134 citations · 920 across the 72 of their papers we have counts for
8 papers · 1 filter
Efficient Model-Free Reinforcement Learning Using Gaussian Process
Ying Fan, Letian Chen, Yizhou Wang
Efficient Reinforcement Learning usually takes advantage of demonstration or good exploration strategy. By applying posterior sampling in model-free RL under the hypothesis of GP,…
CRAVES: Controlling Robotic Arm with a Vision-based Economic System
Yiming Zuo, Weichao Qiu, Lingxi Xie +3
Training a robotic arm to accomplish real-world tasks has been attracting increasing attention in both academia and industry. This work discusses the role of computer vision algori…
End-to-end Active Object Tracking and Its Real-world Deployment via Reinforcement Learning
Wenhan Luo, Peng Sun, Fangwei Zhong +3
We study active object tracking, where a tracker takes visual observations (i.e., frame sequences) as input and produces the corresponding camera control signals as output (e.g., m…
Integrating Feature and Image Pyramid: A Lung Nodule Detector Learned in Curriculum Fashion
Benyuan Sun, Zhen Zhou, Fandong Zhang +2
Lung nodules suffer large variation in size and appearance in CT images. Nodules less than 10mm can easily lose information after down-sampling in convolutional neural networks, wh…
FDR-HS: An Empirical Bayesian Identification of Heterogenous Features in Neuroimage Analysis
Xinwei Sun, Lingjing Hu, Fandong Zhang +2
Recent studies found that in voxel-based neuroimage analysis, detecting and differentiating "procedural bias" that are introduced during the preprocessing steps from lesion feature…
MSplit LBI: Realizing Feature Selection and Dense Estimation Simultaneously in Few-shot and Zero-shot Learning
Bo Zhao, Xinwei Sun, Yanwei Fu +2
It is one typical and general topic of learning a good embedding model to efficiently learn the representation coefficients between two spaces/subspaces. To solve this task, $L_{1}…
A Large-scale Attribute Dataset for Zero-shot Learning
Bo Zhao, Yanwei Fu, Rui Liang +3
Zero-Shot Learning (ZSL) has attracted huge research attention over the past few years; it aims to learn the new concepts that have never been seen before. In classical ZSL algorit…
Joint Learning for Pulmonary Nodule Segmentation, Attributes and Malignancy Prediction
Botong Wu, Zhen Zhou, Jianwei Wang +1
Refer to the literature of lung nodule classification, many studies adopt Convolutional Neural Networks (CNN) to directly predict the malignancy of lung nodules with original thora…