"with"的相关文档

标签“with”的相关文档，共634条

Regularization in directable environments with application to Tetris
RegularizationinDirectableEnvironmentswithApplicationtoTetrisJanMalteLichtenberg1O¨zgu¨rS¸ims¸ek1Abstractonregularization.Speciﬁcally,weproposeamodelthatintroducesabiastowardgivingallfeaturese...
with in to Regularization Application
2023-11-13 14:48:231338420.65 KB28
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Refined Complexity of PCA with Outliers
ReﬁnedComplexityofPCAwithOutliersFedorFomin1PetrGolovach1FahadPanolan1KirillSimonov1Abstractlow-rankapproximationofdatamatrixMbysolvingPrincipalcomponentanalysis(PCA)isoneoftheminimizeM−L2mostfun...
of with Complexity Outliers PCA
2023-11-13 14:48:231841321.25 KB15
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Random Walks on Hypergraphs with Edge-Dependent Vertex Weights
RandomWalksonHypergraphswithEdge-DependentVertexWeightsUthsavChitra1BenjaminJRaphael1Abstractbetweengroupsofproteinsinproteincomplexes(Ramadanetal.,2004;Ritzetal.,2014).Hypergraphsareusedinmachinel...
with on random Hypergraphs Walks
2023-11-13 14:48:211787329.14 KB17
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PROVEN Verifying Robustness of Neural Networks with a Probabilistic Approach
PROVEN:VerifyingRobustnessofNeuralNetworkswithaProbabilisticApproachTsui-WeiWeng1Pin-YuChen2LamM.Nguyen2MarkS.Squillante2AkhilanBoopathy1IvanOseledets3LucaDaniel1Abstractdevelopingeffectivecounterm...
of Neural Networks with Robustness
2023-11-13 14:48:19508159.11 KB24
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QTRAN Learning to Factorize with Transformation for Cooperative Multi-Agent Reinforcement Learning
QTRAN:LearningtoFactorizewithTransformationforCooperativeMulti-AgentReinforcementlearningKyunghwanSon1DaewooKim1WanJuKang1DavidHostallero1YungYi1Abstractneuralnetworks,whichcanrepresentaction-value...
Learning for with to Transformation
2023-11-13 14:48:19720922.77 KB30
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Provably efficient RL with Rich Observations via Latent State Decoding
ProvablyefﬁcientRLwithRichObservationsviaLatentStateDecodingSimonS.Du1AkshayKrishnamurthy2NanJiang3AlekhAgarwal4MiroslavDud´ık2JohnLangford2Abstract2010;Lattimore&Hutter,2012).Consequently,treat...
Efficient with via Provably Observations
2023-11-13 14:48:191859751.73 KB10
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Projection onto Minkowski Sums with Application to Constrained Learning
ProjectionontoMinkowskiSumswithApplicationtoConstrainedLearningJoong-HoWon1JasonXu2KennethLange3AbstractBorwein,1993).Inmanytasks,however,theMinkowskisumisamoreappropriateorusefuloperationtoconside...
with to Projection Sums Application
2023-11-13 14:48:18639419.17 KB27
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Processing Megapixel Images with Deep Attention-Sampling Models
ProcessingMegapixelImageswithDeepAttention-SamplingModelsAngelosKatharopoulos12Franc¸oisFleuret12Abstract(b)Existingdeeparchitecturescannotoperateonvery(a)(c)largesignalssuchasmegapixelimagesdueto...
Models with Deep Images Processing
2023-11-13 14:48:1719081.19 MB9
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Predicate Exchange Inference with Declarative Knowledge
PredicateExchange:InferencewithDeclarativeKnowledgeZennaTavares1JavierBurroni2EdgarMinasyan3ArmandoSolarLezama1RajeshRanganath4Abstracttributionoverthreedimensionalscenes.Someformsofknowledge,sucha...
