"Towards"的相关文档 - 文库宝

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标签“Towards”的相关文档，共46条

Two-way kernel matrix puncturing Towards resource-efficient PCA and spectral clustering
Two-waykernelmatrixpuncturing:Towardsresource-efﬁcientPCAandspectralclusteringRomainCouillet12FlorentChatelain1NicolasLeBihan1Abstractbeprocessedinreal-timebeforebeingdiscardedaltogether.Inparalle...
Kernel Matrix Resource-efficient Towards PCA
2023-11-16 19:42:1518753.07 MB17
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Towards Tight Bounds on the Sample Complexity of Average-reward MDPs
TowardsTightBoundsontheSampleComplexityofAverage-rewardMDPsYujiaJin1AaronSidford1Abstractmakingunderuncertaintyandreinforcementlearning(Puter-man,2014;Sutton&Barto,2018).Itisaprominenttheoret-Wepro...
Complexity on the bounds Sample
2023-11-16 19:42:1215061.88 MB3
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Towards Understanding Learning in Neural Networks with Linear Teachers
TowardsUnderstandingLearninginNeuralNetworkswithLinearTeachersRoeiSarussi1AlonBrutzkus1AmirGloberson1Abstractwillseparatethedata.Whichofthesewillbefoundbygradientdescent?Cananeuralnetworkminimizing...
Learning Neural Networks with in
2023-11-16 19:42:121479594.64 KB4
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Towards Understanding and Mitigating Social Biases in Language Models
TowardsUnderstandingandMitigatingSocialBiasesinLanguageModelsPaulPuLiang1ChiyuWu1Louis-PhilippeMorency1RuslanSalakhutdinov1AbstractZhaoetal.,2017).Morerecently,languagemodels(LMs)areincreasinglyuse...
and in Towards Understanding Mitigating
2023-11-16 19:42:12965963.33 KB26
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Towards the Unification and Robustness of Perturbation and Gradient Based Explanations
TowardstheUniﬁcationandRobustnessofPerturbationandGradientBasedExplanationsSushantAgarwal1ShahinJabbari2ChiragAgarwal2SohiniUpadhyay2ZhiweiStevenWu3HimabinduLakkaraju2Abstractcanunderstandandconse...
of and the Robustness Towards
2023-11-16 19:42:118431.4 MB13
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Towards Rigorous Interpretations a Formalisation of Feature Attribution
TowardsRigorousInterpretations:aFormalisationofFeatureAttributionDariusAfchar12RomainHennequin1VincentGuigue2Abstractcontrollinganddisentanglingeveryaspectofamodelpre-diction,rangingfromhowthedatai...
of Feature Attribution Towards Interpretations
2023-11-16 19:42:11708970.95 KB18
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Towards Practical Mean Bounds for Small Samples
TowardsPracticalMeanBoundsforSmallSamplesMyPhan1PhilipS.Thomas1ErikLearned-Miller1Abstractrefertotwoseparatesettings,theone-endedsupportsetting,inwhichthedistributionisknowntofallintheintervalHisto...
for Mean bounds Samples Practical
2023-11-16 19:42:1113021.26 MB13
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Towards Open Ad Hoc Teamwork Using Graph-based Policy Learning
TowardsOpenAdHocTeamworkUsingGraph-basedPolicyLearningArrasyRahman1NiklasHo¨pner2FilipposChristianos1StefanoV.Albrecht1AbstractPrioradhocteamworkapproaches(Barrett&Stone,2015;Albrechtetal.,2016;Ba...
Using Graph-based Towards Open Ad
2023-11-16 19:42:111858733.97 KB19
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Towards Open-World Recommendation An Inductive Model-based Collaborative Filtering Approach
TowardsOpen-WorldRecommendation:AnInductiveModel-basedCollaborativeFilteringApproachQitianWu12HengruiZhang1XiaofengGao12JunchiYan12HongyuanZha3Abstract(MC)whereonehasauser-itemratingmatrixwhoseentr...
An Model-Based Collaborative Towards Inductive
2023-11-16 19:42:1119151.02 MB27
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Towards Domain-Agnostic Contrastive Learning
TowardsDomain-AgnosticContrastiveLearningVikasVerma12Minh-ThangLuong1KenjiKawaguchi3HieuPham1QuocV.Le1Abstract(Dai&Le,2015;Howard&Ruder,2018;Petersetal.,2018;Radfordetal.,2019;Clarketal.,2020),ands...
