117 citations · 207 across the 12 of their papers we have counts for
7 papers · 1 filter
Distillation Early Stopping? Harvesting Dark Knowledge Utilizing Anisotropic Information Retrieval For Overparameterized Neural Network
Bin Dong, Jikai Hou, Yiping Lu +1
Distillation is a method to transfer knowledge from one model to another and often achieves higher accuracy with the same capacity. In this paper, we aim to provide a theoretical u…
Annotation-Free Cardiac Vessel Segmentation via Knowledge Transfer from Retinal Images
Fei Yu, Jie Zhao, Yanjun Gong +6
Segmenting coronary arteries is challenging, as classic unsupervised methods fail to produce satisfactory results and modern supervised learning (deep learning) requires manual ann…
Understanding and Improving Transformer From a Multi-Particle Dynamic System Point of View
Yiping Lu, Zhuohan Li, Di He +5
The Transformer architecture is widely used in natural language processing. Despite its success, the design principle of the Transformer remains elusive. In this paper, we provide…
NPTC-net: Narrow-Band Parallel Transport Convolutional Neural Network on Point Clouds
Pengfei Jin, Tianhao Lai, Rongjie Lai +1
Convolution plays a crucial role in various applications in signal and image processing, analysis, and recognition. It is also the main building block of convolution neural network…
Learning to Discretize: Solving 1D Scalar Conservation Laws via Deep Reinforcement Learning
Yufei Wang, Ziju Shen, Zichao Long +1
Conservation laws are considered to be fundamental laws of nature. It has broad applications in many fields, including physics, chemistry, biology, geology, and engineering. Solvin…
You Only Propagate Once: Accelerating Adversarial Training via Maximal Principle
Dinghuai Zhang, Tianyuan Zhang, Yiping Lu +2
Deep learning achieves state-of-the-art results in many tasks in computer vision and natural language processing. However, recent works have shown that deep networks can be vulnera…