Inference with Knowledge Predicate Exchange
2023-11-13 14:48:171606954.87 KB12
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Plug-and-Play Methods Provably Converge with Properly Trained Denoisers
Plug-and-PlayMethodsProvablyConvergewithProperlyTrainedDenoisersErnestK.Ryu1JialinLiu1SichengWang2XiaohanChen2ZhangyangWang2WotaoYin1Abstractmeasurementsoftheimage,isencodedinf(x).Sof(x)issmallifxa...
with Methods Provably Converge Trained
2023-11-13 14:48:15659369.47 KB28
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Phase transition in PCA with missing data Reduced signal-to-noise ratio, not sample size!
PhasetransitioninPCAwithmissingdata:Reducedsignal-to-noiseratio,notsamplesize!NielsBruunIpsen1LarsKaiHansen1Abstract(1999)andthisformulationallowsforestimatingprincipalcomponentsinthepresenceofmiss...
with Data in Phase Missing
2023-11-13 14:48:141715896.19 KB14
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Optimal Transport for structured data with application on graphs
OptimalTransportforstructureddatawithapplicationongraphsTitouanVayer1LaetitiaChapel1Re´miFlamary2RomainTavenard3NicolasCourty1Abstractevenimages(Bach&Harchaoui,2007).Thisworkconsiderstheproblemofc...
for with Data Optimal Transport
2023-11-13 14:48:101341937.58 KB23
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Optimal Minimal Margin Maximization with Boosting
OptimalMinimalMarginMaximizationwithBoostingAllanGrønlund1KasperGreenLarsen1AlexanderMathiasen1Abstractstructsalinearcombinationclassiﬁersign(Tαtht(x)),t=1Boostingalgorithmsiterativelyproducelin...
Maximization with Optimal Margin Boosting
2023-11-13 14:48:0912911.38 MB18
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Optimal Algorithms for Lipschitz Bandits with Heavy-tailed Rewards
OptimalAlgorithmsforLipschitzBanditswithHeavy-tailedRewardsShiyinLu1GuanghuiWang1YaoHu2LijunZhang1Abstractfromaﬁxedbutunknownprobabilitydistributionassociatedwiththechosenarm.Inordertomaximizehisg...
for Algorithms with Optimal Bandits
2023-11-13 14:48:091645725.43 KB6
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Open Vocabulary Learning on Source Code with a Graph-Structured Cache
OpenVocabularyLearningonSourceCodewithaGraph–StructuredCacheMilanCvitkovic1BadalSingh2AnimaAnandkumar1AbstractWhilecodecontainsnaturallanguagewordsandphrasesinordertobehuman–readable,codeisnotmea...
Learning with on Code Source
2023-11-13 14:48:0814871.24 MB20
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Online Variance Reduction with Mixtures
OnlineVarianceReductionwithMixturesZalánBorsos1SebastianCuri1KﬁrY.Levy1AndreasKrause1AbstractWhymixtures?Themajorityofexistingworksonadap-tivesamplingdistributionsareunabletoexploitsimilaritiesAd...
Online with Variance Reduction Mixtures
2023-11-13 14:48:0815021.79 MB29
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Online learning with kernel losses
OnlinelearningwithkernellossesAldoPacchiano1NiladriS.Chatterji1PeterL.Bartlett1Abstracttheendofeachround.Another,morechallengingfeedbackmodelisthepartialinformationorbanditfeedbackmodelWepresentage...
Learning Kernel Online with Losses
2023-11-13 14:48:081655353.79 KB7
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Online Learning with Sleeping Experts and Feedback Graphs
OnlineLearningwithSleepingExpertsandFeedbackGraphsCorinnaCortes1GiuliaDeSalvo1ClaudioGentile1MehryarMohri12ScottYang3Abstractworkforonlinelearningwheretheactionlossesthatareobservabletothelearnerar...
Learning Online and with Feedback
2023-11-13 14:48:088591.09 MB26
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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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Online Control with Adversarial Disturbances
OnlineControlwithAdversarialDisturbancesNamanAgarwal1BrianBullins21EladHazan21ShamM.Kakade341KaranSingh21AbstractChallenge1.Perhapsthemostimportantchallengeweaddressisindealingwitharbitrarydisturba...
Online Adversarial with Control Disturbances
2023-11-13 14:48:071263275.69 KB24
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