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Privacy Preserving

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Showing 2501–2550 of 2975 papers

TitleStatusHype
Privacy-Preserving Object Detection & Localization Using Distributed Machine Learning: A Case Study of Infant Eyeblink ConditioningCode0
S3ML: A Secure Serving System for Machine Learning Inference—0
Chasing Your Long Tails: Differentially Private Prediction in Health Care Settings—0
Differentially Private Secure Multi-Party Computation for Federated Learning in Financial Applications—0
A Unified Framework for Generic, Query-Focused, Privacy Preserving and Update Summarization using Submodular Information Measures—0
Data-driven Regularized Inference Privacy—0
Bias and Variance of Post-processing in Differential Privacy—0
Latent Dirichlet Allocation Model Training with Differential Privacy—0
Differentially Private Deep Learning with Direct Feedback Alignment—0
Correlated Differential Privacy: Feature Selection in Machine Learning—0
PCAL: A Privacy-preserving Intelligent Credit Risk Modeling Framework Based on Adversarial Learning—0
Toward Privacy and Utility Preserving Image Representation—0
Oblivious Sampling Algorithms for Private Data Analysis—0
Privacy-Preserving Dynamic Personalized Pricing with Demand Learning—0
Machine Learning Algorithms for Active Monitoring of High Performance Computing as a Service (HPCaaS) Cloud Environments—0
Resource-Constrained On-Device Learning by Dynamic Averaging—0
Privacy-Preserving Push-sum Average Consensus via State Decomposition—0
Privacy-preserving Transfer Learning via Secure Maximum Mean Discrepancy—0
FastSecAgg: Scalable Secure Aggregation for Privacy-Preserving Federated Learning—0
Dynamic Fusion based Federated Learning for COVID-19 Detection—0
Privacy Preserving K-Means Clustering: A Secure Multi-Party Computation Approach—0
Beyond Identity: What Information Is Stored in Biometric Face Templates?—0
Epidemic mitigation by statistical inference from contact tracing data—0
Subverting Privacy-Preserving GANs: Hiding Secrets in Sanitized Images—0
Adversarial Robustness through Bias Variance Decomposition: A New Perspective for Federated Learning—0
Private Reinforcement Learning with PAC and Regret Guarantees—0
The Capacity of Multi-user Private Information Retrieval for Computationally Limited Databases—0
FedSmart: An Auto Updating Federated Learning Optimization Mechanism—0
Differentially Private Language Models Benefit from Public Pre-training—0
Privacy-Preserving Dynamic Average Consensus via State Decomposition: Case Study on Multi-Robot Formation Control—0
Privacy-Preserving Machine Learning in Untrusted Clouds Made Simple—0
Hybrid Differentially Private Federated Learning on Vertically Partitioned Data—0
Blockchain-based Federated Learning for Failure Detection in Industrial IoT—0
FLFE: A Communication-Efficient and Privacy-Preserving Federated Feature Engineering Framework—0
ESMFL: Efficient and Secure Models for Federated Learning—0
Fairness in the Eyes of the Data: Certifying Machine-Learning Models—0
Private Weighted Random Walk Stochastic Gradient Descent—0
Differentially private k-means clustering via exponential mechanism and max cover—0
POSEIDON: Privacy-Preserving Federated Neural Network Learning—0
Privacy-Preserving Distributed Zeroth-Order Optimization—0
Deconvoluting Kernel Density Estimation and Regression for Locally Differentially Private Data—0
Every Query Counts: Analyzing the Privacy Loss of Exploratory Data Analyses—0
GuardNN: Secure Accelerator Architecture for Privacy-Preserving Deep Learning—0
In-Home Daily-Life Captioning Using Radio Signals—0
A Federated Multi-View Deep Learning Framework for Privacy-Preserving Recommendations—0
Precision Health Data: Requirements, Challenges and Existing Techniques for Data Security and Privacy—0
Multiple Classification with Split Learning—0
An Efficient Privacy-Preserving Multi-Keyword Query Scheme in Location Based Services—0
Privacy Preserving Recalibration under Domain Shift—0
Shared MF: A privacy-preserving recommendation system—0
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