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TITLE
DATE
VIEWS
Dense Neural Networks are not Universal Approximators
By Levi Rauchwerger, Stefanie Jegelka, Ron Levie · ArXiv: 2602.07618
2026-02-10
0
Fast Rerandomization for Balancing Covariates in Randomized Experiments: A Metropolis-Hastings Framework
By Jiuyao Lu, Tianruo Zhang, Ke Zhu · ArXiv: 2602.07613
2026-02-07
0
Beyond Arrow: From Impossibility to Possibilities in Multi-Criteria Benchmarking
By Polina Gordienko, Christoph Jansen, Julian Rodemann · ArXiv: 2602.07593
2026-02-07
0
Gaussian Match-and-Copy: A Minimalist Benchmark for Studying Transformer Induction
By Antoine Gonon, Alex, re Cordonnier · ArXiv: 2602.07562
2026-02-07
0
Deriving Neural Scaling Laws from the statistics of natural language
By Francesco Cagnetta, Allan Raventós, Surya Ganguli · ArXiv: 2602.07488
2026-02-12
0
Event-driven type design for clinical trials with recurrent events
By Jingwen Zhang, Satoshi Hattori · ArXiv: 2602.07482
2026-02-07
0
Statistical inference after variable selection in Cox models: A simulation study
By Lena Schemet, Sarah Friedrich-Welz · ArXiv: 2602.07477
2026-02-07
0
Bandit Allocational Instability
By Yilun Chen, Jiaqi Lu · ArXiv: 2602.07472
2026-02-07
0
Consistency Assessment of Regional Treatment Effect for Multi-Regional Clinical Trials in the Presence of Covariate Shift
By Kunhai Qing, Xinru Ren, Jin Xu · ArXiv: 2602.07468
2026-02-07
0
Estimation of log-Gaussian gamma processes with iterated posterior linearization and Hamiltonian Monte Carlo
By Teemu Härkönen, Simo Särkkä · ArXiv: 2602.07454
2026-02-07
0
Data-Aware and Scalable Sensitivity Analysis for Decision Tree Ensembles
By Namrita Varshney, Ashutosh Gupta, Arhaan Ahmad · ArXiv: 2602.07453
2026-02-07
0
Adaptive Experimental Design Using Shrinkage Estimators
By Evan T. R. Rosenman, Kristen B. Hunter · ArXiv: 2602.07404
2026-02-07
0
The ABL Rule and the Perils of Post-Selection
By Jacob A. Bar, es · ArXiv: 2602.07402
2026-02-07
0
Balancing Covariates in Survey Experiments
By Pengfei Tian, Jiyang Ren, Yingying Ma · ArXiv: 2602.07390
2026-02-07
0
Dichotomy of Feature Learning and Unlearning: Fast-Slow Analysis on Neural Networks with Stochastic Gradient Descent
By Shota Imai, Sota Nishiyama, Masaaki Imaizumi · ArXiv: 2602.07378
2026-02-07
0
Privately Learning Decision Lists and a Differentially Private Winnow
By Mark Bun, William Fang · ArXiv: 2602.07370
2026-02-07
0
Robust Ultra-High-Dimensional Variable Selection With Correlated Structure Using Group Testing
By Wanru Guo, Juan Xie, Binbin Wang · ArXiv: 2602.07258
2026-02-06
0
Beyond Euclidean Summaries: Online Change Point Detection for Distribution-Valued Data
By Yingyan Zeng, Yujing Huang, Xiaoyu Chen · ArXiv: 2602.07252
2026-02-06
0
Modelling heavy tail data with bayesian nonparametric mixtures
By Luis E. Nieto-Barajas · ArXiv: 2602.07228
2026-02-06
0
Collaborative and Efficient Fine-tuning: Leveraging Task Similarity
By Gagik Magakyan, Amirhossein Reisizadeh, Chanwoo Park · ArXiv: 2602.07218
2026-02-06
0
Online Learning for Uninformed Markov Games: Empirical Nash-Value Regret and Non-Stationarity Adaptation
By Junyan Liu, Haipeng Luo, Zihan Zhang · ArXiv: 2602.07205
2026-02-06
0
Bayesian Dynamic Gamma Models for Route-Level Travel Time Reliability
By Vadim Sokolov, Refik Soyer · ArXiv: 2602.07170
2026-02-06
0
PoissonRatioUQ: An R package for band ratio uncertainty quantification
By Matthew LeDuc, Tomoko Matsuo · ArXiv: 2602.07165
2026-02-06
0
Free Energy Mixer
By Jiecheng Lu, Shihao Yang · ArXiv: 2602.07160
2026-02-06
0
Functional Estimation of the Marginal Likelihood
By Omiros Papaspiliopoulos, Timothée Stumpf-Fétizon, Jonathan Weare · ArXiv: 2602.07148
2026-02-06
0
BONSAI: Bayesian Optimization with Natural Simplicity and Interpretability
By Samuel Daulton, David Eriksson, Maximilian Bal · ArXiv: 2602.07144
2026-02-06
0
Fast and Robust Likelihood-Guided Diffusion Posterior Sampling with Amortized Variational Inference
By Léon Zheng, Thomas Hirtz, Yazid Janati · ArXiv: 2602.07102
2026-02-06
0
Scalable spatial point process models for forensic footwear analysis
By Alokesh Manna, Neil Spencer, Dipak K. Dey · ArXiv: 2602.07006
2026-01-30
0
On micromodes in Bayesian posterior distributions and their implications for MCMC
By Sanket Agrawal, Sebastiano Grazzi, Gareth O. Roberts · ArXiv: 2602.06931
2026-02-06
0
Continuous-time reinforcement learning: ellipticity enables model-free value function approximation
By Wenlong Mou · ArXiv: 2602.06930
2026-02-06
0
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