Results 311 to 320 of about 6,326,915 (384)

Transferred Feature Selection

2009 IEEE International Conference on Data Mining Workshops, 2009
Traditional feature selection algorithms require a large number of labeled training instances to find out the most informative subset of features. However, in many real-world applications, the labeled data are often difficult, expensive or time-consuming to obtain.
Wei Bi, Yuan Shi, Zhenzhong Lan
openaire   +1 more source

A Minimax Game for Instance based Selective Transfer Learning

Knowledge Discovery and Data Mining, 2019
Deep neural network based transfer learning has been widely used to leverage information from the domain with rich data to help domain with insufficient data.
Bo Wang, Minghui Qiu, Xisen Wang, Yaliang Li, Yu Gong, Xiaoyi Zeng, Jun Huang, Bo Zheng, Deng Cai, Jingren Zhou   +9 more
semanticscholar   +1 more source

Metal organic framework-capsulated CoCu nanoparticles for the selective transfer hydrogenation of nitrobenzaldehydes: engineering active armour by half-way injection method.

Chemistry, 2020
A novel armour-type composite of metal organic framework-capsulated CoCu nanoparticles with Fe3O4 core (Fe3O4@SiO2-NH2-CoCu@UiO-66) has been designed and synthesized by the half-way injection method, which successfully serves as an efficient and ...
Yang Li, Yu‐Nong Li, Jianwei Zheng, Xiao-Yun Dong, Rongxiu Guo, Yiming Wang, Ze‐nan Hu, Yongjian Ai, Qiong-lin Liang, Hong‐bin Sun   +9 more
semanticscholar   +1 more source

Selective Cross-City Transfer Learning for Traffic Prediction via Source City Region Re-Weighting

Knowledge Discovery and Data Mining, 2022
Deep learning models have been demonstrated powerful in modeling complex spatio-temporal data for traffic prediction. In practice, effective deep traffic prediction models rely on large-scale traffic data, which is not always available in real-world ...
Yilun Jin, Kai Chen, Qian Yang
semanticscholar   +1 more source

CoOx@Co Nanoparticle‐based Catalyst for Efficient Selective Transfer Hydrogenation of α,β‐Unsaturated Aldehydes

, 2020
Currently, developing simple and effective catalysts for selective hydrogenation of α,β‐unsaturated aldehydes to unsaturated alcohols is challenging.
Wanbing Gong, Miaomiao Han, Chun Chen, Yue Lin, Guozhong Wang, Haimin Zhang, Huijun Zhao   +6 more
semanticscholar   +1 more source

Transfer RNA in Solution: Selected Topics

Annual Review of Biophysics and Bioengineering, 1980
Ever since the elucidation of the primary structure of a specific tRNA (45), there have been a progression of physical studies aimed at de­ termining the detailed structure and solution behavior of tRNA. Some of this work culminated in the three-dimensional crystal structure de­ termination (65,90), which provided a concrete foundation on which to ...
P R, Schimmel, A G, Redfield
openaire   +2 more sources

Tubal selection for gamete intrafallopian transfer

Fertility and Sterility, 1994
When both fallopian tubes appear normal, tubal selection for GIFT is left to the surgeon's discretion. We were interested to learn whether pregnancy rates were influenced by the choice of tubal transfer in relation to ovarian dominance. Ovarian dominance was defined sonographically as the ovary containing the greater number of follicles having a mean ...
M X, Ransom, G H, Corsan, A J, Garcia, K A, Doherty, E, Kemmann   +4 more
openaire   +2 more sources

Selective Transfer Based Evolutionary Multitasking Optimization for Change Detection

IEEE Transactions on Emerging Topics in Computational Intelligence
Change detection in multitemporal remote sensing images aims to generate a difference image (DI) and then analyze it to identify the unchanged/changed areas. The current change detection techniques always investigate a single change detection task of two
Hao Li, Tianshi Luo, Liwen Liu, Maoguo Gong, W. Qiao, Fei Xie, A. K. Qin   +6 more
semanticscholar   +1 more source

An Interpretable Deep Transfer Learning-Based Remaining Useful Life Prediction Approach for Bearings With Selective Degradation Knowledge Fusion

IEEE Transactions on Instrumentation and Measurement, 2022
This article tries to answer the two questions of bearings’ remaining useful life (RUL) prediction with deep transfer learning: what bearing data in the source domain contribute more to transfer learning and how to quantify such contribution?
Wentao Mao, J. Liu, Jiaxian Chen, Xihui Liang   +3 more
semanticscholar   +1 more source

Selective saturation in magnetization transfer experiments

Magnetic Resonance in Medicine, 1994
AbstractThe concept of magnetic saturation in single and binary spin systems is essential to the understanding of magnetization transfer experiments. This paper outlines the requirements for selective magnetic saturation of either of two spin pools contained in a mixture, both having identical chemical shifts. Following a brief discussion of saturation
J C, McGowan, J S, Leigh
openaire   +2 more sources