arXiv Statistics @arxiv_stats@qoto.org

Predicting Power Grid Failures Using Self-Organized Criticality: A Case Study of the Texas Grid 2014-2022 https://arxiv.org/abs/2504.10675 #stat.AP

Power properties of the two sample test based on nearest neighbors graphs https://arxiv.org/abs/2504.10719 #math.ST #stat.TH

Gaussian Approximation for High-Dimensional $U$-statistics with Size-Dependent Kernels https://arxiv.org/abs/2504.10866 #math.ST #stat.TH

Can SGD Select Good Fishermen? Local Convergence under Self-Selection Biases and Beyond https://arxiv.org/abs/2504.07133 #stat.ML #math.ST #stat.TH #cs.DS #cs.LG

NFL Draft Modelling: Loss Functional Analysis https://arxiv.org/abs/2504.07291 #stat.AP #stat.ME

Effective treatment allocation strategies under partial interference https://arxiv.org/abs/2504.07305 #stat.ME #stat.AP

A Unified Framework for Large-Scale Classification: Error Rate Control and Optimality https://arxiv.org/abs/2504.07321 #stat.ME

What is the price of approximation? The saddlepoint approximation to a likelihood function https://arxiv.org/abs/2504.07324 #stat.ME

Throughput-Optimal Scheduling Algorithms for LLM Inference and AI Agents https://arxiv.org/abs/2504.07347 #stat.ML #math.PR #cs.LG

A GARMA Framework for Unit-Bounded Time Series Based on the Unit-Lindley Distribution with Application to Renewable Energy Data https://arxiv.org/abs/2504.07351 #math.ST #stat.AP #stat.TH

Estimand framework development for eGFR slope estimation and comparative analyses across various estimation methods https://arxiv.org/abs/2504.07411 #stat.ME

Regression for Left-Truncated and Right-Censored Data: A Semiparametric Sieve Likelihood Approach https://arxiv.org/abs/2504.07413 #stat.ME

Conditional Data Synthesis Augmentation https://arxiv.org/abs/2504.07426 #stat.ME #cs.LG

Deep Fair Learning: A Unified Framework for Fine-tuning Representations with Sufficient Networks https://arxiv.org/abs/2504.06470 #stat.ML #cs.LG

Sparsified-Learning for Heavy-Tailed Locally Stationary Processes https://arxiv.org/abs/2504.06477 #stat.ML #math.ST #stat.TH #cs.LG

LassoRNet: Accurate dim-light melatonin onset time prediction from multiple blood tissue samples https://arxiv.org/abs/2504.06494 #stat.AP #stat.CO

The Software Behind the Stats: A Student Exploration of Software Trends Across Disciplines https://arxiv.org/abs/2504.06507 #stat.OT

Estimation of rates in population-age-dependent processes by means of test functions https://arxiv.org/abs/2504.06516 #q-bio.PE #math.ST #math.PR #stat.TH

Sequential Change Point Detection with FDR Control in Reconfigurable Sensor Networks https://arxiv.org/abs/2504.06526 #stat.ME

Hyperflows: Pruning Reveals the Importance of Weights https://arxiv.org/abs/2504.05349 #stat.ML #cs.AI #cs.LG