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Poster
Tue 7:00 Fast and Private Submodular and $k$-Submodular Functions Maximization with Matroid Constraints
Akbar Rafiey · Yuichi Yoshida
Poster
Tue 7:00 An end-to-end Differentially Private Latent Dirichlet Allocation Using a Spectral Algorithm
Christopher 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 Fair Learning with Private Demographic Data
Hussein Mozannar · Mesrob Ohannessian · Nati Srebro
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 Private Query Release Assisted by Public Data
Raef Bassily · Albert Cheu · Shay Moran · Aleksandar Nikolov · Jonathan Ullman · Steven Wu
Poster
Wed 5:00 Privately Learning Markov Random Fields
Huanyu Zhang · Gautam Kamath · Janardhan Kulkarni · Steven Wu
Poster
Wed 5:00 InstaHide: Instance-hiding Schemes for Private Distributed Learning
Yangsibo Huang · Zhao Song · Kai Li · Sanjeev Arora