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检索条件"主题词=Probabilistic Graphical Models"
399 条 记 录,以下是181-190 订阅
排序:
A hybrid approach to dialogue management based on probabilistic rules
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COMPUTER SPEECH AND LANGUAGE 2015年 第1期34卷 232-255页
作者: Lison, Pierre Univ Oslo Dept Informat Language Technol Grp N-0316 Oslo Norway
We present a new modelling framework for dialogue management based on the concept of probabilistic rules. probabilistic rules are defined as structured mappings between logical conditions and probabilistic effects. Th... 详细信息
来源: 评论
AMIDST: A Java toolbox for scalable probabilistic machine learning
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KNOWLEDGE-BASED SYSTEMS 2019年 163卷 595-597页
作者: Masegosa, Andres R. Martinez, Ana M. Ramos-Lopez, Dario Cabanas, Rafael Salmeron, Antonio Langseth, Helge Nielsen, Thomas D. Madsen, Anders L. Univ Almeria ES-04120 Almeria Spain Aalborg Univ DK-9220 Aalborg Denmark Norwegian Univ Sci & Technol NO-7491 Trondheim Norway HUGIN EXPERT AS DK-9000 Aalborg Denmark Rey Juan Carlos Univ ES-28933 Madrid Spain
The AMIDST Toolbox is an open source Java software for scalable probabilistic machine learning with a special focus on (massive) streaming data. The toolbox supports a flexible modelling language based on probabilisti... 详细信息
来源: 评论
graphical models
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STATISTICAL SCIENCE 2004年 第1期19卷 140-155页
作者: Jordan, MI Univ Calif Berkeley Div Comp Sci Berkeley CA 94720 USA Univ Calif Berkeley Dept Stat Berkeley CA 94720 USA
Statistical applications in fields such as bioinformatics, information retrieval, speech processing, image processing and communications often involve large-scale models in which thousands or millions of random variab... 详细信息
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The dynamic chain event graph
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ELECTRONIC JOURNAL OF STATISTICS 2015年 第2期9卷 2130-2169页
作者: Barclay, Lorna M. Collazo, Rodrigo A. Smith, Jim Q. Thwaites, Peter A. Nicholson, Ann E. Univ Warwick Dept Stat Coventry CV4 7AL W Midlands England Univ Leeds Sch Math Leeds LS2 9JT W Yorkshire England Monash Univ Fac Informat Technol Clayton Vic 3800 Australia
In this paper we develop a formal dynamic version of Chain Event Graphs (CEGs), a particularly expressive family of discrete graphical models. We demonstrate how this class links to semi-Markov models and provides a c... 详细信息
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Accurate prediction for atomic-level protein design and its application in diversifying the near-optimal sequence space
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PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS 2009年 第3期75卷 682-705页
作者: Fromer, Menachem Yanover, Chen Hebrew Univ Jerusalem Sch Engn & Comp Sci IL-91904 Jerusalem Israel Fred Hutchinson Canc Res Ctr Program Computat Biol Seattle WA 98104 USA
The task of engineering a protein to assume a target three-dimensional structure is known as protein design. Computational search algorithms are devised to predict a minimal energy amino acid sequence for a particular... 详细信息
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Machine learning in bioinformatics
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BRIEFINGS IN BIOINFORMATICS 2006年 第1期7卷 86-112页
作者: Larranaga, Pedro Calvo, Borja Santana, Roberto Bielza, Concha Galdiano, Josu Inza, Inaki Lozano, Jose A. Armananzas, Ruben Santafe, Guzman Perez, Aritz Robles, Victor Univ Basque Country Dept Comp Sci & Artificial Intelligence Intelligent Syst Grp San Sebastian 20018 Spain Madrid Tech Univ Sch Comp Sci Madrid Spain Harvard Univ Sch Med Cambridge MA 02138 USA Univ Politecn Madrid Dept Comp Syst Architecture & Technol E-28040 Madrid Spain
This article reviews machine learning methods for bioinformatics. It presents modelling methods, such as supervised classification, clustering and probabilistic graphical models for knowledge discovery, as well as det... 详细信息
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Fast local search methods for solving limited memory influence diagrams
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INTERNATIONAL JOURNAL OF APPROXIMATE REASONING 2016年 68卷 230-245页
作者: Maua, Denis Deratani Cozman, Fabio Gagliardi Univ Sao Paulo Inst Matemat & Estat BR-05508090 Sao Paulo Brazil Univ Sao Paulo Escola Politecn BR-05508030 Sao Paulo Brazil
Limited memory influence diagrams are graph-based models that describe decision problems with limited information such as planning with teams and/or agents with imperfect recall. Solving a (limited memory) influence d... 详细信息
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Exploiting Sparsity in Hyperspectral Image Classification via graphical models
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IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 2013年 第3期10卷 505-509页
作者: Srinivas, Umamahesh Chen, Yi Monga, Vishal Nasrabadi, Nasser M. Tran, Trac D. Penn State Univ Dept Elect Engn University Pk PA 16802 USA Johns Hopkins Univ Dept Elect & Comp Engn Baltimore MD 21218 USA USA Res Lab Adelphi MD 20783 USA
A significant recent advance in hyperspectral image (HSI) classification relies on the observation that the spectral signature of a pixel can be represented by a sparse linear combination of training spectra from an o... 详细信息
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Behavior Priors for Efficient Reinforcement Learning
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JOURNAL OF MACHINE LEARNING RESEARCH 2022年 第1期23卷 1-68页
作者: Tirumala, Dhruva Galashov, Alexandre Noh, Hyeonwo Hasenclever, Leonard Pascanu, Razvan Schwarz, Jonathan Desjardins, Guillaume Czarnecki, Wojciech Marian Ahuja, Arun Teh, Yee Whye Heess, Nicolas DeepMind R714-18 Handyside St London England UCL London WC1E 6BT England OpenAI 3180 18th St San Francisco CA 94110 USA
As we deploy reinforcement learning agents to solve increasingly challenging problems, methods that allow us to inject prior knowledge about the structure of the world and ef-fective solution strategies becomes increa... 详细信息
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graphical models for interactive POMDPs: representations and solutions
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AUTONOMOUS AGENTS AND MULTI-AGENT SYSTEMS 2009年 第3期18卷 376-416页
作者: Doshi, Prashant Zeng, Yifeng Chen, Qiongyu Univ Georgia Inst AI Athens GA 30602 USA Aalborg Univ Dept Comp Sci DK-9220 Aalborg Denmark Natl Univ Singapore Dept Comp Sci Singapore 117548 Singapore Univ Georgia Dept Comp Sci Athens GA 30602 USA
We develop new graphical representations for the problem of sequential decision making in partially observable multiagent environments, as formalized by interactive partially observable Markov decision processes (I-PO... 详细信息
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