17 citations · 42 across the 8 of their papers we have counts for
8 papers
Voucher Abuse Detection with Prompt-based Fine-tuning on Graph Neural Networks
Zhihao Wen, Yuan Fang, Yihan Liu +2
Voucher abuse detection is an important anomaly detection problem in E-commerce. While many GNN-based solutions have emerged, the supervised paradigm depends on a large quantity of…
Two Heads are Actually Better than One: Towards Better Adversarial Robustness via Transduction and Rejection
Nils Palumbo, Yang Guo, Xi Wu +3
Both transduction and rejection have emerged as important techniques for defending against adversarial perturbations. A recent work by Goldwasser et al. showed that rejection combi…
Adversarial Attacks on ML Defense Models Competition
Yinpeng Dong, Qi-An Fu, Xiao Yang +25
Due to the vulnerability of deep neural networks (DNNs) to adversarial examples, a large number of defense techniques have been proposed to alleviate this problem in recent years.…
Towards Evaluating the Robustness of Neural Networks Learned by Transduction
Jiefeng Chen, Xi Wu, Yang Guo +2
There has been emerging interest in using transductive learning for adversarial robustness (Goldwasser et al., NeurIPS 2020; Wu et al., ICML 2020; Wang et al., ArXiv 2021). Compare…
Towards Adversarial Robustness via Transductive Learning
Jiefeng Chen, Yang Guo, Xi Wu +4
There has been emerging interest to use transductive learning for adversarial robustness (Goldwasser et al., NeurIPS 2020; Wu et al., ICML 2020). Compared to traditional "test-time…
Tensor Random Projection for Low Memory Dimension Reduction
Yiming Sun, Yang Guo, Joel A. Tropp +1
Random projections reduce the dimension of a set of vectors while preserving structural information, such as distances between vectors in the set. This paper proposes a novel use o…
Representation Bayesian Risk Decompositions and Multi-Source Domain Adaptation
Xi Wu, Yang Guo, Jiefeng Chen +3
We consider representation learning (hypothesis class ) where training and test distributions can be different. Recent studies provide hi…
Low-Rank Tucker Approximation of a Tensor From Streaming Data
Yiming Sun, Yang Guo, Charlene Luo +2
This paper describes a new algorithm for computing a low-Tucker-rank approximation of a tensor. The method applies a randomized linear map to the tensor to obtain a sketch that cap…