FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2068642301> ?p ?o ?g. }

• W2068642301 endingPage "806" @default.
• W2068642301 startingPage "800" @default.
• W2068642301 abstract "Many learning and heuristic search algorithms require tuning of parameters to achieve optimum performance. In stationary and deterministic problem domains this is usually achieved through off-line sensitivity analysis. However, this method breaks down in non-stationary and non-deterministic environments, where the optimal set of values for the parameters keep changing over time. What is needed in such scenarios is a meta-learning (ML) mechanism that can learn the optimal set of parameters on-line while the learning algorithm is trying to learn its target concept. In this paper, we present a simple meta-learning algorithm to learn the temperature parameter of the Softmax reinforcement-learning (RL) algorithm. We present results to show the efficacy of this meta-learning algorithm in two domains." @default.
• W2068642301 created "2016-06-24" @default.
• W2068642301 creator A5083426951 @default.
• W2068642301 date "2008-12-01" @default.
• W2068642301 modified "2023-09-24" @default.
• W2068642301 title "Meta-learning optimal parameter values in non-stationary environments" @default.
• W2068642301 cites W1533058732 @default.
• W2068642301 cites W1564592130 @default.
• W2068642301 cites W1596324102 @default.
• W2068642301 cites W1598796067 @default.
• W2068642301 cites W1600175013 @default.
• W2068642301 cites W1639032689 @default.
• W2068642301 cites W1989048657 @default.
• W2068642301 cites W2014239346 @default.
• W2068642301 cites W2022290342 @default.
• W2068642301 cites W2035174176 @default.
• W2068642301 cites W2121863487 @default.
• W2068642301 cites W2145680191 @default.
• W2068642301 cites W2160644528 @default.
• W2068642301 cites W2165675153 @default.
• W2068642301 cites W2904250082 @default.
• W2068642301 cites W2911283634 @default.
• W2068642301 cites W3124164442 @default.
• W2068642301 cites W99485931 @default.
• W2068642301 doi "https://doi.org/10.1016/j.knosys.2008.03.041" @default.
• W2068642301 hasPublicationYear "2008" @default.
• W2068642301 type Work @default.
• W2068642301 sameAs 2068642301 @default.
• W2068642301 citedByCount "6" @default.
• W2068642301 countsByYear W20686423012013 @default.
• W2068642301 countsByYear W20686423012015 @default.
• W2068642301 countsByYear W20686423012016 @default.
• W2068642301 countsByYear W20686423012018 @default.
• W2068642301 crossrefType "journal-article" @default.
• W2068642301 hasAuthorship W2068642301A5083426951 @default.
• W2068642301 hasConcept C111472728 @default.
• W2068642301 hasConcept C115903097 @default.
• W2068642301 hasConcept C117765406 @default.
• W2068642301 hasConcept C119857082 @default.
• W2068642301 hasConcept C126255220 @default.
• W2068642301 hasConcept C127413603 @default.
• W2068642301 hasConcept C138885662 @default.
• W2068642301 hasConcept C154945302 @default.
• W2068642301 hasConcept C162324750 @default.
• W2068642301 hasConcept C17061570 @default.
• W2068642301 hasConcept C173801870 @default.
• W2068642301 hasConcept C177264268 @default.
• W2068642301 hasConcept C187736073 @default.
• W2068642301 hasConcept C188441871 @default.
• W2068642301 hasConcept C199190896 @default.
• W2068642301 hasConcept C199360897 @default.
• W2068642301 hasConcept C21200559 @default.
• W2068642301 hasConcept C24326235 @default.
• W2068642301 hasConcept C2780451532 @default.
• W2068642301 hasConcept C2780586882 @default.
• W2068642301 hasConcept C2781002164 @default.
• W2068642301 hasConcept C33923547 @default.
• W2068642301 hasConcept C41008148 @default.
• W2068642301 hasConcept C50644808 @default.
• W2068642301 hasConcept C77967617 @default.
• W2068642301 hasConcept C8038995 @default.
• W2068642301 hasConcept C97541855 @default.
• W2068642301 hasConceptScore W2068642301C111472728 @default.
• W2068642301 hasConceptScore W2068642301C115903097 @default.
• W2068642301 hasConceptScore W2068642301C117765406 @default.
• W2068642301 hasConceptScore W2068642301C119857082 @default.
• W2068642301 hasConceptScore W2068642301C126255220 @default.
• W2068642301 hasConceptScore W2068642301C127413603 @default.
• W2068642301 hasConceptScore W2068642301C138885662 @default.
• W2068642301 hasConceptScore W2068642301C154945302 @default.
• W2068642301 hasConceptScore W2068642301C162324750 @default.
• W2068642301 hasConceptScore W2068642301C17061570 @default.
• W2068642301 hasConceptScore W2068642301C173801870 @default.
• W2068642301 hasConceptScore W2068642301C177264268 @default.
• W2068642301 hasConceptScore W2068642301C187736073 @default.
• W2068642301 hasConceptScore W2068642301C188441871 @default.
• W2068642301 hasConceptScore W2068642301C199190896 @default.
• W2068642301 hasConceptScore W2068642301C199360897 @default.
• W2068642301 hasConceptScore W2068642301C21200559 @default.
• W2068642301 hasConceptScore W2068642301C24326235 @default.
• W2068642301 hasConceptScore W2068642301C2780451532 @default.
• W2068642301 hasConceptScore W2068642301C2780586882 @default.
• W2068642301 hasConceptScore W2068642301C2781002164 @default.
• W2068642301 hasConceptScore W2068642301C33923547 @default.
• W2068642301 hasConceptScore W2068642301C41008148 @default.
• W2068642301 hasConceptScore W2068642301C50644808 @default.
• W2068642301 hasConceptScore W2068642301C77967617 @default.
• W2068642301 hasConceptScore W2068642301C8038995 @default.
• W2068642301 hasConceptScore W2068642301C97541855 @default.
• W2068642301 hasIssue "8" @default.
• W2068642301 hasLocation W20686423011 @default.
• W2068642301 hasOpenAccess W2068642301 @default.
• W2068642301 hasPrimaryLocation W20686423011 @default.
• W2068642301 hasRelatedWork W2068642301 @default.
• W2068642301 hasRelatedWork W2954428433 @default.
• W2068642301 hasRelatedWork W3095538999 @default.
• W2068642301 hasRelatedWork W3136151706 @default.
• W2068642301 hasRelatedWork W3196155444 @default.

• next