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标签“Features”的相关文档，共22条

Quantization Algorithms for Random Fourier Features
QuantizationAlgorithmsforRandomFourierFeaturesXiaoyunLi,PingLiCognitiveComputingLabBaiduResearch10900NE8thStBellevueWA98004USA{lixiaoyun996,pingli98}@gmail.comAbstract1.IntroductionThemethodofrando...
for Algorithms random Features Fourier
2023-11-16 19:28:36606832.7 KB7
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Policy Caches with Successor Features
PolicyCacheswithSuccessorFeaturesMarkNemecek1RonaldParr1Abstracttaskswhichvaryintheirrewardfunctions,butwherethedynamicsremainthesame.Althoughlimitedinscope,thisTransferinreinforcementlearningisbas...
with Policy Features Successor Caches
2023-11-16 19:28:2919765.25 MB19
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Examining and Combating Spurious Features under Distribution Shift
ExaminingandCombatingSpuriousFeaturesunderDistributionShiftChuntingZhou1XuezheMa2PaulMichel1GrahamNeubig1Abstract(a)ERM(b)GroupDRO[clean](average=93.3%robust=83.4%)(average=96.5%robust=95.8%)Acentr...
and under Distribution Features Spurious
2023-11-16 18:38:0417021.09 MB11
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APS Active Pretraining with Successor Features
APS:ActivePretrainingwithSuccessorFeaturesHaoLiu1PieterAbbeel1Abstract2019;Vinyalsetal.,2019;Badiaetal.,2020a)andsolvingcomplexroboticcontroltasks(Andrychowiczetal.,2017;Weintroduceanewunsupervised...
Active with Features Successor Pretraining
2023-11-16 18:00:178991.47 MB20
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A New Representation of Successor Features for Transfer across Dissimilar Environments
ANewRepresentationofSuccessorFeaturesforTransferacrossDissimilarEnvironmentsMajidAbdolshah1HungLe1ThommenKarimpanalGeorge1SunilGupta1SantuRana1SvethaVenkatesh1Abstractintoindependentsub-domains.How...
of for Transfer Representation New
2023-11-16 17:51:5611571.21 MB30
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Sparse Gaussian Processes with Spherical Harmonic Features
SparseGaussianProcesseswithSphericalHarmonicFeaturesVincentDutordoir1NicolasDurrande1JamesHensman2AbstractyWeintroduceanewclassofinter-domainvari-biasationalGaussianprocesses(GP)wheredataismappedon...
Sparse with Gaussian Processes Features
2023-11-14 21:46:2710961.15 MB21
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Scalable and Efficient Comparison-based Search without Features
ScalableandEfﬁcientComparison-basedSearchwithoutFeaturesDaniyarChumbalov1LucasMaystre2MatthiasGrossglauser1Abstractameaningfulquery.However,thisisoftenanon-trivialtaskforahumanuser.Forexample,most...
Efficient and without Search Features
2023-11-14 21:46:17917630.96 KB26
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Preference modelling with context-dependent salient Features
PreferenceModelingwithContext-DependentSalientFeaturesAmandaBower1LauraBalzano2Abstractmodelsaddressthisissuewithmodelingnoise,ignoringitssystematicnature.Weobserve,asothershavebeforeusWeconsiderth...
with Features Context-Dependent Preference Salient
2023-11-14 21:45:551234623.59 KB9
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Graph Random Neural Features for Distance-Preserving Graph Representations
GraphRandomNeuralFeaturesforDistance-PreservingGraphRepresentationsDanieleZambon1CesareAlippi12LorenzoLivi34AbstractWhendatacomeasrealvectors,theseminalpaperbyRahimi&Recht(2008a)providesanefﬁcient...
Neural for Representations Graph random
2023-11-14 21:44:261457869.08 KB22
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Generalisation error in learning with random Features and the hidden manifold model
GeneralisationerrorinlearningwithrandomFeaturesandthehiddenmanifoldmodelFedericaGerace1BrunoLoureiro1FlorentKrzakala2MarcMézard2LenkaZdeborová1Abstracttiveresearchsubject.Thetraditionallearningth...
