Yingqi Liu | DeepAI

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∙ 05/24/2023

Towards More Suitable Personalization in Federated Learning via Decentralized Partial Model Training

Personalized federated learning (PFL) aims to produce the greatest perso...

0 Yifan Shi, et al. ∙

∙ 05/01/2023

Towards the Flatter Landscape and Better Generalization in Federated Learning under Client-level Differential Privacy

To defend the inference attacks and mitigate the sensitive information l...

3 Yifan Shi, et al. ∙

∙ 03/23/2023

Detecting Backdoors in Pre-trained Encoders

Self-supervised learning in computer vision trains on unlabeled data, su...

5 Shiwei Feng, et al. ∙

∙ 03/20/2023

Make Landscape Flatter in Differentially Private Federated Learning

To defend the inference attacks and mitigate the sensitive information l...

0 Yifan Shi, et al. ∙

∙ 01/16/2023

BEAGLE: Forensics of Deep Learning Backdoor Attack for Better Defense

Deep Learning backdoor attacks have a threat model similar to traditiona...

14 Siyuan Cheng, et al. ∙

∙ 11/29/2022

Backdoor Vulnerabilities in Normally Trained Deep Learning Models

We conduct a systematic study of backdoor vulnerabilities in normally tr...

16 Guanhong Tao, et al. ∙

∙ 10/23/2022

FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning

Federated Learning (FL) is a distributed learning paradigm that enables ...

1 Kaiyuan Zhang, et al. ∙

∙ 10/12/2022

Efficient Image Super-Resolution using Vast-Receptive-Field Attention

The attention mechanism plays a pivotal role in designing advanced super...

4 Lin Zhou, et al. ∙

∙ 08/16/2022

Traffic Analytics Development Kits (TADK): Enable Real-Time AI Inference in Networking Apps

Sophisticated traffic analytics, such as the encrypted traffic analytics...

0 Kun Qiu, et al. ∙

∙ 06/18/2022

DECK: Model Hardening for Defending Pervasive Backdoors

Pervasive backdoors are triggered by dynamic and pervasive input perturb...

7 Guanhong Tao, et al. ∙

∙ 05/12/2022

Blueprint Separable Residual Network for Efficient Image Super-Resolution

Recent advances in single image super-resolution (SISR) have achieved ex...

11 Zheyuan Li, et al. ∙

∙ 02/11/2022

Constrained Optimization with Dynamic Bound-scaling for Effective NLPBackdoor Defense

We develop a novel optimization method for NLPbackdoor inversion. We lev...

2 Guangyu Shen, et al. ∙

∙ 03/16/2021

EX-RAY: Distinguishing Injected Backdoor from Natural Features in Neural Networks by Examining Differential Feature Symmetry

Backdoor attack injects malicious behavior to models such that inputs em...

0 Yingqi Liu, et al. ∙

∙ 02/09/2021

Backdoor Scanning for Deep Neural Networks through K-Arm Optimization

Back-door attack poses a severe threat to deep learning systems. It inje...

0 Guangyu Shen, et al. ∙

∙ 12/21/2020

Deep Feature Space Trojan Attack of Neural Networks by Controlled Detoxification

Trojan (backdoor) attack is a form of adversarial attack on deep neural ...

8 Siyuan Cheng, et al. ∙

∙ 07/30/2020

Black-box Adversarial Sample Generation Based on Differential Evolution

Deep Neural Networks (DNNs) are being used in various daily tasks such a...

0 Junyu Lin, et al. ∙

∙ 10/27/2018

Attacks Meet Interpretability: Attribute-steered Detection of Adversarial Samples

Adversarial sample attacks perturb benign inputs to induce DNN misbehavi...

0 Guanhong Tao, et al. ∙

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