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Matching Road Network Combining Hierarchical Strokes and Probabilistic Relaxation Method

Lin Yang, Zejun Zuo, Run Wang, Yaqin Ye, Maosheng Hu
2014 Open Automation and Control Systems Journal  
The detailed matching is implemented by an iterative probability relaxation method.  ...  The progress of the matching method adopts recursive method and gives consideration to both global consistency and local similarity of homonymous road features.  ...  YF Zhang and BS Yang [14, 15] proposed a probabilistic matching unit relaxation method to solve the 1 : 0 matching problem and two-way matching problem.  ... 
doi:10.2174/1874444301406010268 fatcat:uhlxcmaihnd2tcdyexpv73vtga

Hinge-Loss Markov Random Fields and Probabilistic Soft Logic [article]

Stephen H. Bach, Matthias Broecheler, Bert Huang, Lise Getoor
2017 arXiv   pre-print
Many important problem areas are both richly structured and large scale, from social and biological networks, to knowledge graphs and the Web, to images, video, and natural language.  ...  We unite three approaches from the randomized algorithms, probabilistic graphical models, and fuzzy logic communities, showing that all three lead to the same inference objective.  ...  Disclaimer: The views and conclusions contained herein are those of the authors and should 7. An open source implementation, tutorials, and data sets are available at  ... 
arXiv:1505.04406v3 fatcat:msjfalt6nrfxfo37fe5yrc536y

Probabilistic Topic Models

David Blei, Lawrence Carin, David Dunson
2010 IEEE Signal Processing Magazine  
We discuss its connections to probabilistic modeling, and describe two kinds of algorithms for topic discovery.  ...  These extensions have been developed by relaxing some of the statistical assumptions of LDA, incorporating meta-data into the analysis of the documents, and using similar kinds of models on a diversity  ...  Summary We have surveyed probabilistic topic models, a suite of algorithms that provide a statistical solution to the problem of managing large archives of documents.  ... 
doi:10.1109/msp.2010.938079 pmid:25104898 pmcid:PMC4122269 fatcat:pignwt65obhyxinw4b4vfvstxi

Probabilistic topic models

David Blei
2011 Proceedings of the 17th ACM SIGKDD International Conference Tutorials on - KDD '11 Tutorials  
We discuss its connections to probabilistic modeling, and describe two kinds of algorithms for topic discovery.  ...  These extensions have been developed by relaxing some of the statistical assumptions of LDA, incorporating meta-data into the analysis of the documents, and using similar kinds of models on a diversity  ...  Summary We have surveyed probabilistic topic models, a suite of algorithms that provide a statistical solution to the problem of managing large archives of documents.  ... 
doi:10.1145/2107736.2107741 fatcat:patt4fqxrba35pxono3sbeo2j4

Probabilistic Temporal Reasoning [chapter]

Steve Hanks, David Madigan
2005 Foundations of Artificial Intelligence  
Work in probabilistic temporal reasoning tries to relax some or all of these assumptions, addressing situations where the reasoner has partial information about the state and events, and where subsequent  ...  We will begin with a summary of the deterministic problem, based on the Yale Shooting Problem example [Hanks and McDermott, 1987].  ...  In this model, the relationship between state and observation is state independent, though this assumption could easily be relaxed.  ... 
doi:10.1016/s1574-6526(05)80012-4 fatcat:tud2u7yjuzc4de4lmz3ffq4dxq

Engineering a Conformant Probabilistic Planner

N. Onder, G. C. Whelan, L. Li
2006 The Journal of Artificial Intelligence Research  
We explain the successes and difficulties encountered during the design and implementation of Probapop.  ...  We present a partial-order, conformant, probabilistic planner, Probapop which competed in the blind track of the Probabilistic Planning Competition in IPC-4.  ...  Smith, and the anonymous reviewers for their very helpful comments.  ... 
doi:10.1613/jair.1701 fatcat:wvrn55jg4zdl3ax7hlt5r2vtu4

Probabilistic N -k failure-identification for power systems

Kaarthik Sundar, Carleton Coffrin, Harsha Nagarajan, Russell Bent
2018 Networks  
A general cutting-plane algorithm is proposed to solve the convex relaxation and linear approximations of the N-k problem.  ...  This paper considers a probabilistic generalization of the N-k failure-identification problem in power transmission networks, where the probability of failure of each component in the network is known  ...  F dc is still an open question.  ... 
doi:10.1002/net.21806 fatcat:bppmfhq5ozblll276sutstuny4

Relax, Compensate and Then Recover [chapter]

Arthur Choi, Adnan Darwiche
2011 Lecture Notes in Computer Science  
We further discuss the relationship between this framework for approximate inference and an approach to exact inference based on symbolic reasoning.  ...  First, our notion of an approximation is based on "relaxing" equality constraints, for the purposes of simplifying a problem so that it can be solved more readily.  ...  A B X Y (b) Relaxing the equivalence constraint of 2(a). Approximate Probabilistic Inference Consider now the problem of approximate probabilistic inference.  ... 
doi:10.1007/978-3-642-25655-4_16 fatcat:vrsjf5zs2nhdtmg4spleghv4vu

