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Statistical relational learning

Known as: SRL, PRM, Probabilistic relational model 
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 intelligenceAssociation rule learningBayesian networkCluster analysis

Broader (2)

Computational statisticsMachine learning

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2015
2015
Industrial system knowledge formalization to aid decision making in maintenance strategies assessment
2015
2015
A hybrid sampling strategy with optimized Probabilistic Roadmap Method
Probabilistic Roadmap Method(PRM) is sampling-based techniques being extensively used for virtual humans field. In this paper, we… 
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… 
2008
2008
Improving the Performance of Sampling-Based Motion Planning With Symmetry-Based Gap Reduction
Sampling-based nonholonomic and kinodynamic planning iteratively constructs solutions with sampled controls. A constructed… 
2008
2008
A bandwidth adaptive method for estimating end-to-end available bandwidth
  • Dawei XuD. Qian
  • 11th IEEE Singapore International Conference on…
  • 2008
  • Corpus ID: 28647260
The probe gap model (PGM) was proposed as a lightweight and fast available bandwidth estimation method. Compared to the probe… 
2007
2007
Chinese Named Entity Recognition with Cascaded Hybrid Model
We propose a high-performance cascaded hybrid model for Chinese NER. Firstly, we use Boosting, a standard and theoretically well… 
2006
2006
Resilient multicast using overlays
We introduce Probabilistic Resilient Multicast (PRM): a multicast data recovery scheme that improves data delivery ratios while… 
2003
2003
Statistical Relational Learning at U Penn
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… 
2002
2002
Generalizing the analysis of PRM
This paper presents it novel analysis of the probabilistic roadmap method (PRM) for path planning. We formulate the problem in… 
Highly Cited
2001
Highly Cited
2001
Customizing PRM roadmaps at query time
We propose an approach for building and querying probabilistic roadmaps. In the roadmap construction stage, we build coarse… 
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