Statistical Learning
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Algorithmic Linearly Constrained Gaussian Processes
Neural Information Processing Systems
Neural Information Processing Systems http://nips.cc/
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DINGO: Distributed Newton-Type Method for Gradient-Norm Optimization
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Neural Information Processing Systems http://nips.cc/
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Fast-rate PAC-Bayes Generalization Bounds via Shifted Rademacher Processes
Jun Yang, Shengyang Sun, Daniel M. Roy
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The developments of Rademacher complexity and PAC-Bayesian theory have been largely independent.
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Precision-Recall Divergence Optimization for Generative Modeling with GANs and Normalizing Flows
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Achieving a balance between image quality (precision) and diversity (recall) is a significant challenge in the domain of generative models.
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