Reliability-Aware Probabilistic Reserve Procurement [article]

Lars Herre, Pierre Pinson, Spyros Chatzivasileiadis
2021 arXiv   pre-print
The proposed probabilistic reserve procurement allows restricted reserve providers to enter the market, thereby increases liquidity and has the potential to lower procurement costs in power systems with  ...  The original non-convex market clearing problem is approximated by a MILP reformulation.  ...  Energy markets with probabilistic offers have been investigated in [2] . Reference [3] analysed aggregation problems and risky power markets.  ... 
arXiv:2110.11445v2 fatcat:7betjiaf2ffnhaegjvibwni3zi

On Probabilistic Application Compliance

Antonio La Marra, Fabio Martinelli, Andrea Saracino, Alessandro Aldini
2016 2016 IEEE Trustcom/BigDataSE/ISPA  
With these objectives in view, in this paper we define a probabilistic extension of the Security-by-Contract model, and we show its impact in realworld scenarios through the analysis of several practical  ...  This also opens the possibility to balance the application of (expensive) enforcement mechanisms with the security guarantees.  ...  The present work is not necessarily focused on malicious app, and potentially any kind of policy can be applied.  ... 
doi:10.1109/trustcom.2016.0283 dblp:conf/trustcom/MarraMSA16 fatcat:ldk4auwfjjeilmanuyjxfln4wm

Probabilistic Label Relation Graphs with Ising Models [article]

Nan Ding and Jia Deng and Kevin Murphy and Hartmut Neven
2015 arXiv   pre-print
In this paper, we extend the HEX model to allow for soft or probabilistic relations between labels, which is useful when there is uncertainty about the relationship between two labels (e.g., an antelope  ...  To jointly model hierarchy and exclusion relations, the notion of a HEX (hierarchy and exclusion) graph was introduced in [7].  ...  Probabilistic HEX models In this section, we introduce an extension of the HEX model to allow for soft or probabilistic relationships between labels.  ... 
arXiv:1503.01428v3 fatcat:eoiz7ijsxndb3jr32gnfkitzsy

Learning probabilistic logic models from probabilistic examples

Jianzhong Chen, Stephen Muggleton, José Santos
2008 Machine Learning  
sub-explanations) for G (and subgoals of G) are probabilistically exclusive to each other.  ...  Our results demonstrate that the PILP approach provides a way of learning probabilistic logic models from probabilistic examples, and the PILP models learned from probabilistic examples lead to a significant  ...  Acknowledgements The authors would like to acknowledge support from the Royal Academy of Engineering/Microsoft Research Chair on 'Automated Microfluidic Experimentation using Probabilistic Inductive Logic  ... 
doi:10.1007/s10994-008-5076-4 pmid:19888348 pmcid:PMC2771423 fatcat:vpnu5djquncwfgsfvxlzsaoe3i

Pairing for Generation of Synthetic Populations: the Direct Probabilistic Pairing method [article]

Samuel Thiriot, Marie Sevenet
2020 arXiv   pre-print
We propose a theoretical framework to tackle this problem. We then highlight how this problem is over-constrained and requires relaxation of some constraints to be solved.  ...  We propose a method to solve the problem analytically which lets the user select which input data should be preserved and adapts the others in order to make the data consistent.  ...  Acknowledgements This study was funded by the EDF energy utility and the EIFER European Institute For Energy Research.  ... 
arXiv:2002.03853v1 fatcat:gab6mxje7ze7xpgcrbbwulosre

Probabilistic ontology for net-centric fusion

Kathryn Blackmond Laskey, Paulo C.G. da Costa, Edward J. Wright, Kenneth J. Laskey
2007 2007 10th International Conference on Information Fusion  
Among these is the need for semantic interoperability among systems with different internal data models and vocabularies.  ...  This paper proposes the use of probabilistic ontologies within a service-oriented architecture as a means to enable semantic interoperability in net-centric fusion systems.  ...  Probabilistic ontologies can also mediate this inference problem.  ... 
doi:10.1109/icif.2007.4408012 dblp:conf/fusion/LaskeyCWL07 fatcat:c4jndpdgcbd2llpfzumfqhlxce

Probabilistic Data Analysis with Probabilistic Programming [article]

Feras Saad, Vikash Mansinghka
2016 arXiv   pre-print
Probabilistic techniques are central to data analysis, but different approaches can be difficult to apply, combine, and compare.  ...  This paper introduces composable generative population models (CGPMs), a computational abstraction that extends directed graphical models and can be used to describe and compose a broad class of probabilistic  ...  and discussions.  ... 
arXiv:1608.05347v1 fatcat:cy3ddgzb5rdzxctz7lfzoecm4u
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