3 citations · 3 across the 5 of their papers we have counts for
6 papers
Detecting Changes in Causal Dependence with Kernels and Copulas
Shakeel Gavioli-Akilagun, Kieran Wood, Francesco Quinzan
We propose a framework for determining whether the causal dependence of an outcome on a covariate changes at a given time point, given confounders . For ins…
Detecting Changes in Production Frontiers
Shakeel Gavioli-Akilagun, Yining Chen, Flavio Ziegelmann
We study the problem of estimating locations in time at which the level of technology in an economy changes when given a sequence of time ordered inputs and outputs. We approach th…
Kernel Integrated : A Measure of Dependence
Pouya Roudaki, Shakeel Gavioli-Akilagun, Florian Kalinke +2
We introduce kernel integrated , a new measure of statistical dependence that combines the local normalization principle of the recently introduced integrated with the f…
AdaDetectGPT: Adaptive Detection of LLM-Generated Text with Statistical Guarantees
Hongyi Zhou, Jin Zhu, Pingfan Su +4
We study the problem of determining whether a piece of text has been authored by a human or by a large language model (LLM). Existing state of the art logits-based detectors make u…
Optimal Online Change Detection via Random Fourier Features
Florian Kalinke, Shakeel Gavioli-Akilagun
This article studies the problem of online non-parametric change point detection in multivariate data streams. We approach the problem through the lens of kernel-based two-sample t…
Fast and Optimal Inference for Change Points in Piecewise Polynomials via Differencing
Shakeel Gavioli-Akilagun, Piotr Fryzlewicz
We consider the problem of uncertainty quantification in change point regressions, where the signal can be piecewise polynomial of arbitrary but fixed degree. That is we seek disjo…