FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2951949691> ?p ?o ?g. }

• W2951949691 endingPage "2111" @default.
• W2951949691 startingPage "2089" @default.
• W2951949691 abstract "We consider the problem of learning Relational Logistic Regression (RLR). Unlike standard logistic regression, the features of RLR are first-order formulae with associated weight vectors instead of scalar weights. We turn the problem of learning RLR to learning these vector-weighted formulae and develop a learning algorithm based on the recently successful functional-gradient boosting methods for probabilistic logic models. We derive the functional gradients and show how weights can be learned simultaneously in an efficient manner. Our empirical evaluation on standard data sets demonstrates the superiority of our approach over other methods for learning RLR." @default.
• W2951949691 created "2019-06-27" @default.
• W2951949691 creator A5033257344 @default.
• W2951949691 creator A5037636074 @default.
• W2951949691 creator A5044532113 @default.
• W2951949691 creator A5049799303 @default.
• W2951949691 creator A5053382180 @default.
• W2951949691 creator A5064323671 @default.
• W2951949691 creator A5065918431 @default.
• W2951949691 creator A5078428949 @default.
• W2951949691 date "2021-07-14" @default.
• W2951949691 modified "2023-10-16" @default.
• W2951949691 title "Structure learning for relational logistic regression: an ensemble approach" @default.
• W2951949691 cites W1013643069 @default.
• W2951949691 cites W1530558387 @default.
• W2951949691 cites W1535439311 @default.
• W2951949691 cites W1585529040 @default.
• W2951949691 cites W1604179321 @default.
• W2951949691 cites W1608748481 @default.
• W2951949691 cites W1678356000 @default.
• W2951949691 cites W1977970897 @default.
• W2951949691 cites W1987902506 @default.
• W2951949691 cites W1997945384 @default.
• W2951949691 cites W2021602734 @default.
• W2951949691 cites W2033072307 @default.
• W2951949691 cites W2034227939 @default.
• W2951949691 cites W2065606385 @default.
• W2951949691 cites W2119831128 @default.
• W2951949691 cites W2120247405 @default.
• W2951949691 cites W2121075864 @default.
• W2951949691 cites W2125922627 @default.
• W2951949691 cites W2144429462 @default.
• W2951949691 cites W2150475393 @default.
• W2951949691 cites W2150678881 @default.
• W2951949691 cites W2169992051 @default.
• W2951949691 cites W2219888463 @default.
• W2951949691 cites W2734531055 @default.
• W2951949691 cites W2746855033 @default.
• W2951949691 cites W2751933316 @default.
• W2951949691 cites W4294940931 @default.
• W2951949691 doi "https://doi.org/10.1007/s10618-021-00770-8" @default.
• W2951949691 hasPublicationYear "2021" @default.
• W2951949691 type Work @default.
• W2951949691 sameAs 2951949691 @default.
• W2951949691 citedByCount "2" @default.
• W2951949691 countsByYear W29519496912022 @default.
• W2951949691 countsByYear W29519496912023 @default.
• W2951949691 crossrefType "journal-article" @default.
• W2951949691 hasAuthorship W2951949691A5033257344 @default.
• W2951949691 hasAuthorship W2951949691A5037636074 @default.
• W2951949691 hasAuthorship W2951949691A5044532113 @default.
• W2951949691 hasAuthorship W2951949691A5049799303 @default.
• W2951949691 hasAuthorship W2951949691A5053382180 @default.
• W2951949691 hasAuthorship W2951949691A5064323671 @default.
• W2951949691 hasAuthorship W2951949691A5065918431 @default.
• W2951949691 hasAuthorship W2951949691A5078428949 @default.
• W2951949691 hasBestOaLocation W29519496912 @default.
• W2951949691 hasConcept C105795698 @default.
• W2951949691 hasConcept C119857082 @default.
• W2951949691 hasConcept C124101348 @default.
• W2951949691 hasConcept C151956035 @default.
• W2951949691 hasConcept C154945302 @default.
• W2951949691 hasConcept C169258074 @default.
• W2951949691 hasConcept C177877439 @default.
• W2951949691 hasConcept C2524010 @default.
• W2951949691 hasConcept C33923547 @default.
• W2951949691 hasConcept C41008148 @default.
• W2951949691 hasConcept C46686674 @default.
• W2951949691 hasConcept C49937458 @default.
• W2951949691 hasConcept C5655090 @default.
• W2951949691 hasConcept C57691317 @default.
• W2951949691 hasConcept C70153297 @default.
• W2951949691 hasConcept C83546350 @default.
• W2951949691 hasConceptScore W2951949691C105795698 @default.
• W2951949691 hasConceptScore W2951949691C119857082 @default.
• W2951949691 hasConceptScore W2951949691C124101348 @default.
• W2951949691 hasConceptScore W2951949691C151956035 @default.
• W2951949691 hasConceptScore W2951949691C154945302 @default.
• W2951949691 hasConceptScore W2951949691C169258074 @default.
• W2951949691 hasConceptScore W2951949691C177877439 @default.
• W2951949691 hasConceptScore W2951949691C2524010 @default.
• W2951949691 hasConceptScore W2951949691C33923547 @default.
• W2951949691 hasConceptScore W2951949691C41008148 @default.
• W2951949691 hasConceptScore W2951949691C46686674 @default.
• W2951949691 hasConceptScore W2951949691C49937458 @default.
• W2951949691 hasConceptScore W2951949691C5655090 @default.
• W2951949691 hasConceptScore W2951949691C57691317 @default.
• W2951949691 hasConceptScore W2951949691C70153297 @default.
• W2951949691 hasConceptScore W2951949691C83546350 @default.
• W2951949691 hasIssue "5" @default.
• W2951949691 hasLocation W29519496911 @default.
• W2951949691 hasLocation W29519496912 @default.
• W2951949691 hasOpenAccess W2951949691 @default.
• W2951949691 hasPrimaryLocation W29519496911 @default.
• W2951949691 hasRelatedWork W3001440478 @default.
• W2951949691 hasRelatedWork W3151529617 @default.
• W2951949691 hasRelatedWork W3159367627 @default.
• W2951949691 hasRelatedWork W3159988495 @default.

• next