no code implementations • 30 Apr 2018 • Pei Li, Bingyu Shen, Weishan Dong
Both local and global deep features are extracted using VGG model\cite{Simonyan14c}, which are fused later for more robust system performance.
1 code implementation • 5 Jan 2017 • Weishan Dong, Ting Yuan, Kai Yang, Changsheng Li, Shilei Zhang
In this paper, we study learning generalized driving style representations from automobile GPS trip data.
2 code implementations • 13 Jul 2016 • Weishan Dong, Jian Li, Renjie Yao, Changsheng Li, Ting Yuan, Lanjun Wang
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 industries.
no code implementations • 6 Apr 2016 • Changsheng Li, Junchi Yan, Fan Wei, Weishan Dong, Qingshan Liu, Hongyuan Zha
In this paper, we propose a novel multi-task learning (MTL) framework, called Self-Paced Multi-Task Learning (SPMTL).
no code implementations • 22 Mar 2016 • Changsheng Li, Fan Wei, Junchi Yan, Weishan Dong, Qingshan Liu, Xiao-Yu Zhang, Hongyuan Zha
In this paper, we propose a novel multi-label learning framework, called Multi-Label Self-Paced Learning (MLSPL), in an attempt to incorporate the self-paced learning strategy into multi-label learning regime.
no code implementations • 4 Mar 2015 • Changsheng Li, Xiangfeng Wang, Weishan Dong, Junchi Yan, Qingshan Liu, Hongyuan Zha
In particular, our method runs in one-shot without the procedure of iterative sample selection for progressive labeling.
no code implementations • 18 Dec 2014 • Changsheng Li, Fan Wei, Weishan Dong, Qingshan Liu, Xiangfeng Wang, Xin Zhang
MORES can \emph{dynamically} learn the structure of the coefficients change in each update step to facilitate the model's continuous refinement.
no code implementations • 16 Dec 2014 • Changsheng Li, Qingshan Liu, Weishan Dong, Xin Zhang, Lin Yang
In this paper, we propose a new max-margin based discriminative feature learning method.