91 citations · 147 across the 8 of their papers we have counts for
8 papers
An Anti-fraud System for Car Insurance Claim Based on Visual Evidence
Pei Li, Bingyu Shen, Weishan Dong
Automatically scene understanding using machine learning algorithms has been widely applied to different industries to reduce the cost of manual labor. Nowadays, insurance companie…
Autoencoder Regularized Network For Driving Style Representation Learning
Weishan Dong, Ting Yuan, Kai Yang +2
In this paper, we study learning generalized driving style representations from automobile GPS trip data. We propose a novel Autoencoder Regularized deep neural Network (ARNet) and…
Characterizing Driving Styles with Deep Learning
Weishan Dong, Jian Li, Renjie Yao +3
Characterizing driving styles of human drivers using vehicle sensor data, e.g., GPS, is an interesting research problem and an important real-world requirement from automotive indu…
Self-Paced Multi-Task Learning
Changsheng Li, Junchi Yan, Fan Wei +3
In this paper, we propose a novel multi-task learning (MTL) framework, called Self-Paced Multi-Task Learning (SPMTL). Different from previous works treating all tasks and instances…
Joint Active Learning with Feature Selection via CUR Matrix Decomposition
Changsheng Li, Xiangfeng Wang, Weishan Dong +3
This paper presents an unsupervised learning approach for simultaneous sample and feature selection, which is in contrast to existing works which mainly tackle these two problems s…
Dynamic Structure Embedded Online Multiple-Output Regression for Stream Data
Changsheng Li, Fan Wei, Weishan Dong +3
Online multiple-output regression is an important machine learning technique for modeling, predicting, and compressing multi-dimensional correlated data streams. In this paper, we…
Max-Margin based Discriminative Feature Learning
Changsheng Li, Qingshan Liu, Weishan Dong +2
In this paper, we propose a new max-margin based discriminative feature learning method. Specifically, we aim at learning a low-dimensional feature representation, so as to maximiz…
Scaling Up Estimation of Distribution Algorithms For Continuous Optimization
Weishan Dong, Tianshi Chen, Peter Tino +1
Since Estimation of Distribution Algorithms (EDA) were proposed, many attempts have been made to improve EDAs' performance in the context of global optimization. So far, the studie…