Zobrazeno 1 - 10
of 75
pro vyhledávání: '"Jianping Yin"'
Publikováno v:
IEEE Access, Vol 9, Pp 9101-9116 (2021)
to the vehicle’s severe maneuver and abnormal measurements of GPS in practical applications, the statistic of process noise in SINS/GPS integrated navigation system may be unknown and the measurement noise may not follow the Gaussian distribution,
Autor:
Wendi Wu, Jianping Yin, Xinwang Liu, Xingxing Zhang, Yawei Zhao, Shixiong Wang, Lailong Luo, En Zhu
Publikováno v:
ACM Transactions on Intelligent Systems and Technology. 12:1-17
Recently, convex-concave bilinear Saddle Point Problems (SPP) is widely used in lasso problems, Support Vector Machines, game theory, and so on. Previous researches have proposed many methods to solve SPP, and present their convergence rate theoretic
Autor:
Jianping Yin, Jiyuan Liu, Xifeng Guo, Xinwang Liu, Sihang Zhou, Yongping Zhai, En Zhu, Wen Gao, Yawei Zhao
Publikováno v:
AAAI
Multi-view spectral clustering aims to group data into different categories by optimally exploring complementary information from multiple Laplacian matrices. However, existing methods usually linearly combine a group of pre-specified first-order Lap
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems. 31:1351-1362
Multiple kernel clustering (MKC) has been intensively studied during the last few decades. Even though they demonstrate promising clustering performance in various applications, existing MKC algorithms do not sufficiently consider the intrinsic neigh
Publikováno v:
Information Fusion. 53:145-154
Multiple kernel clustering (MKC) is an important research topic during the last few decades. It optimally combines a group of pre-specified base kernels to improve clustering performance. Though demonstrating promising performance in various applicat
Publikováno v:
AAAI
Incomplete multi-view clustering (IMVC) optimally fuses multiple pre-specified incomplete views to improve clustering performance. Among various excellent solutions, the recently proposed multiple kernel k-means with incomplete kernels (MKKM-IK) form
Publikováno v:
AAAI
Efficient detection of outliers from massive data with a high outlier ratio is challenging but not explicitly discussed yet. In such a case, existing methods either suffer from poor robustness or require expensive computations. This paper proposes a
Publikováno v:
Multimedia Tools and Applications. 78:29509-29527
A smart environment is one of the application scenarios of the Internet of Things (IoT). In order to provide a ubiquitous smart environment for humans, a variety of technologies are developed. In a smart environment system, sound event detection is o
Publikováno v:
IEEE Access, Vol 7, Pp 69162-69171 (2019)
Clustering has been intensively studied in machine learning and data mining communities. Although demonstrating promising performance in various applications, most of the existing clustering algorithms cannot efficiently handle clustering tasks with
Publikováno v:
IEEE Access, Vol 7, Pp 51656-51664 (2019)
This paper presents a robust image hashing algorithm that exploits low-rank decomposition and path integral local binary pattern (pi-LBP), referred to LRPL hashing. The proposed algorithm generates a compact binary sequence from a low-rank component