no code implementations • 28 Feb 2022 • Hossein Keshavarz, Meiyappan Nagappan
In this paper, we present ApacheJIT, a large dataset for Just-In-Time defect prediction.
no code implementations • 16 Mar 2020 • Hossein Keshavarz, George Michailidis
The problem of identifying change points in high-dimensional Gaussian graphical models (GGMs) in an online fashion is of interest, due to new applications in biology, economics and social sciences.
1 code implementation • 12 Sep 2019 • Hossein Keshavarz, Shohreh Tabatabayi Seifi, Mohammad Izadi
We generated a significant number of paired texts from this dataset and assigned each pair a score from 0 to 3, which demonstrates the degree of similarity between the domains of the pair.
no code implementations • 20 Jun 2018 • Hossein Keshavarz, George Michailidis, Yves Atchade
High dimensional piecewise stationary graphical models represent a versatile class for modelling time varying networks arising in diverse application areas, including biology, economics, and social sciences.
no code implementations • 15 Jan 2016 • Hossein Keshavarz, Clayton Scott, XuanLong Nguyen
Gaussian random fields are a powerful tool for modeling environmental processes.
no code implementations • 3 Jun 2015 • Hossein Keshavarz, Clayton Scott, XuanLong Nguyen
By contrast, the standard CUSUM method, which does not account for the covariance structure, is shown to be asymptotically optimal only in the increasing domain.