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标签“Processes”的相关文档，共49条

Variational Auto-Regressive Gaussian Processes for Continual Learning
VariationalAuto-RegressiveGaussianProcessesforContinualLearningSanyamKapoor1TheofanisKaraletsos2ThangD.Bui3Abstract(a)VAR-GP(ours)Throughsequentialconstructionofposteriorson(b)VCL(withcoresetsize10...
Learning for Variational Gaussian Processes
2023-11-16 19:42:229441.67 MB4
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Value-at-Risk Optimization with Gaussian Processes
Value-at-RiskOptimizationwithGaussianProcessesQuocPhongNguyen1ZhongxiangDai1BryanKianHsiangLow1PatrickJaillet2AbstractuncertaintyinZcanbecontrolledviathemean-varianceoptimizationframework(Iwazakiet...
Optimization with Gaussian Processes Value-at-Risk
2023-11-16 19:42:219381.28 MB9
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Sparse within Sparse Gaussian Processes using Neighbor Information
SparsewithinSparseGaussianProcessesusingNeighborInformationGia-LacTran12DimitriosMilios1PietroMichiardi1MaurizioFilippone1Abstract&Ghahramani,2005;Naish-Guzman&Holden,2007;Tit-sias,2009;Hensmanetal...
Using Sparse Gaussian Processes Information
2023-11-16 19:41:547274.84 MB27
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SigGPDE Scaling Sparse Gaussian Processes on Sequential Data
SigGPDE:ScalingSparseGaussianProcessesonSequentialDataMaudLemercier1CristopherSalvi2ThomasCass3EdwinV.Bonilla4TheodorosDamoulas1TerryLyons2AbstractvationsN,withnaïveapproacheshavingatimecomplexity...
Sparse on Gaussian Processes Sequential
2023-11-16 19:41:47705570.42 KB8
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Scalable Variational Gaussian Processes via Harmonic Kernel Decomposition
ScalableVariationalGaussianProcessesviaHarmonicKernelDecompositionShengyangSun12JiaxinShi3AndrewGordonWilson4RogerGrosse12Abstract2t=0t=1t=2t=3WeintroduceanewscalablevariationalGaus-1sianprocessapp...
Kernel Variational Gaussian via Processes
2023-11-16 19:41:4218046.85 MB24
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Reinforcement Learning for Cost-Aware Markov Decision Processes
ReinforcementLearningforCost-AwareMarkovDecisionProcessesWesleyA.Suttle1KaiqingZhang2ZhuoranYang3DavidN.Kraemer1JiLiu4Abstractquentlyusedinpractice.Nevertheless,alternativeobjectiveshaveseenincreas...
Learning for Reinforcement Markov Decision
2023-11-16 19:41:301656528.56 KB18
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Meta-learning Hyperparameter Performance Prediction with Neural Processes
Meta-learningHyperparameterPerformancePredictionwithNeuralProcessesYingWei1PeilinZhao2JunzhouHuang2AbstractFreefromthelimitationsofexhaustivesearch(Bergstra&Bengio,2012)beingcomputationallyexpensiv...
Neural with Processes Prediction Hyperparameter
2023-11-16 19:05:1711961.48 MB6
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Equivariant Learning of Stochastic Fields Gaussian Processes and Steerable Conditional Neural Processes
EquivariantLearningofStochasticFields:GaussianProcessesandSteerableConditionalNeuralProcessesPeterHolderrieth1MichaelHutchinson1YeeWhyeTeh12AbstractFigure1.Aschematicofequivariantlearningofvectorﬁ...
Learning of Gaussian Stochastic Processes
2023-11-16 18:38:016731.53 MB21
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Deep kernel Processes
DeepkernelProcessesLaurenceAitchison1AdamX.Yang1SebastianW.Ober2Abstractalreadyexist.Inthesemethods,whicharecloselyre-latedtoinﬁniteBayesianneuralnetworks(Leeetal.,2017;WedeﬁnedeepkernelProcesses...