Learning Towards Contrastive Domain-Agnostic
2023-11-16 19:42:10827463.02 KB20
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Towards Defending against Adversarial Examples via Attack-Invariant Features
TowardsDefendingagainstAdversarialExamplesviaAttack-InvariantFeatures455DaweiZhou12Ton8g9li1angLiu2BoHan3Nanna5nWang1†5ChunleiPeng4XinboGao55AbstractTruckAutomobilePGD??ShipAADeepneuralnetworks(...
Adversarial via Examples Towards against
2023-11-16 19:42:10801826.07 KB19
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Towards Certifying L-infinity Robustness using Neural Networks with L-inf-dist Neurons
TowardsCertifying∞RobustnessusingNeuralNetworkswith∞-distNeuronsBohangZhang1TianleCai23ZhouLu4DiHe5LiweiWang16Abstract1.IntroductionItiswell-knownthatstandardneuralnetworks,Modernneuralnetworksar...
Neural Using Networks Robustness Towards
2023-11-16 19:42:101820885.14 KB1
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Towards Distraction-Robust Active Visual Tracking
TowardsDistraction-RobustActiveVisualTrackingFangweiZhong1PengSun2WenhanLuo3TingyunYan14YizhouWang1AbstractWhichoneistherealtarget?Inactivevisualtracking,itisnotoriouslydifﬁ-TemplateVisualObservat...
Active Towards Tracking Visual Distraction-Robust
2023-11-16 19:42:1014542.2 MB15
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Towards Better Robust Generalization with Shift Consistency Regularization
TowardsBetterRobustGeneralizationwithShiftConsistencyRegularizationShufeiZhang12ZhuangQian12KaizhuHuang1QiufengWang1RuiZhang3XinpingYi2Abstract2015;Heetal.,2016;Miyatoetal.,2017;Zagoruyko&Komodakis...
with Robust Consistency generalization Better
2023-11-16 19:42:1010092.95 MB8
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Towards Better Laplacian Representation in Reinforcement Learning with Generalized Graph Drawing
TowardsBetterLaplacianRepresentationinReinforcementLearningwithGeneralizedGraphDrawingKaixinWang1KuangqiZhou1QixinZhang2JieShao3BryanHooi1JiashiFeng1AbstractFigure1.VisualizationofenvironmentandLap...
Learning Reinforcement in Representation Better
2023-11-16 19:42:0912372.67 MB26
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To be Robust or to be Fair Towards Fairness in Adversarial Training
TobeRobustortobeFair:TowardsFairnessinAdversarialTrainingHanXu1XiaoruiLiu1YaxinLi1AnilK.Jain1JiliangTang1Abstracttobewronglyclassiﬁed:AdversarialtrainingalgorithmshavebeenprovedminEmaxL(f(x+δ),y)...
Robust Be to to Towards
2023-11-16 19:42:081319657.11 KB6
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Regularizing Towards Causal Invariance Linear Models with Proxies
RegularizingTowardsCausalInvariance:LinearModelswithProxiesMichaelOberst1NikolajThams2JonasPeters2DavidSontag1AbstractβxAβyWeproposeamethodforlearninglinearmod-XαYelswhosepredictiveperformanceis...
Models with Causal Linear Towards
2023-11-16 19:41:291075977.73 KB8
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Bridging Multi-Task Learning and Meta-Learning Towards Efficient Training and Effective Adaptation
BridgingMulti-TaskLearningandMeta-Learning:TowardsEfﬁcientTrainingandEffectiveAdaptationHaoxiangWang1HanZhao1BoLi1Abstract1.IntroductionMulti-tasklearning(MTL)aimstoimprovetheMulti-tasklearninghas...
Learning Efficient and Multi-task Meta-Learning
2023-11-16 18:11:161221622.28 KB22
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A Free Lunch From ANN Towards Efficient, Accurate Spiking Neural Networks Calibration
AFreeLunchFromANN:TowardsEfﬁcient,AccurateSpikingNeuralNetworksCalibrationYuhangLi12ShikuangDeng1XinDong3RuihaoGong4ShiGu1AbstractFeaturesTrainingConversionCalibrationSpikingNeuralNetwork(SNN)hasb...
from Efficient Accurate Towards Free
2023-11-16 17:52:026522.96 MB2
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Towards Understanding the Regularization of Adversarial Robustness on Neural Networks
TowardsUnderstandingtheRegularizationofAdversarialRobustnessonNeuralNetworksYuxinWen12ShuaiLi1KuiJia12Abstract(Szegedyetal.,2014).Moreintriguingly,theseadversarialexamplesaregeneratedbyaddingimperc...
of Adversarial the Robustness Regularization
2023-11-14 21:46:499111.65 MB13
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