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The Differentiable Cross-Entropy Method
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Stochastic Optimization for Non-convex Inf-Projection Problems
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Spectrum Dependent Learning Curves in Kernel Regression and Wide Neural Networks
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Spectral Graph Matching and Regularized Quadratic Relaxations Algorithm and Theory
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Responsive Safety in Reinforcement Learning
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Reinforcement Learning for Non-Stationary Markov Decision Processes The Blessing of (More) Optimism
ReinforcementLearningforNon-StationaryMarkovDecisionProcesses:TheBlessingof(More)OptimismWangChiCheung1DavidSimchi-Levi2RuihaoZhu2Abstractimizesitscumulativerewards,whilefacingthefollowingchallenge...
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Quadratically Regularized Subgradient Methods for Weakly Convex Optimization with Weakly Convex Constraints
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Puzzle Mix Exploiting Saliency and Local Statistics for Optimal Mixup
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PENNI Pruned Kernel Sharing for Efficient CNN Inference
PENNI:PrunedKernelSharingforEfﬁcientCNNInferenceShiyuLi1EdwardHanson1HaiLi1YiranChen1Abstractlayer(Zagoruyko&Komodakis,2016),ormorebranches(Szegedyetal.,2015).Amajordrawbackofna¨ıvelyin-Although...
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Ordinal Non-negative Matrix Factorization for Recommendation
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Optimal transport mapping via input convex neural networks
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Optimal Differential Privacy Composition for Exponential Mechanisms
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On Second-Order Group Influence Functions for Black-Box Predictions
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Normalized Flat Minima Exploring Scale Invariant Definition of Flat Minima for Neural Networks Using PAC-Bayesian Analysis
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Moniqua Modulo Quantized Communication in Decentralized SGD
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Logarithmic Regret for Online Control with Adversarial Noise
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Learning for Dose Allocation in Adaptive Clinical Trials with Safety Constraints
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Influence Diagram Bandits
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Inferring DQN structure for high-dimensional continuous control
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Implicit Learning Dynamics in Stackelberg Games Equilibria Characterization, Convergence Analysis, and Empirical Study
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