305 citations · 896 across the 41 of their papers we have counts for
8 papers · 1 filter
DART: Domain-Adversarial Residual-Transfer Networks for Unsupervised Cross-Domain Image Classification
Xianghong Fang, Haoli Bai, Ziyi Guo +3
The accuracy of deep learning (e.g., convolutional neural networks) for an image classification task critically relies on the amount of labeled training data. Aiming to solve an im…
Robust Graph Learning from Noisy Data
Zhao Kang, Haiqi Pan, Steven C. H. Hoi +1
Learning graphs from data automatically has shown encouraging performance on clustering and semisupervised learning tasks. However, real data are often corrupted, which may cause t…
Deep Density-based Image Clustering
Yazhou Ren, Ni Wang, Mingxia Li +1
Recently, deep clustering, which is able to perform feature learning that favors clustering tasks via deep neural networks, has achieved remarkable performance in image clustering…
Latent Dirichlet Allocation in Generative Adversarial Networks
Lili Pan, Shen Cheng, Jian Liu +2
We study the problem of multimodal generative modelling of images based on generative adversarial networks (GANs). Despite the success of existing methods, they often ignore the un…
Compressing Recurrent Neural Networks with Tensor Ring for Action Recognition
Yu Pan, Jing Xu, Maolin Wang +4
Recurrent Neural Networks (RNNs) and their variants, such as Long-Short Term Memory (LSTM) networks, and Gated Recurrent Unit (GRU) networks, have achieved promising performance in…
Self-Paced Multi-Task Clustering
Yazhou Ren, Xiaofan Que, Dezhong Yao +1
Multi-task clustering (MTC) has attracted a lot of research attentions in machine learning due to its ability in utilizing the relationship among different tasks. Despite the succe…