The occlusion process: improving sampler performance with parallel computation and variational approximation https://arxiv.org/abs/2411.11983 #stat.CO
US COVID-19 school closure was not cost-effective, but other measures were https://arxiv.org/abs/2411.12016 #stat.AP
On the Efficiency of ERM in Feature Learning https://arxiv.org/abs/2411.12029 #stat.ML #math.ST #stat.TH #cs.LG
Prediction-Guided Active Experiments https://arxiv.org/abs/2411.12036 #stat.ML #econ.EM #cs.LG
A Comparison of Zero-Inflated Models for Modern Biomedical Data https://arxiv.org/abs/2411.12086 #stat.ME #stat.AP
Asymptotics in Multiple Hypotheses Testing under Dependence: beyond Normality https://arxiv.org/abs/2411.12119 #math.ST #stat.ME #stat.TH
Exact Risk Curves of signSGD in High-Dimensions: Quantifying Preconditioning and Noise-Compression Effects https://arxiv.org/abs/2411.12135 #stat.ML #cs.LG
Tangential Randomization in Linear Bandits (TRAiL): Guaranteed Inference and Regret Bounds https://arxiv.org/abs/2411.12154 #stat.ML #eess.SY #cs.LG #cs.SY
Efficient inference for differential equation models without numerical solvers https://arxiv.org/abs/2411.10494 #stat.ME
Inference for overparametrized hierarchical Archimedean copulas https://arxiv.org/abs/2411.10615 #stat.ME
Doubly Robust Estimation of Causal Excursion Effects in Micro-Randomized Trials with Missing Longitudinal Outcomes https://arxiv.org/abs/2411.10620 #stat.ME
Sensitivity Analysis for Observational Studies with Flexible Matched Designs https://arxiv.org/abs/2411.10623 #stat.ME
Wasserstein Spatial Depth https://arxiv.org/abs/2411.10646 #math.ST #stat.ME #stat.TH
False Discovery Control in Multiple Testing: A Brief Overview of Theories and Methodologies https://arxiv.org/abs/2411.10647 #stat.ME #math.ST #stat.AP #stat.TH
Subsampling-based Tests in Mediation Analysis https://arxiv.org/abs/2411.10648 #stat.ME
Series Expansion of Probability of Correct Selection for Improved Finite Budget Allocation in Ranking and Selection https://arxiv.org/abs/2411.10695 #stat.ML #math.OC #cs.LG
Variance bounds and robust tuning for pseudo-marginal Metropolis--Hastings algorithms https://arxiv.org/abs/2411.10785 #math.ST #stat.CO #stat.TH
Improving Causal Estimation by Mixing Samples to Address Weak Overlap in Observational Studies https://arxiv.org/abs/2411.10801 #stat.ME
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