1k citations · 2.4k across the 22 of their papers we have counts for
6 papers · 1 filter
ReNAS:Relativistic Evaluation of Neural Architecture Search
Yixing Xu, Yunhe Wang, Kai Han +4
An effective and efficient architecture performance evaluation scheme is essential for the success of Neural Architecture Search (NAS). To save computational cost, most of existing…
Full-Stack Filters to Build Minimum Viable CNNs
Kai Han, Yunhe Wang, Yixing Xu +3
Deep convolutional neural networks (CNNs) are usually over-parameterized, which cannot be easily deployed on edge devices such as mobile phones and smart cameras. Existing works us…
Bringing Giant Neural Networks Down to Earth with Unlabeled Data
Yehui Tang, Shan You, Chang Xu +2
Compressing giant neural networks has gained much attention for their extensive applications on edge devices such as cellphones. During the compressing process, one of the most imp…
Multi-view Vector-valued Manifold Regularization for Multi-label Image Classification
Yong Luo, Dacheng Tao, Chang Xu +3
In computer vision, image datasets used for classification are naturally associated with multiple labels and comprised of multiple views, because each image may contain several obj…
Multi-View Intact Space Learning
Chang Xu, Dacheng Tao, Chao Xu
It is practical to assume that an individual view is unlikely to be sufficient for effective multi-view learning. Therefore, integration of multi-view information is both valuable…
Cost-Sensitive Feature Selection by Optimizing F-Measures
Meng Liu, Chang Xu, Yong Luo +3
Feature selection is beneficial for improving the performance of general machine learning tasks by extracting an informative subset from the high-dimensional features. Conventional…