83 citations · 141 across the 19 of their papers we have counts for
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An axiomatized PDE model of deep neural networks
Tangjun Wang, Wenqi Tao, Chenglong Bao +1
Inspired by the relation between deep neural network (DNN) and partial differential equations (PDEs), we study the general form of the PDE models of deep neural networks. To achiev…
Semi-Supervised Clustering via Dynamic Graph Structure Learning
Huaming Ling, Chenglong Bao, Xin Liang +1
Most existing semi-supervised graph-based clustering methods exploit the supervisory information by either refining the affinity matrix or directly constraining the low-dimensional…
Convergence Rates of Training Deep Neural Networks via Alternating Minimization Methods
Jintao Xu, Chenglong Bao, Wenxun Xing
Training deep neural networks (DNNs) is an important and challenging optimization problem in machine learning due to its non-convexity and non-separable structure. The alternating…
A scalable deep learning approach for solving high-dimensional dynamic optimal transport
Wei Wan, Yuejin Zhang, Chenglong Bao +2
The dynamic formulation of optimal transport has attracted growing interests in scientific computing and machine learning, and its computation requires to solve a PDE-constrained o…
AFEC: Active Forgetting of Negative Transfer in Continual Learning
Liyuan Wang, Mingtian Zhang, Zhongfan Jia +5
Continual learning aims to learn a sequence of tasks from dynamic data distributions. Without accessing to the old training samples, knowledge transfer from the old tasks to each n…
Diffusion Mechanism in Residual Neural Network: Theory and Applications
Tangjun Wang, Zehao Dou, Chenglong Bao +1
Diffusion, a fundamental internal mechanism emerging in many physical processes, describes the interaction among different objects. In many learning tasks with limited training sam…
Brain-inspired reverse adversarial examples
Shaokai Ye, Sia Huat Tan, Kaidi Xu +3
A human does not have to see all elephants to recognize an animal as an elephant. On contrast, current state-of-the-art deep learning approaches heavily depend on the variety of tr…
SCAN: A Scalable Neural Networks Framework Towards Compact and Efficient Models
Linfeng Zhang, Zhanhong Tan, Jiebo Song +3
Remarkable achievements have been attained by deep neural networks in various applications. However, the increasing depth and width of such models also lead to explosive growth in…
Be Your Own Teacher: Improve the Performance of Convolutional Neural Networks via Self Distillation
Linfeng Zhang, Jiebo Song, Anni Gao +3
Convolutional neural networks have been widely deployed in various application scenarios. In order to extend the applications' boundaries to some accuracy-crucial domains, research…
Wasserstein-Fisher-Rao Document Distance
Zihao Wang, Datong Zhou, Yong Zhang +2
As a fundamental problem of natural language processing, it is important to measure the distance between different documents. Among the existing methods, the Word Mover's Distance…