From the 1 of 103 linked papers with an AI index.
13 papers · 1 filter
Distribution-free changepoint localization after sequential change detection
Aytijhya Saha, Aaditya Ramdas
This paper introduces a distribution-free framework for constructing post-detection confidence sets for changepoints after stopping a sequential change detection procedure. It is w…
Online monotone density estimation and log-optimal calibration
Rohan Hore, Ruodu Wang, Aaditya Ramdas
We study the problem of online monotone density estimation, where density estimators must be constructed in a predictable manner from sequentially observed data. We propose two onl…
Vector-valued self-normalized concentration inequalities beyond sub-Gaussianity
Diego Martinez-Taboada, Tomas Gonzalez, Aaditya Ramdas
The study of self-normalized processes plays a crucial role in a wide range of applications, from sequential decision-making to econometrics. While the behavior of self-normalized…
Post-detection inference for sequential changepoint localization
Aytijhya Saha, Aaditya Ramdas
This paper addresses a fundamental but largely unexplored challenge in sequential changepoint analysis: conducting inference following a detected change. We develop a very general…
Operationalizing Stein's Method for Online Linear Optimization: CLT-Based Optimal Tradeoffs
Zhiyu Zhang, Aaditya Ramdas
Adversarial online linear optimization (OLO) is essentially about making performance tradeoffs with respect to the unknown difficulty of the adversary. In the setting of one-dimens…
Conformal online model aggregation
Matteo Gasparin, Aaditya Ramdas
Conformal prediction equips machine learning models with a reasonable notion of uncertainty quantification without making strong distributional assumptions. It wraps around any pre…