Revision as of 07:04, 27 March 2018 edit Eriq.augustine (talk \| contribs) 29 edits Updated some old references to point to the current material (the LINQS lab has moved from UMD to UCSC). Touched up the description to more closely match the newest PSL journal article. ← Previous edit		Revision as of 18:37, 5 February 2020 edit undo JCW-CleanerBot (talk \| contribs) Bots 137,069 edits m →top: task, replaced: Journal of Machine Learning Research (JMLR) → Journal of Machine Learning Research Tag: AWB Next edit →
Line 1: '''Probabilistic soft logic (PSL)''' is a [[Statistical relational learning\|SRL]] framework for collective, [[probabilistic reasoning]] in relational domains. PSL uses [[first order logic]] rules as a template language for [[graphical model]]s over [[random variable]]s with soft truth values from the interval [0,1].<ref>{{cite journal \|last1=Bach \|first1=Stephen \|last2=Broecheler \|first2=Matthias \|last3=Huang \|first3=Bert \|last4=Getoor \|first4=Lise \|date=2017 \|title=Hinge-Loss Markov Random Fields and Probabilistic Soft Logic \|journal=Journal of Machine Learning Research ~~(JMLR)~~ \|volume=18 \|pages=~~1-67~~1–67}}</ref>. == Description ==

Probabilistic soft logic: Difference between revisions