"as"的相关文档

标签“as”的相关文档，共29条

Dropout as a Structured Shrinkage Prior
DropoutasastructuredShrinkagePriorEricNalisnick1JoséMiguelHernández-Lobato123PadhraicSmyth4Abstractexplaindropout’sinner-workingsandsuccessarealsoplen-tiful.Togiveafewexamples,Srivastavaetal.(20...
Dropout Structured as Prior Shrinkage
2023-11-13 14:46:581123832.73 KB7
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Automatic Classifiers as Scientific Instruments One Step Further Away from Ground-Truth
AutomaticClassiﬁersasScientiﬁcInstruments:OneStepFurtherAwayfromGround-TruthJacobWhitehill1AnandRamakrishnan1Abstractotherﬁeldsbyservingasscientiﬁcinstrumentsthatcanmeasurebehavioral,medical,so...
Automatic Classifiers as One Scientific
2023-11-13 14:46:2711391.83 MB20
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TAPas Tricks to Accelerate (encrypted) Prediction as a Service
TAPas:TrickstoAccelerate(encrypted)PredictionasaserviceAmartyasanyal12MattJ.Kusner23Adria`Gasco´n23VarunKanade12Abstractconcerns.Examplesincludeassistinginmedicaldiagnoses(Kononenko,2001;Bleckeret...
to Prediction as Encrypted TAPAS
2023-11-13 12:00:491647598.71 KB24
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Policy Optimization as Wasserstein Gradient Flows
PolicyOptimizationasWassersteinGradientFlowsRuiyiZhang1ChangyouChen2ChunyuanLi1LawrenceCarin1Abstractwiththeenvironment.Policyoptimizationisacorecomponentofrein-astandardtechniqueforpolicylearningi...
Optimization Gradient Policy Wasserstein Flows
2023-11-13 12:00:2619751.66 MB14
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Noisy Natural Gradient as Variational Inference
NoisyNaturalGradientasVariationalInferenceGuodongZhang12ShengyangSun12DavidDuvenaud12RogerGrosse12Abstract&Welling,2017),butﬁttingsuchmodelscanbeexpensivewithoutfurtherapproximations.VariationalBa...
Inference Variational Gradient Natural Noisy
2023-11-13 12:00:1613002.77 MB30
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Graph Networks as Learnable Physics Engines for Inference and Control
GraphNetworksasLearnablePhysicsEnginesforInferenceandControlAlvaroSanchez-Gonzalez1NicolasHeess1JostTobiasSpringenberg1JoshMerel1MartinRiedmiller1RaiaHadsell1PeterBattaglia1AbstractPendulumCartpole...
for Networks Graph as Learnable
2023-11-13 11:59:427002.04 MB16
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ADMM and Accelerated ADMM as Continuous Dynamical Systems
ADMMandAcceleratedADMMasContinuousDynamicalSystemsGuilhermeFranc¸a1DanielP.Robinson1Rene´Vidal1Abstract1.1.RelatedworkRecently,therehasbeenanincreasinginterestinPerhapsthesimplestconnectionbetwee...
ADMM and Accelerated Systems Continuous
2023-11-13 11:58:591443402.14 KB13
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OptNet Differentiable Optimization as a Layer in Neural Networks
OptNet:DifferentiableOptimizationasaLayerinNeuralNetworksBrandonAmos1J.ZicoKolter1Abstracttalcanreducetheoveralldepthofthenetworkwhilepre-servingrichnessofrepresentation.Speciﬁcally,webuildaThispa...
Neural Optimization in Differentiable Layer
2023-11-12 20:44:591518600.71 KB6
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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++
2023-11-12 20:44:541776415.39 KB12
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