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检索条件"主题词=Probabilistic Graphical Models"
398 条 记 录,以下是211-220 订阅
排序:
Cauchy graphical models  12
Cauchy Graphical Models
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12th International Conference on probabilistic graphical models (PGM)
作者: Muvunza, Taurai Li, Yang Kuruoglu, Ercan Engin Tsinghua Univ Tsinghua Berkeley Shenzhen Inst Inst Data & Informat Shenzhen Int Grad Sch Beijing Peoples R China
A common approach to learning Bayesian networks involves specifying an appropriately chosen family of parameterized probability density such as Gaussian. However, the distribution of most real-life data is leptokurtic... 详细信息
来源: 评论
A Scientific Inquiry Fusion Theory for High-Level Information Fusion  17
A Scientific Inquiry Fusion Theory for High-Level Informatio...
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17th International Conference on Information Fusion (FUSION)
作者: Ao, Zhuoyun Scholz, Jason Oxenham, Martin Joint and Operations Analysis Division Defence Science Technology Organisation South Australia Australia
The Joint Directors of Laboratories fusion model is adequate as a functional description, but falls short as a formal design guide for the application of logical inference under uncertainty for high-level information ... 详细信息
来源: 评论
The PC-Algorithm of the Algebraic Bayesian Network Secondary Structure Training  1
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19th Russian Conference on Artificial Intelligence (RCAI)
作者: Kharitonov, Nikita Abramov, Maxim Tulupyev, Alexander St Petersburg State Univ St Petersburg Russia Russian Acad Sci St Petersburg Fed Res Ctr St Petersburg Russia
Algebraic Bayesian networks and Bayesian belief networks are one of the probabilistic graphical models. One of the main tasks which need to be solved during the networks' handling is the model structure training. ... 详细信息
来源: 评论
Protein Secondary Structure Prediction using Large Margin Methods
Protein Secondary Structure Prediction using Large Margin Me...
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8th IEEE/ACIS International Conference on Computer and Information Science
作者: Tang, Buzhou Wang, Xuan Wang, Xiaolong Harbin Inst Technol Shenzhen Grad Sch Shenzhen 518055 Peoples R China
Protein secondary structure prediction is an important step to understanding protein tertiary structure. Recent studies indicate that the correlation between neighboring secondary structures are beneficial to improve ... 详细信息
来源: 评论
WHAT COULD BE ACHIEVED WITH A MILLION QUBITS QUANTUM ANNEALER IN REMOTE SENSING?
WHAT COULD BE ACHIEVED WITH A MILLION QUBITS QUANTUM ANNEALE...
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IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
作者: Gawron, Piotr Sadowski, Przemyslaw Glomb, Przemyslaw Gardas, Bartlomiej van Waveren, Matthijs Forray, Clement Pasero, Guillaume Savinaud, Mickael Brunet, Pierre-Marie Faucoz, Orphee Puchala, Zbigniew Pawela, Lukasz PAS Nicolaus Copernicus Astron Ctr AstroCeNT Rektorska 4 PL-00614 Warsaw Poland PAS Inst Theoret & Appl Informat Baltycka 5 PL-44100 Gliwice Poland CS GRP 6 Rue Brindejonc Moulinais F-31506 Toulouse France CNES 10 Ave Edouard Belin F-31401 Toulouse France
We discuss the applicability of large quantum annealers for the purpose of processing Remote Sensing images. We show an application of currently existing quantum annealers for the purpose of post-processing segmentati... 详细信息
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A Countable State PGM for Tracking Entity Movement  15
A Countable State PGM for Tracking Entity Movement
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15th IEEE International Conference on Machine Learning and Applications (ICMLA)
作者: Zajic, Tim Raytheon Integrated Def Syst 235 Presidential Way Woburn MA 01801 USA
We consider a probabilistic graphical model for the problem of tracking entities moving among a finite set of sites. The observations consist of counts of the number of entities at sites and during movement between si... 详细信息
来源: 评论
SPATIAL-TEMPORAL CONDITIONAL RANDOM FIELD BASED MODEL FOR CROP RECOGNITION IN TROPICAL REGIONS  37
SPATIAL-TEMPORAL CONDITIONAL RANDOM FIELD BASED MODEL FOR CR...
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IEEE International Geoscience & Remote Sensing Symposium
作者: Achanccaray, P. Feitosa, R. Q. Rottensteiner, F. Sanches, I. D. Heipke, C. Pontifical Catholic Univ Rio de Janeiro Dept Elect Engn Rio De Janeiro Brazil Univ Estado Rio De Janeiro Dept Comp Engn Rio De Janeiro Brazil Leibniz Univ Hannover Inst Photogrammetry & GeoInformat Hannover Germany Natl Inst Space Res Remote Sensing Div Sao Jose Dos Campos Brazil
This work presents a spatio-temporal Conditional Random Field (CRF) based model for crop recognition from multi-temporal remote sensing image sequences. The association potential at each image site is based on the cla... 详细信息
来源: 评论
Multi-Label Inference for Crowdsourcing  18
Multi-Label Inference for Crowdsourcing
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24th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)
作者: Zhang, Jing Wu, Xindong Nanjing Univ Sci & Technol Sch Comp Sci & Engn 200 Xiaolingwei St Nanjing 210094 Jiangsu Peoples R China Univ Louisiana Lafayette Sch Comp & Informat 222 James R Oliver Hall Lafayette LA 70504 USA
When acquiring labels from crowdsourcing platforms, a task may be designed to include multiple labels and the values of each label may belong to a set of various distinct options, which is the so-called multi-class mu... 详细信息
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Locally averaged Bayesian Dirichlet metrics for learning the structure and the parameters of Bayesian networks
Locally averaged Bayesian Dirichlet metrics for learning the...
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11th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSARU)
作者: Cano, Andres Gomez-Olmedo, Manuel Masegosa, Andres R. Moral, Serafin Univ Granada Dept Comp Sci & Artificial Intelligence E-18071 Granada Spain
The marginal likelihood of the data computed using Bayesian score metrics is at the core of score+search methods when learning Bayesian networks from data. However, common formulations of those Bayesian score metrics ... 详细信息
来源: 评论
Unifying Logical and Statistical AI  16
Unifying Logical and Statistical AI
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31st Annual ACM-IEEE Symposium on Logic in Computer Science (LICS)
作者: Domingos, Pedro Lowd, Daniel Kok, Stanley Nath, Aniruddh Poon, Hoifung Richardson, Matthew Singla, Parag Univ Washington Seattle WA 98195 USA Univ Oregon Eugene OR 97403 USA Singapore Univ Technol & Design Singapore Singapore Google Mountain View CA USA Microsoft Res Mountain View CA USA Indian Inst Technol Delhi India
Intelligent agents must be able to handle the complexity and uncertainty of the real world. Logical AI has focused mainly on the former, and statistical AI on the latter. Markov logic combines the two by attaching wei... 详细信息
来源: 评论