Kernel Deep Processes
2023-11-16 18:31:01952217.12 KB8
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Cumulants of Hawkes Processes are Robust to Observation Noise
CumulantsofHawkesProcessesareRobusttoObservationNoiseWilliamTrouleau1JalalEtesami2MatthiasGrossglauser1NegarKiyavash2PatrickThiran1Abstracttheyareusedtomodelthestochastictimeevolutionoflimitorderbo...
of Robust Processes to Are
2023-11-16 18:30:5417681.82 MB20
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Conditional Temporal Neural Processes with Covariance Loss
ConditionalTemporalNeuralProcesseswithCovarianceLossBoseonYoo1JiwooLee2JanghoonJu2SeijunChung1SoyeonKim1JaesikChoi13Abstractducedin(Garneloetal.,2018a),whicharethenoveleffortsthatimplementsuchGPswi...
Neural with Conditional Processes Loss
2023-11-16 18:11:256046.12 MB14
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Bias-Free Scalable Gaussian Processes via Randomized Truncations
Bias-FreeScalableGaussianProcessesviaRandomizedTruncationsAndresPotapczynski1LuhuanWu2DanBiderman1GeoffPleiss1JohnP.Cunningham12Abstractbiasofinducingpointmethods(Baueretal.,2016;Burtetal.,2019),th...
Gaussian via Processes Scalable Randomized
2023-11-16 18:07:3611591.06 MB18
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Temporal Logic Point Processes
TemporalLogicPointProcessesShuangLi1LuWang2RuizhiZhang3XiaofuChang4XuqinLiu4YaoXie5YuanQi4LeSong46Abstracteventdatabecomesincreasinglyimportanttounderstandtheunderlyingsystems,tomakeaccuratepredict...
Processes Point Temporal Logic
2023-11-14 21:46:406402.01 MB12
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Stochastic Gradient and Langevin Processes
StochasticGradientandLangevinProcessesXiangCheng1DongYin1PeterBartlett1MichaelJordan1AbstractrestrictedtoisotropicGaussiannoise,whereasthenoiseinSGDcanbefarfromGaussian.Second,thenoisedependsWeprov...
and Gradient Stochastic Processes Langevin
2023-11-14 21:46:3218371.72 MB8
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Sparse Gaussian Processes with Spherical Harmonic Features
SparseGaussianProcesseswithSphericalHarmonicFeaturesVincentDutordoir1NicolasDurrande1JamesHensman2AbstractyWeintroduceanewclassofinter-domainvari-biasationalGaussianProcesses(GP)wheredataismappedon...
Sparse with Gaussian Processes Features
2023-11-14 21:46:2710951.15 MB21
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Scalable Exact Inference in Multi-Output Gaussian Processes
ScalableExactInferenceinMulti-OutputGaussianProcessesWesselP.Bruinsma12EricPerim2WillTebbutt1J.ScottHosking34ArnoSolin5RichardE.Turner16Abstract(Hennigetal.,2015),suchasinoptimisation(Brochuetal.,2...
Inference Gaussian in Processes Exact
2023-11-14 21:46:18570825.17 KB10
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Reinforcement Learning for Non-Stationary Markov Decision Processes The Blessing of (More) Optimism
ReinforcementLearningforNon-StationaryMarkovDecisionProcesses:TheBlessingof(More)OptimismWangChiCheung1DavidSimchi-Levi2RuihaoZhu2Abstractimizesitscumulativerewards,whilefacingthefollowingchallenge...
Learning for Reinforcement Markov Decision
2023-11-14 21:46:07550648.51 KB30
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Randomly Projected Additive Gaussian Processes for Regression
RandomlyProjectedAdditiveGaussianProcessesforRegressionIanDelbridge1DavidBindel1AndrewGordonWilson2Abstractsmall-dataregime,wherecarefuluncertaintyrepresentationisparticularlycrucial,strongpriorspr...
for Gaussian Regression Processes Projected
2023-11-14 21:46:041680481.9 KB23
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Neural Clustering Processes
NeuralClusteringProcessesAriPakman1YueqiWang12CatalinMitelut1JinHyungLee1LiamPaninski1Abstractticularlychallenging,sinceingeneralinthesecasesthemodelparameterscannotbemarginalizedandmustbekeptProba...
Neural Clustering Processes
2023-11-14 21:45:2113801.87 MB18
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Learning Adversarial Markov Decision Processes with Bandit Feedback and Unknown Transition
LearningAdversarialMarkovDecisionProcesseswithBanditFeedbackandUnknownTransitionChiJin1TianchengJin2HaipengLuo2SuvritSra3TianchengYu3AbstractThemajorityoftheliteratureinlearningMDPsassumesstationar...
Learning Adversarial with Markov Decision
2023-11-14 21:44:481044330.21 KB22
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