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检索条件"主题词=Stochastic Gradient Algorithm"
92 条 记 录,以下是31-40 订阅
排序:
Convergence in quadratic mean of averaged stochastic gradient algorithms without strong convexity nor bounded gradient
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Series Statistics 2023年 第3期57卷
作者: Antoine Godichon-Baggioni Laboratoire de Probabilités Statistique et Modélisation Sorbonne-Université Paris France
Online averaged stochastic gradient algorithms are more and more studied since (i) they can deal quickly with large sample taking values in high-dimensional spaces, (ii) they enable to treat data sequentially, (iii) t... 详细信息
来源: 评论
Adaptive Filtering under Minimum Information Divergence Criterion
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INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS 2009年 第2期7卷 157-164页
作者: Chen, Badong Zhu, Yu Hu, Jinchun Sun, Zengqi Tsinghua Univ Inst Mfg Engn Dept Precis Instruments & Mechanol Beijing 100084 Peoples R China Tsinghua Univ Dept Comp Sci & Technol State Key Lab Intelligent Technol & Syst Beijing 100084 Peoples R China
Traditional filtering theory is always based on optimization of the expected value of a suitably chosen function of error, Such as the minimum mean-square error (MMSE) criterion, the minimum error entropy (MEE) criter... 详细信息
来源: 评论
Minimum deviation distribution machine for large scale regression
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KNOWLEDGE-BASED SYSTEMS 2018年 146卷 167-180页
作者: Liu, Ming-Zeng Shao, Yuan-Hai Wang, Zhen Li, Chun-Na Chen, Wei-Jie Dalian Univ Technol Sch Math & Phys Sci Panjin 124221 Peoples R China Hainan Univ Sch Econ & Management Haikou 570228 Hainan Peoples R China Inner Mongolia Univ Sch Math Sci Hohhot 010021 Peoples R China Zhejiang Univ Technol Zhijiang Coll Hangzhou 310024 Zhejiang Peoples R China
In this paper, by introducing the statistics of training data into support vector regression (SVR), we propose a minimum deviation distribution regression (MDR). Rather than just minimizing the structural risk, MDR al... 详细信息
来源: 评论
Recursive coupled projection algorithms for multivariable output-error-like systems with coloured noises
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IET SIGNAL PROCESSING 2020年 第7期14卷 455-466页
作者: Pan, Jian Ma, Hao Zhang, Xiao Liu, Qinyao Ding, Feng Chang, Yufang Sheng, Jie Hubei Univ Technol Sch Elect & Elect Engn Hubei Key Lab High Efficiency Utilizat Solar Ener Wuhan 430068 Peoples R China Jiangnan Univ Sch Internet Things Engn Wuxi 214122 Jiangsu Peoples R China Univ Washington Sch Engn & Technol Tacoma WA 98402 USA
By combining the coupling identification concept with the gradient search, this study develops a partially coupled generalised extended projection algorithm and a partially coupled generalised extended stochastic grad... 详细信息
来源: 评论
Adaptive error-constrained method for LMS algorithms and applications
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SIGNAL PROCESSING 2005年 第10期85卷 1875-1897页
作者: Choi, S Lee, TW Hong, D Yonsei Univ Ctr IT Seoul 120749 South Korea Univ Calif San Diego INC La Jolla CA 92093 USA
An adaptive error-constrained least mean square (AECLMS) algorithm is derived and proposed using adaptive error-constrained optimization techniques. This is accomplished by modifying the cost function of the LMS algor... 详细信息
来源: 评论
Low-Rate-Feedback-Assisted Beamforming and Power Control for MIMO-OFDM Systems
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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2010年 第1期59卷 225-234页
作者: Merli, Filippo Zuccardi Wang, Xiaodong Vitetta, Giorgio Matteo Univ Modena & Reggio Emilia Dept Informat Engn I-41100 Modena Italy Columbia Univ Dept Elect Engn New York NY 10027 USA
This paper proposes a novel solution to the problem of beamforming and power control in the downlink of a multiple-input multiple-output ( MIMO) orthogonal frequency-division multiplexing (OFDM) system. This solution ... 详细信息
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Identifying Cognitive Radars-Inverse Reinforcement Learning Using Revealed Preferences
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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2020年 68卷 4529-4542页
作者: Krishnamurthy, Vikram Angley, Daniel Evans, Robin Moran, Bill Cornell Univ Sch Elect & Comp Engn Ithaca NY 14853 USA Univ Melbourne Dept Elect & Elect Engn Parkville Vic 3010 Australia
We consider an inverse reinforcement learning problem involving "us" versus an "enemy" radar equipped with a Bayesian tracker. By observing the emissions of the enemy radar, how can we identify if ... 详细信息
来源: 评论
A modified constrained constant modulus approach to blind adaptive multiuser detection
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IEEE TRANSACTIONS ON COMMUNICATIONS 2001年 第9期49卷 1642-1648页
作者: Xu, CJ Feng, GZ Kwak, KS Nanjing Univ Posts & Telecommun Dept Telecommun Engn Nanjing 21003 Peoples R China Inha Univ Sch Informat & Commun Engn Inchon 402751 South Korea
An alternative blind adaptive multiuser detection is investigated based on modified constrained constant modulus (CM) criterion. It has been shown that the performance of a CM-based receiver is limited by the received... 详细信息
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Research on a learning rate with energy index in deep learning
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NEURAL NETWORKS 2019年 110卷 225-231页
作者: Zhao, Huizhen Liu, Fuxian Zhang, Han Liang, Zhibing Air Force Engn Univ Changle East Rd1 Jia Zi Xian Shaanxi Peoples R China
The stochastic gradient descent algorithm (SGD) is the main optimization solution in deep learning. The performance of SGD depends critically on how learning rates are tuned over time. In this paper, we propose a nove... 详细信息
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Convergence of the recursive identification algorithms for multivariate pseudo-linear regressive systems
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INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING 2016年 第6期30卷 824-842页
作者: Wang, Xuehai Ding, Feng Jiangnan Univ Key Lab Adv Proc Control Light Ind Minist Educ Wuxi 214122 Peoples R China Henan Univ Urban Construct Sch Math & Phys Pingdingshan 467036 Peoples R China
The performance analysis of the recursive algorithms for the multivariate systems with an autoregressive moving average noise process is still open. This paper analyzes the convergence of two recursive identification ... 详细信息
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