中国科学院机构知识库网格系统: 检索

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	Efficient and High-quality Recommendations via Momentum-incorporated Parallel Stochastic Gradient Descent-Based Learning 期刊论文 OAI收割 IEEE-CAA JOURNAL OF AUTOMATICA SINICA, 2021, 卷号: 8, 期号: 2, 页码: 402-411 作者: Luo, Xin; Qin, Wen; Dong, Ani; Sedraoui, Khaled; Zhou, MengChu \| 收藏 \| 浏览/下载：23/0 \| 提交时间：2021/03/17 Big data industrial application industrial data latent factor analysis machine learning parallel algorithm recommender system (RS) stochastic gradient descent (SGD)
	Efficient and High-quality Recommendations via Momentum-incorporated Parallel Stochastic Gradient Descent-Based Learning 期刊论文 OAI收割 IEEE/CAA Journal of Automatica Sinica, 2021, 卷号: 8, 期号: 2, 页码: 402-411 作者: Xin Luo; Wen Qin; Ani Dong; Khaled Sedraoui; MengChu Zhou \| 收藏 \| 浏览/下载：16/0 \| 提交时间：2021/04/09 Big data industrial application industrial data latent factor analysis machine learning parallel algorithm recommender system (RS) stochastic gradient descent (SGD)
	Convergence acceleration algorithms related to a generalized E-transformation and its particular cases 期刊论文 OAI收割 JAPAN JOURNAL OF INDUSTRIAL AND APPLIED MATHEMATICS, 2013, 卷号: 30, 期号: 2, 页码: 263-285 作者: He, Yi; Hu, Xing-Biao; Tam, Hon-Wah; Tsujimoto, Satoshi 收藏 \| 浏览/下载：12/0 \| 提交时间：2015/06/23 E-transformation epsilon-algorithm G-algorithm rs-algorithm qd-algorithm
	A generalization of the G-transformation and the related algorithms 期刊论文 OAI收割 APPLIED NUMERICAL MATHEMATICS, 2010, 卷号: 60, 期号: 12, 页码: 1221-1230 作者: Brezinski, Claude; He, Yi; Hu, Xing-Biao; Sun, Jian-Qing \| 收藏 \| 浏览/下载：18/0 \| 提交时间：2018/07/30 G-transformation G-algorithm rs-algorithm qd-algorithm
	A new method of target recognition based on rough set and support vector machine (EI CONFERENCE) 会议论文 OAI收割 2nd International Conference on Image Analysis and Signal Processing, IASP'2010, April 12, 2010 - April 14, 2010, Xiamen, China 作者: He X. 收藏 \| 浏览/下载：18/0 \| 提交时间：2013/03/25 Automatic target recognition (ATR) is an important task in image application. This paper concentrates on two key subroutines of ATR system: Pre-treatment and design of classifier. In the pre-treatment subroutine a new method based on Rough Set (RS) is proposed to partition the original sample set into some subsets and calculate their class membership so that some samples can be chosen by class membership to be trained. After pre-treatment an iterative algorithm based on Rough Set and Support Vector Machines (IRSSVM) is introduced to design a classifier for recognizing two types of targets. The experiment results show that IRSSVM needs less training time and the classifier is simpler and has more generalization and higher recognition rate. 2010 IEEE.
	A design of high-speed and low-consume parallel grouping RS code and simulation (EI CONFERENCE) 会议论文 OAI收割 2010 3rd International Conference on Advanced Computer Theory and Engineering, ICACTE 2010, August 20, 2010 - August 22, 2010, Chengdu, China Chen C.; Jin G. 收藏 \| 浏览/下载：22/0 \| 提交时间：2013/03/25 RS code is a linear error correction codes with better error correction capability is widely used in different kinds of occasions for communications or data storage. But for its high difficulty of coding and decoding algorithm and low throughput optimization RS algorithm is always studied as one of the focus in the error-correction field. A new coding method parallel coding and decoding data into groups in lower step finite field for avoiding complex matrix iteration and Chien search computation is proposed in this paper. It is proved that the coding and decoding throughput of the parallel grouping RS coder is increased and the hardware complexity is reduced with changeless error-correction capability from the simulation results using ModelSim SE 6.0 and synthetic results using ISE 9.11. 2010 IEEE.