A T-estimation-based procedure for adaptive density estimation and optimal control in offline contextual MDPs without stationarity, providing oracle risk bounds under two loss functions and finite-sample cost guarantees.
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A maximum likelihood estimator based on geometric records estimates the tail index of Pareto-type distributions with proven consistency, asymptotic normality, and advantages over Hill's estimator in sequential or low-measurement contexts.
The deep SPAR model shows concurrent floods and droughts becoming more likely in the Upper Danube by 2100 under high emissions, with changes in the dependence between catchments contributing substantially to the increase.
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Adaptive Estimation and Optimal Control in Offline Contextual MDPs without Stationarity
A T-estimation-based procedure for adaptive density estimation and optimal control in offline contextual MDPs without stationarity, providing oracle risk bounds under two loss functions and finite-sample cost guarantees.
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Estimating the tail index of Pareto-type distributions from geometric records
A maximum likelihood estimator based on geometric records estimates the tail index of Pareto-type distributions with proven consistency, asymptotic normality, and advantages over Hill's estimator in sequential or low-measurement contexts.
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Exploring climate change effects on concurrent floods and concurrent droughts via statistical deep learning
The deep SPAR model shows concurrent floods and droughts becoming more likely in the Upper Danube by 2100 under high emissions, with changes in the dependence between catchments contributing substantially to the increase.