First order expansion of convex regularized estimators. - Pierre C. Bellec; Arun K. Kuchibhotla (NeurIPS, 2019)

On Least Squares Estimation under Heteroscedastic and Heavy-Tailed Errors. - Arun K. Kuchibhotla; Rohit K. Patra (CoRR, 2019)

Near-Optimal Confidence Sequences for Bounded Random Variables. - Arun K. Kuchibhotla; Qinqing Zheng (ICML, 2021)

Mitigating multiple descents: A model-agnostic framework for risk monotonization. - Pratik Patil; Arun Kumar Kuchibhotla; Yuting Wei 001; Alessandro Rinaldo (CoRR, 2022)

Nested conformal prediction and quantile out-of-bag ensemble methods. - Chirag Gupta; Arun K. Kuchibhotla; Aaditya Ramdas (Pattern Recognit., 2022)

Subsample Ridge Ensembles: Equivalences and Generalized Cross-Validation. - Jin-Hong Du; Pratik Patil; Arun K. Kuchibhotla (ICML, 2023)

Bagging in overparameterized learning: Risk characterization and risk monotonization. - Pratik Patil; Jin-Hong Du; Arun Kumar Kuchibhotla (J. Mach. Learn. Res., 2023)

Extrapolated Cross-Validation for Randomized Ensembles. - Jin-Hong Du; Pratik Patil; Kathryn Roeder; Arun Kumar Kuchibhotla (J. Comput. Graph. Stat., 2024)

Statistical Inference for Online Algorithms. - Selina Carter; Arun K. Kuchibhotla (CoRR, 2025)