Search Results for author:
Found 7 papers, 4 papers with code
Federated Pruning: Improving Neural Network Efficiency with Federated Learning
Automatic Speech Recognition models require large amount of speech data for training, and the collection of such data often leads to privacy concerns.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Online Model Compression for Federated Learning with Large Models
This paper addresses the challenges of training large neural network models under federated learning settings: high on-device memory usage and communication cost.
Enabling On-Device Training of Speech Recognition Models with Federated Dropout
Federated learning can be used to train machine learning models on the edge on local data that never leave devices, providing privacy by default.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
PGLP: Customizable and Rigorous Location Privacy through Policy Graph
Third, we design a private location trace release framework that pipelines the detection of location exposure, policy graph repair, and private trajectory release with customizable and rigorous location privacy.
Cryptography and Security Computers and Society
PANDA: Policy-aware Location Privacy for Epidemic Surveillance
Our system has three primary functions for epidemic surveillance: location monitoring, epidemic analysis, and contact tracing.
Databases Cryptography and Security
Quantifying Differential Privacy in Continuous Data Release under Temporal Correlations
Our analysis reveals that, the event-level privacy loss of a DP mechanism may \textit{increase over time}.
Databases
Quantifying Differential Privacy under Temporal Correlations
Our analysis reveals that the privacy leakage of a DP mechanism may accumulate and increase over time.
Databases Cryptography and Security
