170 citations · 468 across the 48 of their papers we have counts for
9 papers · 1 filter
Domain-Invariant Adversarial Learning for Unsupervised Domain Adaption
Yexun Zhang, Ya Zhang, Yanfeng Wang +1
Unsupervised domain adaption aims to learn a powerful classifier for the target domain given a labeled source data set and an unlabeled target data set. To alleviate the effect of…
Phase Collaborative Network for Two-Phase Medical Image Segmentation
Huangjie Zheng, Lingxi Xie, Tianwei Ni +5
In real-world practice, medical images acquired in different phases possess complementary information, {\em e.g.}, radiologists often refer to both arterial and venous scans in ord…
Variational Collaborative Learning for User Probabilistic Representation
Kenan Cui, Xu Chen, Jiangchao Yao +1
Collaborative filtering (CF) has been successfully employed by many modern recommender systems. Conventional CF-based methods use the user-item interaction data as the sole informa…
A Unified Framework for Generalizable Style Transfer: Style and Content Separation
Yexun Zhang, Ya Zhang, Wenbin Cai
Image style transfer has drawn broad attention in recent years. However, most existing methods aim to explicitly model the transformation between different styles, and the learned…
Masking: A New Perspective of Noisy Supervision
Bo Han, Jiangchao Yao, Gang Niu +4
It is important to learn various types of classifiers given training data with noisy labels. Noisy labels, in the most popular noise model hitherto, are corrupted from ground-truth…
Variational Composite Autoencoders
Jiangchao Yao, Ivor Tsang, Ya Zhang
Learning in the latent variable model is challenging in the presence of the complex data structure or the intractable latent variable. Previous variational autoencoders can be low…
An Element Sensitive Saliency Model with Position Prior Learning for Web Pages
Yujun Gu, Jie Chang, Ya Zhang +1
Understanding human visual attention is important for multimedia applications. Many studies have attempted to learn from eye-tracking data and build computational saliency predicti…
Collaborative Learning for Weakly Supervised Object Detection
Jiajie Wang, Jiangchao Yao, Ya Zhang +1
Weakly supervised object detection has recently received much attention, since it only requires image-level labels instead of the bounding-box labels consumed in strongly supervise…
Degeneration in VAE: in the Light of Fisher Information Loss
Huangjie Zheng, Jiangchao Yao, Ya Zhang +1
While enormous progress has been made to Variational Autoencoder (VAE) in recent years, similar to other deep networks, VAE with deep networks suffers from the problem of degenerat…