Learning with random in Features
2023-11-14 21:44:2014091.12 MB8
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Decentralised Learning with Random Features and Distributed Gradient Descent
DecentralisedLearningwithDistributedGradientDescentandRandomFeaturesDominicRichards1PatrickRebeschini1LorenzoRosasco234Abstractofnewdatapoints.Duetothegrowingsizeofmoderndatasetsandcomplexityofmany...
Learning Distributed and with random
2023-11-14 21:43:431609998.9 KB15
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Towards a Unified Analysis of Random Fourier Features
TowardsaUniﬁedAnalysisofRandomFourierFeaturesZhuLi1Jean-FrançoisTon1DinoOglic2DinoSejdinovic1Abstractimplicitcomputationofaninnerproductbetweenrichfea-turerepresentationsofdatathroughthekerneleva...
of Analysis random Features Fourier
2023-11-13 14:48:491118673.39 KB11
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Sample-Optimal Parametric Q-Learning Using Linearly Additive Features
Sample-OptimalParametricQ-LearningUsingLinearlyAdditiveFeaturesLinF.Yang1MengdiWang1Abstractthistheoretical-sharpresultdoesnotgeneralizetopracticalproblemswhereS,Acanbearbitrarilylargeorinﬁnite.Co...
Using Features Parametric Q-learning Additive
2023-11-13 14:48:28843343.22 KB19
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Online Learning to Rank with Features
OnlineLearningtoRankwithFeaturesShuaiLi1TorLattimore2CsabaSzepesvári2AbstractamodelwithatleastLparameters,whichisprohibitivelylargeintheapplicationswehaveinmind.Weintroduceanewmodelforonlinerankin...
Learning Rank Online with to
2023-11-13 14:48:078851.41 MB23
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Hybrid Models with Deep and Invertible Features
HybridModelswithDeepandInvertibleFeaturesEricNalisnick1AkihiroMatsukawa1YeeWhyeTeh1DilanGorur1BalajiLakshminarayanan1Abstractdetection(Bishop,1994),semi-supervisedlearning(Drucketal.,2007),andinfor...
Models and with Deep Features
2023-11-13 14:47:2615641.27 MB21
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Discovering Conditionally Salient Features with Statistical Guarantees
DiscoveringConditionallySalientFeatureswithStatisticalGuaranteesJaimeRoqueroGimenez1JamesZou2Abstractingsomestatisticalcontrolontherateoffalsediscoveries.Thisproblemhasbeenextensivelystudiedinthest...
with Guarantees Statistical Discovering Features
2023-11-13 14:46:5416201.17 MB16
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Adversarial Generation of Time-Frequency Features with application in audio synthesis
AdversarialGenerationofTime-FrequencyFeatureswithapplicationinaudiosynthesisAndre´sMaraﬁoti1NickiHolighaus1Nathanae¨lPerraudin2PiotrMajdak1Abstracttrainedsimultaneouslyinatwo-playermin-maxgame:T...
of Adversarial Generation with Features
2023-11-13 14:46:218522.37 MB11
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Provable Variable Selection for Streaming Features
ProvableVariableSelectionforStreamingFeaturesJingWang1JieShen2PingLi3AbstractandonlyrelatedFeatureswillbeincludedintherecommen-dationmodel.Hence,inreal-worldapplications,FeaturesInlarge-scalemachin...
for Selection Features Provable Variable
2023-11-13 12:00:29520328.57 KB12
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On the Spectrum of Random Features Maps of High Dimensional Data
OntheSpectrumofRandomFeaturesMapsofHighDimensionalDataZhenyuLiao1RomainCouillet12AbstractFeaturesrelevanttosomegiventask.ThenonlinearitiesmaketheserepresentationsmoremightybutmeanwhileRandomfeature...
of on the random Features
2023-11-13 12:00:20907785.78 KB17
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Random Fourier Features for Kernel Ridge Regression Approximation Bounds and Statistical Guarantees
RandomFourierFeaturesforKernelRidgeRegression:ApproximationBoundsandStatisticalGuaranteesHaimAvron1MichaelKapralov2CameronMusco3ChristopherMusco3AmeyaVelingker2AmirZandieh2AbstractIntheabove,K2Rn⇥...
for Kernel Regression random Features
2023-11-12 20:45:051525557.73 KB5
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