About: Multitask optimization

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Multi-task optimization is a paradigm in the optimization literature that focuses on solving multiple self-contained tasks simultaneously. The paradigm has been inspired by the well-established concepts of transfer learning and multi-task learning in predictive analytics. The key motivation behind multi-task optimization is that if optimization tasks are related to each other in terms of their optimal solutions or the general characteristics of their function landscapes, the search progress can be transferred to substantially accelerate the search on the other.

Attributes	Values
rdfs:label	Multitask optimization (en)
rdfs:comment	Multi-task optimization is a paradigm in the optimization literature that focuses on solving multiple self-contained tasks simultaneously. The paradigm has been inspired by the well-established concepts of transfer learning and multi-task learning in predictive analytics. The key motivation behind multi-task optimization is that if optimization tasks are related to each other in terms of their optimal solutions or the general characteristics of their function landscapes, the search progress can be transferred to substantially accelerate the search on the other. (en)
dbp:wikiPageUsesTemplate	dbt:Short_description dbt:Context
Subject	Machine learning
prov:wasDerivedFrom	http://en.wikipedia.org/wiki/Multitask_optimization?oldid=1065047534&ns=0
Wikipage page ID	58175832 (xsd:integer)
page length (characters) of wiki page	7813 (xsd:nonNegativeInteger)
Wikipage revision ID	1065047534 (xsd:integer)
Link from a Wikipage to another Wikipage	Machine learning Bayesian optimization Machine learning Crossover (genetic algorithm) Hyperparameter optimization Predictive analytics Paradigm Ensemble learning Gaussian process Implicit parallelism Evolutionary computation Transfer learning Multi-objective optimization Meta learning Multicriteria classification Multiple-criteria decision analysis
has abstract	Multi-task optimization is a paradigm in the optimization literature that focuses on solving multiple self-contained tasks simultaneously. The paradigm has been inspired by the well-established concepts of transfer learning and multi-task learning in predictive analytics. The key motivation behind multi-task optimization is that if optimization tasks are related to each other in terms of their optimal solutions or the general characteristics of their function landscapes, the search progress can be transferred to substantially accelerate the search on the other. The success of the paradigm is not necessarily limited to one-way knowledge transfers from simpler to more complex tasks. In practice an attempt is to intentionally solve a more difficult task that may unintentionally solve several smaller problems. (en)
foaf:isPrimaryTopicOf	http://en.wikipedia.org/wiki/Multitask_optimization
is Wikipage redirect of	Evolutionary multitasking Multitask optimisation
is Link from a Wikipage to another Wikipage of	Evolutionary multitasking Meta learning Multitask optimisation
is foaf:primaryTopic of	http://en.wikipedia.org/wiki/Multitask_optimization

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