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An Inference-Based Policy Gradient Method for Learning Options
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Learning for An Gradient Policy
2023-11-13 11:59:02585701.32 KB26
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A Semismooth Newton Method for Fast, Generic Convex Programming
ASemismoothNewtonMethodforFast,GenericConvexProgrammingAlnurAli1EricWong1J.ZicoKolter2Abstracti.e.,thespaceofm×mpositivesemideﬁnitematricesSm+,yieldsasemideﬁniteprogram;andtakingKasthesecond-Wei...
for Newton Fast Convex Method
2023-11-12 20:45:341041765.24 KB3
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SARAH A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient
SARAH:ANovelMethodforMachineLearningProblemsUsingStochasticRecursiveGradientLamM.Nguyen1JieLiu1KatyaScheinberg12MartinTaka´cˇ1AbstractProblemsofthistypearisefrequentlyinsupervisedlearn-Inthispape...
Learning for Machine Method SARAH
2023-11-12 20:45:11513557.46 KB12
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Nyström Method with Kernel K-means++ Samples as Landmarks
Nystro¨mMethodwithKernelK-means++SamplesasLandmarksDinoOglic12ThomasGa¨rtner2AbstractoreigendecompositionwhichscaleasOn3.ToovercomethiscomputationalshortcomingandscalekernelMethodsWeinvestigate,t...
Kernel with Method Nystr K-means++
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Dissipativity Theory for Nesterov’s Accelerated Method
DissipativityTheoryforNesterov’sAcceleratedMethodBinHu1LaurentLessard1Abstracttories.OnceaLyapunovfunctionisfound,onecanrelatetherateofdecreaseofthisinternalenergytotherateofInthispaper,weadaptthe...
for Accelerated Dissipativity Theory Nesterov
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An Inference-Based Policy Gradient Method for Learning Options

A Semismooth Newton Method for Fast, Generic Convex Programming

SARAH A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient

Nyström Method with Kernel K-means++ Samples as Landmarks

Dissipativity Theory for Nesterov’s Accelerated Method