High Dimensional Differentially Private Stochastic Optimization with Heavy-tailed Data

High Dimensional Differentially Private Stochastic Optimization with Heavy-tailed Data

Bibliographic Details
Main Authors:	Hu, Lijie, Ni, Shuo, Xiao, Hanshen, Wang, Di
Other Authors:	Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Format:	Article
Language:	English
Published:	ACM\|Proceedings of the 41st ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems 2022
Online Access:	https://hdl.handle.net/1721.1/146475

Similar Items

Local differential privacy in decentralized optimization
by: Xiao, Hanshen.
Published: (2020)

When Idling is Ideal: Optimizing Tail-Latency for Heavy-Tailed Datacenter Workloads with Perséphone
by: Demoulin, Henri, et al.
Published: (2022)

Throughput Optimal Scheduling in the Presence of Heavy-Tailed Traffic
by: Jagannathan, Krishna Prasanna, et al.
Published: (2011)

Geometry of Sensitivity: Twice Sampling and Hybrid Clipping in Differential Privacy with Optimal Gaussian Noise and Application to Deep Learning
by: Xiao, Hanshen, et al.
Published: (2023)

Heavy-Tailed Response of Structural Systems Subjected to Stochastic Excitation Containing Extreme Forcing Events
by: Joo, Han Kyul, et al.
Published: (2019)

Heavy tails in last-passage percolation
by: Hambly, B, et al.
Published: (2006)

Heavy tails in last passage percolation
by: Hambly, B, et al.
Published: (2005)

Heavy tails in last-passage percolation
by: Hambly, B, et al.
Published: (2007)

Optimal and Differentially Private Data Acquisition: Central and Local Mechanisms
by: Fallah, Alireza, et al.
Published: (2022)

Throughput Optimal Scheduling Over Time-Varying Channels in the Presence of Heavy-Tailed Traffic
by: Jagannathan, Krishna Prasanna, et al.
Published: (2015)

Scheduling in switched queueing networks with heavy-tailed trac
by: Markakis, Mihalis G
Published: (2013)

Central limit theorem for eigenvectors of heavy tailed matrices
by: Benaych-Georges, Florent, et al.
Published: (2014)

Max-weight scheduling in networks with heavy-tailed traffic
by: Markakis, Mihalis G., et al.
Published: (2017)

High-dimensional stochastic optimal control using continuous tensor decompositions
by: Gorodetsky, Alex Arkady, et al.
Published: (2019)

Robust recursive estimation of the state of a discrete-time stochastic linear dynamic system in the presence of heavy-tailed observation noise
by: Schick, Ä°rvin C. (Ä°rvin Cemil)
Published: (2005)

High-Dimensional Optimal Path Planning and Multi-Timescale Lagrangian Data Assimilation in Stochastic Dynamical Ocean Environments
by: Doshi, Manan
Published: (2024)

Rare Probability Estimation under Regularly Varying Heavy Tails
by: Ohannessian, Mesrob I., et al.
Published: (2015)

Corrections to the Central Limit Theorem for Heavy-tailed Probability Densities
by: Lam, Henry, et al.
Published: (2013)

Max-Weight Scheduling in Queueing Networks With Heavy-Tailed Traffic
by: Markakis, Michail, et al.
Published: (2018)

Scheduling policies for single-hop networks with heavy-tailed traffic
by: Modiano, Eytan H., et al.
Published: (2010)

Fair, Robust, and Calibrated Deep Learning with Heavy-Tailed Subgroups
by: Hampton, Lelia Marie
Published: (2023)

When a Heavy Tailed Service Minimizes Age of Information
by: Talak, Rajat, et al.
Published: (2021)

Robust recursive estimation in the presence of heavy-tailed observation noise
Published: (2003)

Max-Weight Scheduling in Queueing Networks With Heavy-Tailed Traffic
by: Markakis, Mihalis G., et al.
Published: (2014)

When a Heavy Tailed Service Minimizes Age of Information
by: Talak, Rajat Rajendra, et al.
Published: (2021)

Differentially private histogram publication
by: Xu, Jia, et al.
Published: (2013)

Optimal Differentially Private Learning of Thresholds and Quasi-Concave Optimization
by: Cohen, Edith, et al.
Published: (2023)

Differentially Private Outlier Detection in Correlated Data
by: Degue, Kwassi H, et al.
Published: (2022)

Framework of secret differential privacy on private data
by: Küçük, A, et al.
Published: (2017)

Modelling heavy-tailed insurance claim data using the hyper-erlang distribution with common scale parameter
by: Seet, Angeline Yuen Chee, et al.
Published: (2011)

Formal Privacy Proof of Data Encoding: The Possibility and Impossibility of Learnable Encryption
by: Xiao, Hanshen, et al.
Published: (2025)

Delay stability of back-pressure policies in the presence of heavy-tailed traffic
by: Markakis, Mihalis G., et al.
Published: (2015)

Central Limit Theorems for Linear Statistics of Heavy Tailed Random Matrices
by: Benaych-Georges, Florent, et al.
Published: (2015)

Surgical scheduling via optimization and machine learning with long-tailed data
by: Shi, Yuan, et al.
Published: (2023)

Integrability and tail estimates for Gaussian rough differential equations
by: Cass, T, et al.
Published: (2011)

Differentially private deep learning for time series data
by: Dwitami, Inggriany
Published: (2020)

Lightweight Techniques for Private Heavy Hitters
by: Boneh, Dan, et al.
Published: (2022)

Size-independent vs. size-dependent policies in scheduling heavy-tailed distributions
by: Nham, John (John T.)
Published: (2009)

Analysis of High Dimensional Multivariate Stochastic Volatility Models.
by: Chib, S, et al.
Published: (2006)

Analysis of high dimensional multivariate stochastic volatility models
by: Chib, S, et al.
Published: (2006)