Catching up faster by switching sooner: a predictive approach to adaptive estimation with an application to the AIC-BIC dilemma von Erven, Tim van, Grünwald, Peter, de Rooij, Steven

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Rényi Divergence and Kullback-Leibler Divergence von van Erven, Tim, Harremoes, Peter

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Game-Theoretically Optimal Reconciliation of Contemporaneous Hierarchical Time Series Forecasts von van Erven, Tim, Cugliari, Jairo

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Fast Exact Bayesian Inference for Sparse Signals in the Normal Sequence Model von van Erven, Tim, Szabó, Botond

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Mixability is Bayes Risk Curvature Relative to Log Loss von van Erven, Tim, D. Reid, Mark, C. Williamson, Robert

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Follow the Leader If You Can, Hedge If You Must von de Rooj, Steven, van Erven, Tim, Grünwad, Peter D., Koolen, Wouter M.

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Modifying Squint for Prediction with Expert Advice in a Changing Environment von Neuteboom, Thom, van Erven, Tim

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The Risks of Recourse in Binary Classification von Fokkema, Hidde, Garreau, Damien, van Erven, Tim

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An Online Feasible Point Method for Benign Generalized Nash Equilibrium Problems von Sachs, Sarah, Hadiji, Hedi, van Erven, Tim, Staudigl, Mathias

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Towards Characterizing the First-order Query Complexity of Learning (Approximate) Nash Equilibria in Zero-sum Matrix Games von Hadiji, Hédi, Sachs, Sarah, van Erven, Tim, Koolen, Wouter M

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Accelerated Rates between Stochastic and Adversarial Online Convex Optimization von Sachs, Sarah, Hadiji, Hedi, van Erven, Tim, Guzman, Cristobal

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Adaptive Selective Sampling for Online Prediction with Experts von Castro, Rui M, Hellström, Fredrik, van Erven, Tim

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Attribution-based Explanations that Provide Recourse Cannot be Robust von Fokkema, Hidde, de Heide, Rianne, van Erven, Tim

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Between Stochastic and Adversarial Online Convex Optimization: Improved Regret Bounds via Smoothness von Sachs, Sarah, Hadiji, Hédi, van Erven, Tim, Guzmán, Cristóbal

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Scale-free Unconstrained Online Learning for Curved Losses von Mayo, Jack J, Hadiji, Hédi, van Erven, Tim

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Fast Exact Bayesian Inference for Sparse Signals in the Normal Sequence Model von van Erven, Tim, Szabo, Botond

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Modifying Squint for Prediction with Expert Advice in a Changing Environment von Neuteboom, Thom, Tim van Erven

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The Risks of Recourse in Binary Classification von Fokkema, Hidde, Garreau, Damien, Tim van Erven

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Generalization Guarantees via Algorithm-dependent Rademacher Complexity von Sachs, Sarah, van Erven, Tim, Hodgkinson, Liam, Khanna, Rajiv, Simsekli, Umut

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First- and Second-Order Bounds for Adversarial Linear Contextual Bandits von Olkhovskaya, Julia, Mayo, Jack, van Erven, Tim, Neu, Gergely, Wei, Chen-Yu

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