25 Results

Poster
Tue 7:00 Fair Learning with Private Demographic Data
Hussein Mozannar, Mesrob Ohannessian, Nati Srebro
Poster
Tue 7:00 An end-to-end Differentially Private Latent Dirichlet Allocation Using a Spectral Algorithm
Chris DeCarolis, Mukul A Ram, Seyed Esmaeili, Yu-Xiang Wang, Furong Huang
Poster
Tue 7:00 Private Reinforcement Learning with PAC and Regret Guarantees
Giuseppe Vietri, Borja de Balle Pigem, Akshay Krishnamurthy, Steven Wu
Poster
Tue 7:00 Fast and Private Submodular and $k$-Submodular Functions Maximization with Matroid Constraints
Akbar Rafiey, Yuichi Yoshida
Poster
Tue 8:00 Oracle Efficient Private Non-Convex Optimization
Seth Neel, Aaron Roth, Giuseppe Vietri, Steven Wu
Poster
Tue 8:00 Differentially Private Set Union
Sivakanth Gopi, Pankaj Gulhane, Janardhan Kulkarni, Judy Hanwen Shen, Milad Shokouhi, Sergey Yekhanin
Poster
Tue 9:00 Context Aware Local Differential Privacy
Jayadev Acharya, Kallista Bonawitz, Peter Kairouz, Daniel Ramage, Ziteng Sun
Poster
Tue 10:00 Federated Learning with Only Positive Labels
Felix Xinnan Yu, Ankit Singh Rawat, Aditya Menon, Sanjiv Kumar
Poster
Tue 13:00 Bayesian Differential Privacy for Machine Learning
Aleksei Triastcyn, Boi Faltings
Poster
Wed 5:00 InstaHide: Instance-hiding Schemes for Private Distributed Learning
Yangsibo Huang, Zhao Song, Kai Li, Sanjeev Arora
Poster
Wed 5:00 Privately Learning Markov Random Fields
Huanyu Zhang, Gautam Kamath, Janardhan Kulkarni, Steven Wu
Poster
Wed 5:00 Private Query Release Assisted by Public Data
Raef Bassily, Albert Cheu, Shay Moran, Sasho Nikolov, Jonathan Ullman, Steven Wu
Poster
Wed 8:00 (Locally) Differentially Private Combinatorial Semi-Bandits
Xiaoyu Chen, Kai Zheng, Zixin(Jack) Zhou, Yunchang Yang, Wei Chen, Liwei Wang
Poster
Wed 8:00 Alleviating Privacy Attacks via Causal Learning
Shruti Tople, Amit Sharma, Aditya Nori
Poster
Wed 11:00 From Local SGD to Local Fixed-Point Methods for Federated Learning
Grigory Malinovsky, Dmitry Kovalev, Elnur Gasanov, Laurent CONDAT, Peter Richtarik
Poster
Wed 12:00 Scalable Differential Privacy with Certified Robustness in Adversarial Learning
Hai Phan, My T. Thai, Han Hu, Ruoming Jin, Tong Sun, Dejing Dou
Poster
Wed 12:00 Radioactive data: tracing through training
Alexandre Sablayrolles, Douze Matthijs, Cordelia Schmid, Herve Jegou
Poster
Wed 12:00 Private Counting from Anonymous Messages: Near-Optimal Accuracy with Vanishing Communication Overhead
Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Rasmus Pagh
Poster
Thu 6:00 Privately detecting changes in unknown distributions
Rachel Cummings, Sara Krehbiel, Yuliia Lut, Wanrong Zhang
Poster
Thu 6:00 Sharp Composition Bounds for Gaussian Differential Privacy via Edgeworth Expansion
Qinqing Zheng, Jinshuo Dong, Qi Long, Weijie Su
Poster
Thu 6:00 New Oracle-Efficient Algorithms for Private Synthetic Data Release
Giuseppe Vietri, Grace Tian, Mark Bun, Thomas Steinke, Steven Wu
Poster
Thu 7:00 Data-Dependent Differentially Private Parameter Learning for Directed Graphical Models
Amrita Roy Chowdhury, Theodoros Rekatsinas, Somesh Jha
Poster
Thu 7:00 On Differentially Private Stochastic Convex Optimization with Heavy-tailed Data
Di Wang, Hanshen Xiao, Srinivas Devadas, Jinhui Xu
Poster
Thu 7:00 Optimal Differential Privacy Composition for Exponential Mechanisms
Jinshuo Dong, David Durfee, Ryan Rogers
Poster
Thu 8:00 Certified Data Removal from Machine Learning Models
Chuan Guo, Tom Goldstein, Awni Hannun, Laurens van der Maaten