253 citations · 745 across the 24 of their papers we have counts for
6 papers · 1 filter
The Expressive Power of Neural Networks: A View from the Width
Zhou Lu, Hongming Pu, Feicheng Wang +2
The expressive power of neural networks is important for understanding deep learning. Most existing works consider this problem from the view of the depth of a network. In this pap…
Generalization Bounds of SGLD for Non-convex Learning: Two Theoretical Viewpoints
Wenlong Mou, Liwei Wang, Xiyu Zhai +1
Algorithm-dependent generalization error bounds are central to statistical learning theory. A learning algorithm may use a large hypothesis space, but the limited number of iterati…
Zero-Shot Fine-Grained Classification by Deep Feature Learning with Semantics
Aoxue Li, Zhiwu Lu, Liwei Wang +3
Fine-grained image classification, which aims to distinguish images with subtle distinctions, is a challenging task due to two main issues: lack of sufficient training data for eve…
Collect at Once, Use Effectively: Making Non-interactive Locally Private Learning Possible
Kai Zheng, Wenlong Mou, Liwei Wang
Non-interactive Local Differential Privacy (LDP) requires data analysts to collect data from users through noisy channel at once. In this paper, we extend the frontiers of Non-inte…
Accurate Pulmonary Nodule Detection in Computed Tomography Images Using Deep Convolutional Neural Networks
Jia Ding, Aoxue Li, Zhiqiang Hu +1
Early detection of pulmonary cancer is the most promising way to enhance a patient's chance for survival. Accurate pulmonary nodule detection in computed tomography (CT) images is…
Quadratic Upper Bound for Recursive Teaching Dimension of Finite VC Classes
Lunjia Hu, Ruihan Wu, Tianhong Li +1
In this work we study the quantitative relation between the recursive teaching dimension (RTD) and the VC dimension (VCD) of concept classes of finite sizes. The RTD of a concept c…