhuri
2017	—	`conf`	Composition properties of inferential privacy for time-series data. Allerton Shuang Song, Kamalika Chaudhuri
2017	—	`conf`	Pufferfish Privacy Mechanisms for Correlated Data. SIGMOD Conference Shuang Song, Yizhen Wang, Kamalika Chaudhuri
2017	—	`conf`	Renyi Differential Privacy Mechanisms for Posterior Sampling. NIPS Joseph Geumlek, Shuang Song, Kamalika Chaudhuri
2017	J	`jnl`	Rényi Differential Privacy Mechanisms for Posterior Sampling. CoRR Joseph Geumlek, Shuang Song, Kamalika Chaudhuri
2016	J	`jnl`	Privacy-preserving Analysis of Correlated Data. CoRR Yizhen Wang, Shuang Song, Kamalika Chaudhuri
2015	A	`conf`	Learning from Data with Heterogeneous Noise using SGD. AISTATS Shuang Song, Kamalika Chaudhuri, Anand D. Sarwate
2014	J	`jnl`	Learning from Data with Heterogeneous Noise using SGD. CoRR Shuang Song, Kamalika Chaudhuri, Anand D. Sarwate
2014	—	`conf`	The Large Margin Mechanism for Differentially Private Maximization. NIPS Kamalika Chaudhuri, Daniel J. Hsu, Shuang Song
2014	J	`jnl`	The Large Margin Mechanism for Differentially Private Maximization. CoRR Kamalika Chaudhuri, Daniel J. Hsu, Shuang Song
2013	—	`conf`	Stochastic gradient descent with differentially private updates. GlobalSIP Shuang Song, Kamalika Chaudhuri, Anand D. Sarwate