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Statistical relational learning
Known as:
SRL
, PRM
, Probabilistic relational model
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Statistical relational learning (SRL) is a subdiscipline of artificial intelligence and machine learning that is concerned with domain models that…
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Related topics
Related topics
23 relations
Artificial intelligence
Association rule learning
Bayesian network
Cluster analysis
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Broader (2)
Computational statistics
Machine learning
Papers overview
Semantic Scholar uses AI to extract papers important to this topic.
2017
2017
Soft quantification in statistical relational learning
G. Farnadi
,
Stephen H. Bach
,
Marie-Francine Moens
,
L. Getoor
,
M. D. Cock
Machine-mediated learning
2017
Corpus ID: 43407720
We present a new statistical relational learning (SRL) framework that supports reasoning with soft quantifiers, such as “most…
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2015
2015
Industrial system knowledge formalization to aid decision making in maintenance strategies assessment
Gabriela Medina-Oliva
,
P. Weber
,
B. Iung
Engineering applications of artificial…
2015
Corpus ID: 22244594
2015
2015
A hybrid sampling strategy with optimized Probabilistic Roadmap Method
Fang Yuan
,
Jiahong Liang
,
Yue-wen Fu
,
Han-Cheng Xu
,
Ke Ma
International Conference on Fuzzy Systems and…
2015
Corpus ID: 23087043
Probabilistic Roadmap Method(PRM) is sampling-based techniques being extensively used for virtual humans field. In this paper, we…
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Review
2013
Review
2013
Statistical Relational Learning
H. Blockeel
Handbook on Neural Information Processing
2013
Corpus ID: 34343661
Relational learning refers to learning from data that have a complex structure. This structure may be either internal (a data…
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2008
2008
A statistical relational model for trust learning
Achim Rettinger
,
Matthias Nickles
,
Volker Tresp
Adaptive Agents and Multi-Agent Systems
2008
Corpus ID: 14930411
We address the learning of trust based on past observations and context information. We argue that from the truster's point of…
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2008
2008
Improving the Performance of Sampling-Based Motion Planning With Symmetry-Based Gap Reduction
P. Cheng
,
Emilio Frazzoli
,
S. LaValle
IEEE Transactions on robotics
2008
Corpus ID: 767929
Sampling-based nonholonomic and kinodynamic planning iteratively constructs solutions with sampled controls. A constructed…
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2006
2006
Resilient multicast using overlays
Suman Banerjee
,
Seungjoon Lee
,
Bobby Bhattacharjee
,
A. Srinivasan
TNET
2006
Corpus ID: 5346686
We introduce Probabilistic Resilient Multicast (PRM): a multicast data recovery scheme that improves data delivery ratios while…
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2003
2003
Statistical Relational Learning at U Penn
Alexandrin Popescul
,
L. Ungar
2003
Corpus ID: 60597141
The methyl, ethyl, n-propy, 2-(acetylamino)ethyl, or 1-(2,3-dihydroxy)propyl ester of E-(3R,5S)-7-(4'-fluoro-3,3',5-trimethyl[1,1…
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2002
2002
Generalizing the analysis of PRM
Andrew M. Ladd
,
L. Kavraki
Proceedings IEEE International Conference on…
2002
Corpus ID: 7734207
This paper presents it novel analysis of the probabilistic roadmap method (PRM) for path planning. We formulate the problem in…
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Highly Cited
2001
Highly Cited
2001
Customizing PRM roadmaps at query time
Guang Song
,
Shawna Miller
,
N. Amato
Proceedings ICRA. IEEE International Conference…
2001
Corpus ID: 12232264
We propose an approach for building and querying probabilistic roadmaps. In the roadmap construction stage, we build coarse…
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