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在“Elsevier”中，命中：405条，耗时：0.0100195 秒

1.Applying active learning to assertion classification of concepts in clinical text

作者：Yukun Chen ; Subramani Mani ; Hua Xu ; ^{hua.xu@vanderbilt.edu}

关键词：Active learning ; Natural language processing ; Clinical text classification ; Machine learning

刊名：Journal of Biomedical Informatics

出版年：2012

2.Inconsistency-based active learning for support vector machines

作者：Ran Wang^a ; [Author Vitae] ; Sam Kwong^a ; ^{CSSAMK@cityu.edu.hk} ; [Author Vitae] ; Degang Chen^b ; [Author Vitae]

关键词：Active learning ; Concept learning ; Inconsistency ; Sample selection ; Support vector machine

刊名：Pattern Recognition

出版年：2012

3.A cluster-assumption based batch mode active learning technique

作者：Swarnajyoti Patra ; Lorenzo Bruzzone ; ^{lorenzo.bruzzone@ing.unitn.it}

关键词：Active learning ; Cluster assumption ; Entropy ; Query function ; Support vector machine

刊名：Pattern Recognition Letters

出版年：2012

4.Simple, fast, and accurate parametric modeling of the coupling and external quality factor for microstrip filter design using active learning method

作者：Payman Rezaee^a ; ^b ; ^{pre@tf.uni-kiel.de} ; [Author Vitae] ; Reinhard Knö ; chel^a ; [Author Vitae] ; Majid Tayarani^b ; [Author Vitae]

关键词：Active learning method ; Coupling factor computation ; External quality factor computation ; Ink drop spread ; Microstrip bandpass filters ; Soft computing techniques

刊名：AEU - International Journal of Electronics and Communications

出版年：2012

5.Sparse multikernel support vector regression machines trained by active learning

作者：V. Ceperic^a ; ^b ; ^{vladimir.ceperic@ieee.org} ; G. Gielen^a ; A. Baric^b

关键词：Support vector machines ; Support vector regression ; Multikernel ; Sparse models ; Active learning

刊名：Expert Systems with Applications

出版年：2012

6.Recurrent sparse support vector regression machines trained by active learning in the time-domain

作者：V. Ceperic^a ; ^b ; ^{vladimir.ceperic@ieee.org} ; G. Gielen^a ; A. Baric^b

关键词：Support vector machines ; Support vector regression ; Recurrent models ; Sparse models ; Active learning

刊名：Expert Systems with Applications

出版年：2012

7.An active learning genetic algorithm for integrated process planning and scheduling

作者：Xinyu Li ; Liang Gao ; ^{gaoliang@mail.hust.edu.cn} ; Xinyu Shao

关键词：Active learning genetic algorithm ; Integrated process planning and scheduling ; Process planning ; Scheduling

刊名：Expert Systems with Applications

出版年：2012

8.Adaptive Selective Learning for automatic identification of sub-kilometer craters

作者：Siyi Liu^a ; ^{sliu@cs.umb.edu} ; [Author Vitae] ; Wei Ding^a ; ^{ding@cs.umb.edu} ; [Author Vitae] ; Feng Gao^b ; ^{feng.gao-1@nasa.gov} ; [Author Vitae] ; Tomasz F. Stepinski^c ; ^{stepintz@uc.edu} ; ^{tom@lpi.usra.edu} ; [Author Vitae]

关键词：Pattern recognition ; Active learning ; Semi-supervised learning ; Crater detection ; Mars

刊名：Neurocomputing

出版年：2012

9.Hierarchical curiosity loops and active sensing

作者：Goren Gordon ; ^{goren@gorengordon.com} ; Ehud Ahissar ^{Ehud.Ahissar@weizmann.ac.il}

关键词：Reinforcement learning ; Intrinsic reward ; Internal models ; Active sensing ; Whisker ; Vibrissa ; Touch ; Object localization

刊名：Neural Networks

出版年：2012

10.The impact of Technology-Enabled Active Learning (TEAL) implementation on student learning and teachers鈥?teaching in a high school context

作者：Ruey S. Shieh ; ^{rueys99@gmail.com}

关键词：Constructivist-oriented pedagogy ; Improving classroom teaching ; Teaching beliefs ; Technology-enhanced instruction

刊名：Computers and Education

出版年：2012

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