arXiv Statistics @arxiv_stats@qoto.org

Sparsity-Inducing Categorical Prior Improves Robustness of the Information Bottleneck. (arXiv:2203.02592v1 [stat.ML]) http://arxiv.org/abs/2203.02592

Improved Pathwise Coordinate Descent for Power Penalties. (arXiv:2203.02596v1 [stat.ME]) http://arxiv.org/abs/2203.02596

False clustering rate in mixture models. (arXiv:2203.02597v1 [math.ST]) http://arxiv.org/abs/2203.02597

High-dimensional Censored Regression via the Penalized Tobit Likelihood. (arXiv:2203.02601v1 [stat.ME]) http://arxiv.org/abs/2203.02601

Reinforcement Learning in Modern Biostatistics: Constructing Optimal Adaptive Interventions. (arXiv:2203.02605v1 [stat.ML]) http://arxiv.org/abs/2203.02605

Target Network and Truncation Overcome The Deadly triad in $Q$-Learning. (arXiv:2203.02628v1 [cs.LG]) http://arxiv.org/abs/2203.02628

Theoretical results and modeling under the discrete Birnbaum-Saunders distribution. (arXiv:2203.02639v1 [stat.ME]) http://arxiv.org/abs/2203.02639

From local to global gene co-expression estimation using single-cell RNA-seq data. (arXiv:2203.01990v1 [stat.ME]) http://arxiv.org/abs/2203.01990

Multi-objective robust optimization using adaptive surrogate models for problems with mixed continuous-categorical parameters. (arXiv:2203.01996v1 [stat.ME]) http://arxiv.org/abs/2203.01996

On consistency of constrained spectral clustering under representation-aware stochastic block model. (arXiv:2203.02005v1 [stat.ML]) http://arxiv.org/abs/2203.02005

Why adversarial training can hurt robust accuracy. (arXiv:2203.02006v1 [cs.LG]) http://arxiv.org/abs/2203.02006

The starting dates of COVID-19 multiple waves. (arXiv:2203.02011v1 [q-bio.PE]) http://arxiv.org/abs/2203.02011

Interventions, Where and How? Experimental Design for Causal Models at Scale. (arXiv:2203.02016v1 [cs.LG]) http://arxiv.org/abs/2203.02016

Online Balanced Experimental Design. (arXiv:2203.02025v1 [stat.ME]) http://arxiv.org/abs/2203.02025

Symmetry Structured Convolutional Neural Networks. (arXiv:2203.02056v1 [stat.ML]) http://arxiv.org/abs/2203.02056

Interpretable Latent Variables in Deep State Space Models. (arXiv:2203.02057v1 [stat.ML]) http://arxiv.org/abs/2203.02057

Bayesian community detection for networks with covariates. (arXiv:2203.02090v1 [stat.ME]) http://arxiv.org/abs/2203.02090

Neural Galerkin Scheme with Active Learning for High-Dimensional Evolution Equations. (arXiv:2203.01360v1 [math.NA]) http://arxiv.org/abs/2203.01360

Faking feature importance: A cautionary tale on the use of differentially-private synthetic data. (arXiv:2203.01363v1 [cs.LG]) http://arxiv.org/abs/2203.01363

A Survey on Offline Reinforcement Learning: Taxonomy, Review, and Open Problems. (arXiv:2203.01387v1 [cs.LG]) http://arxiv.org/abs/2203.01387