activity
20192024
most citedA fully 3D multi-path convolutional neural network with feature fusion and feature weighting for automatic lesion identification in brain MRI images

5 citations · 9 across the 6 of their papers we have counts for

collaborators

6 papers

cs.IR2024

MixRec: Heterogeneous Graph Collaborative Filtering

Lianghao Xia, Meiyan Xie, Yong Xu +1

For modern recommender systems, the use of low-dimensional latent representations to embed users and items based on their observed interactions has become commonplace. However, man…

cs.LG2020★ 2 cited

Defending against substitute model black box adversarial attacks with the 01 loss

Yunzhe Xue, Meiyan Xie, Usman Roshan

Substitute model black box attacks can create adversarial examples for a target model just by accessing its output labels. This poses a major challenge to machine learning models i…

cs.LG2020

Towards adversarial robustness with 01 loss neural networks

Yunzhe Xue, Meiyan Xie, Usman Roshan

Motivated by the general robustness properties of the 01 loss we propose a single hidden layer 01 loss neural network trained with stochastic coordinate descent as a defense agains…

cs.LG2020★ 1 cited

On the transferability of adversarial examples between convex and 01 loss models

Yunzhe Xue, Meiyan Xie, Usman Roshan

The 01 loss gives different and more accurate boundaries than convex loss models in the presence of outliers. Could the difference of boundaries translate to adversarial examples t…

cs.LG2020★ 1 cited

Robust binary classification with the 01 loss

Yunzhe Xue, Meiyan Xie, Usman Roshan

The 01 loss is robust to outliers and tolerant to noisy data compared to convex loss functions. We conjecture that the 01 loss may also be more robust to adversarial attacks. To st…

eess.IV2019★ 5 cited

A fully 3D multi-path convolutional neural network with feature fusion and feature weighting for automatic lesion identification in brain MRI images

Yunzhe Xue, Meiyan Xie, Fadi G. Farhat +5

We propose a fully 3D multi-path convolutional network to predict stroke lesions from 3D brain MRI images. Our multi-path model has independent encoders for different modalities co…