arXiv Statistics @arxiv_stats@qoto.org

An Experimental Design Perspective on Model-Based Reinforcement Learning. (arXiv:2112.05244v1 [cs.LG]) http://arxiv.org/abs/2112.05244

On the Relation between Prediction and Imputation Accuracy under Missing Covariates. (arXiv:2112.05248v1 [stat.ML]) http://arxiv.org/abs/2112.05248

Handling missing data when estimating causal effects with Targeted Maximum Likelihood Estimation. (arXiv:2112.05274v1 [stat.ME]) http://arxiv.org/abs/2112.05274

Solving linear Bayesian inverse problems using a fractional total variation-Gaussian (FTG) prior and transport map. (arXiv:2112.05288v1 [math.ST]) http://arxiv.org/abs/2112.05288

Multivariate double truncated expectation and covariance risk measures for elliptical distributions. (arXiv:2112.05319v1 [math.ST]) http://arxiv.org/abs/2112.05319

Segmenting Time Series via Self-Normalization. (arXiv:2112.05331v1 [stat.ME]) http://arxiv.org/abs/2112.05331

Sketching as a Tool for Understanding and Accelerating Self-attention for Long Sequences. (arXiv:2112.05359v1 [cs.LG]) http://arxiv.org/abs/2112.05359

Daily peak electrical load forecasting with a multi-resolution approach. (arXiv:2112.04492v1 [cs.LG]) http://arxiv.org/abs/2112.04492

A Parametric Approach to Relaxing the Independence Assumption in Relative Survival Analysis. (arXiv:2112.04534v1 [stat.ME]) http://arxiv.org/abs/2112.04534

A Combinatorial Approach for Nonparametric Short-Term Estimation of Queue Lengths using Probe Vehicles. (arXiv:2112.04551v1 [stat.ME]) http://arxiv.org/abs/2112.04551

Ambiguous Dynamic Treatment Regimes: A Reinforcement Learning Approach. (arXiv:2112.04571v1 [cs.LG]) http://arxiv.org/abs/2112.04571

Custom Orthogonal Weight functions (COWs) for Event Classification. (arXiv:2112.04574v1 [stat.ME]) http://arxiv.org/abs/2112.04574

A generalized definition of the average causal effect for both binary and continuous treatments. (arXiv:2112.04580v1 [stat.ME]) http://arxiv.org/abs/2112.04580

Moments estimators and omnibus chi-square tests for some usual probability laws. (arXiv:2112.04589v1 [stat.ME]) http://arxiv.org/abs/2112.04589

The perils of being unhinged: On the accuracy of classifiers minimizing a noise-robust convex loss. (arXiv:2112.04590v1 [cs.LG]) http://arxiv.org/abs/2112.04590

InvGAN: Invertable GANs. (arXiv:2112.04598v1 [cs.CV]) http://arxiv.org/abs/2112.04598

Calibration Improves Bayesian Optimization. (arXiv:2112.04620v1 [cs.LG]) http://arxiv.org/abs/2112.04620

RID-Noise: Towards Robust Inverse Design under Noisy Environments. (arXiv:2112.03912v1 [cs.LG]) http://arxiv.org/abs/2112.03912

Case Study: Evaluation of a meta-analysis of the association between soy protein and cardiovascular disease. (arXiv:2112.03945v1 [stat.AP]) http://arxiv.org/abs/2112.03945

A causal approach to functional mediation analysis with application to a smoking cessation intervention. (arXiv:2112.03960v1 [stat.ME]) http://arxiv.org/abs/2112.03960