13 citations · 19 across the 7 of their papers we have counts for
6 papers · 1 filter
Locally Regularized Sparse Graph by Fast Proximal Gradient Descent
Dongfang Sun, Yingzhen Yang
Sparse graphs built by sparse representation has been demonstrated to be effective in clustering high-dimensional data. Albeit the compelling empirical performance, the vanilla spa…
FSNet: Compression of Deep Convolutional Neural Networks by Filter Summary
Yingzhen Yang, Jiahui Yu, Nebojsa Jojic +2
We present a novel method of compression of deep Convolutional Neural Networks (CNNs) by weight sharing through a new representation of convolutional filters. The proposed method r…
An Empirical Study on Regularization of Deep Neural Networks by Local Rademacher Complexity
Yingzhen Yang, Jiahui Yu, Xingjian Li +2
Regularization of Deep Neural Networks (DNNs) for the sake of improving their generalization capability is important and challenging. The development in this line benefits theoreti…
Learning D-FilterMap for Deep Convolutional Neural Networks
Yingzhen Yang, Jianchao Yang, Ning Xu +1
We present a novel and compact architecture for deep Convolutional Neural Networks (CNNs) in this paper, termed D-FilterMap Convolutional Neural Networks (D-FM-CNNs). The con…
Learning A Deep Encoder for Hashing
Zhangyang Wang, Yingzhen Yang, Shiyu Chang +2
We investigate the -constrained representation which demonstrates robustness to quantization errors, utilizing the tool of deep learning. Based on the Alternating Dire…
Self-Tuned Deep Super Resolution
Zhangyang Wang, Yingzhen Yang, Zhaowen Wang +4
Deep learning has been successfully applied to image super resolution (SR). In this paper, we propose a deep joint super resolution (DJSR) model to exploit both external and self s…