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On Relativistic f-Divergences
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Environment Inference for Invariant Learning
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Lower Bounds on Cross-Entropy Loss in the Presence of Test-time Adversaries
LowerBoundsonCross-EntropyLossinthePresenceofTest-timeAdversariesArjunNitinBhagoji1DanielCullina2VikashSehwag3PrateekMittal3Abstractonestablishingfundamentalboundsonlearninginthepres-enceoftest-tim...
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Understanding Noise Injection in GANs
UnderstandingNoiseInjectioninGANsRuiliFeng1DeliZhao2Zheng-JunZha†1Abstractquantizingneuralnetworks(Baskinetal.,2018).Inrecentyears,noiseinjection1hasattractedmoreandmoreatten-Noiseinjectionisaneff...
2023-11-165512.51 MB10页20
Reinforcement Learning for Non-Stationary Markov Decision Processes The Blessing of (More) Optimism
ReinforcementLearningforNon-StationaryMarkovDecisionProcesses:TheBlessingof(More)OptimismWangChiCheung1DavidSimchi-Levi2RuihaoZhu2Abstractimizesitscumulativerewards,whilefacingthefollowingchallenge...
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Modulating Surrogates for Bayesian Optimization
ModulatingSurrogatesforBayesianOptimizationErikBodin1MarkusKaiser23IevaKazlauskaite4ZhenwenDai5NeillD.F.Campbell4CarlHenrikEk1AbstractsequentialdecisionmakingtaskssuchasBO,wherethemodelisusednotonl...
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On Leveraging Pretrained GANs for Generation with Limited Data
OnLeveragingPretrainedGANsforGenerationwithLimitedDataMiaoyunZhao1YulaiCong1LawrenceCarin1AbstractAlthoughmanypowerfulGANmodelspretrainedonlarge-scaledatasetshavebeenreleased,feweffortshavebeenRece...
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Decentralized Riemannian Gradient Descent on the Stiefel Manifold
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Provably Efficient Algorithms for Multi-Objective Competitive RL
ProvablyEfﬁcientAlgorithmsforMulti-ObjectiveCompetitiveRLTianchengYu1YiTian1JingzhaoZhang1SuvritSra1Abstractaveragereturntoatargetsetsmallaslongasthissetsatisﬁesaconditioncalledapproachability(Bl...
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Size-Invariant Graph Representations for Graph Classification Extrapolations
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Not All Samples Are Created Equal Deep Learning with Importance Sampling
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Invertible generative models for inverse problems mitigating representation error and dataset bias
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Real-Time Adaptive Image Compression
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LP-SparseMAP Differentiable Relaxed Optimization for Sparse Structured Prediction
LP-SparseMAP:DifferentiableRelaxedOptimizationforSparseStructuredPredictionVladNiculae1AndréF.T.Martins123AbstractsleeptheclockaroundBUDGETfactorTREEfactorStructuredpredictorsrequiresolvingacombin...
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Autoencoder Image Interpolation by Shaping the Latent Space
AutoencoderImageInterpolationbyShapingtheLatentSpaceAlonOring1ZoharYakhini1YacovHel-Or1Abstractexistingobjects,cameraparametersandadditionalscenecomponents,suchaslightingandthereﬂectivecharacteris...
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Representation Learning via Adversarially-Contrastive Optimal Transport
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How Framelets Enhance Graph Neural Networks
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Exact MAP Inference by Avoiding Fractional Vertices
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Programming with a Differentiable Forth Interpreter
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World of Bits An Open-Domain Platform for Web-Based Agents
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