7 citations · 21 across the 9 of their papers we have counts for
8 papers · 1 filter
GCoD: Graph Convolutional Network Acceleration via Dedicated Algorithm and Accelerator Co-Design
Haoran You, Tong Geng, Yongan Zhang +2
Graph Convolutional Networks (GCNs) have emerged as the state-of-the-art graph learning model. However, it can be notoriously challenging to inference GCNs over large graph dataset…
One Pass ImageNet
Huiyi Hu, Ang Li, Daniele Calandriello +1
We present the One Pass ImageNet (OPIN) problem, which aims to study the effectiveness of deep learning in a streaming setting. ImageNet is a widely known benchmark dataset that ha…
Semi-Supervised Vision Transformers
Zejia Weng, Xitong Yang, Ang Li +2
We study the training of Vision Transformers for semi-supervised image classification. Transformers have recently demonstrated impressive performance on a multitude of supervised l…
AEVA: Black-box Backdoor Detection Using Adversarial Extreme Value Analysis
Junfeng Guo, Ang Li, Cong Liu
Deep neural networks (DNNs) are proved to be vulnerable against backdoor attacks. A backdoor is often embedded in the target DNNs through injecting a backdoor trigger into training…
Unit Selection with Causal Diagram
Ang Li, Judea Pearl
The unit selection problem aims to identify a set of individuals who are most likely to exhibit a desired mode of behavior, for example, selecting individuals who would respond one…
Towards Adversarial Patch Analysis and Certified Defense against Crowd Counting
Qiming Wu, Zhikang Zou, Pan Zhou +3
Crowd counting has drawn much attention due to its importance in safety-critical surveillance systems. Especially, deep neural network (DNN) methods have significantly reduced esti…