25 citations · 59 across the 13 of their papers we have counts for
14 papers
AntMC: A Large Scale Dataset For Multi-Scenario Multi-Modal CTR Prediction
Zhaoxin Huan, Ke Ding, Ang Li +10
Click-through rate (CTR) prediction is a crucial issue in recommendation systems. There has been an emergence of various public CTR datasets. However, existing datasets primarily s…
Towards Open Temporal Graph Neural Networks
Kaituo Feng, Changsheng Li, Xiaolu Zhang +1
Graph neural networks (GNNs) for temporal graphs have recently attracted increasing attentions, where a common assumption is that the class set for nodes is closed. However, in rea…
BadDet: Backdoor Attacks on Object Detection
Shih-Han Chan, Yinpeng Dong, Jun Zhu +2
Deep learning models have been deployed in numerous real-world applications such as autonomous driving and surveillance. However, these models are vulnerable in adversarial environ…
Progressive-Scale Boundary Blackbox Attack via Projective Gradient Estimation
Jiawei Zhang, Linyi Li, Huichen Li +3
Boundary based blackbox attack has been recognized as practical and effective, given that an attacker only needs to access the final model prediction. However, the query efficiency…
Improving Transferability of Adversarial Patches on Face Recognition with Generative Models
Zihao Xiao, Xianfeng Gao, Chilin Fu +5
Face recognition is greatly improved by deep convolutional neural networks (CNNs). Recently, these face recognition models have been used for identity authentication in security se…
Nonlinear Projection Based Gradient Estimation for Query Efficient Blackbox Attacks
Huichen Li, Linyi Li, Xiaojun Xu +3
Gradient estimation and vector space projection have been studied as two distinct topics. We aim to bridge the gap between the two by investigating how to efficiently estimate grad…
QEBA: Query-Efficient Boundary-Based Blackbox Attack
Huichen Li, Xiaojun Xu, Xiaolu Zhang +2
Machine learning (ML), especially deep neural networks (DNNs) have been widely used in various applications, including several safety-critical ones (e.g. autonomous driving). As a…
Data-Free Adversarial Perturbations for Practical Black-Box Attack
ZhaoXin Huan, Yulong Wang, Xiaolu Zhang +3
Neural networks are vulnerable to adversarial examples, which are malicious inputs crafted to fool pre-trained models. Adversarial examples often exhibit black-box attacking transf…
Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics
Bingzhe Wu, Chaochao Chen, Shiwan Zhao +6
Bayesian deep learning is recently regarded as an intrinsic way to characterize the weight uncertainty of deep neural networks~(DNNs). Stochastic Gradient Langevin Dynamics~(SGLD)…
Pruning from Scratch
Yulong Wang, Xiaolu Zhang, Lingxi Xie +4
Network pruning is an important research field aiming at reducing computational costs of neural networks. Conventional approaches follow a fixed paradigm which first trains a large…
Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection
Bingzhe Wu, Shiwan Zhao, ChaoChao Chen +5
In this paper, we aim to understand the generalization properties of generative adversarial networks (GANs) from a new perspective of privacy protection. Theoretically, we prove th…
P3SGD: Patient Privacy Preserving SGD for Regularizing Deep CNNs in Pathological Image Classification
Bingzhe Wu, Shiwan Zhao, Guangyu Sun +4
Recently, deep convolutional neural networks (CNNs) have achieved great success in pathological image classification. However, due to the limited number of labeled pathological ima…
Infinite Curriculum Learning for Efficiently Detecting Gastric Ulcers in WCE Images
Xiaolu Zhang, Shiwan Zhao, Lingxi Xie
The Wireless Capsule Endoscopy (WCE) is becoming a popular way of screening gastrointestinal system diseases and cancer. However, the time-consuming process in inspecting WCE data…
G2C: A Generator-to-Classifier Framework Integrating Multi-Stained Visual Cues for Pathological Glomerulus Classification
Bingzhe Wu, Xiaolu Zhang, Shiwan Zhao +4
Pathological glomerulus classification plays a key role in the diagnosis of nephropathy. As the difference between different subcategories is subtle, doctors often refer to slides…