activity
20182022
most citedApacheJIT: A Large Dataset for Just-In-Time Defect Prediction

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

cs.SE20221 cited

ApacheJIT: A Large Dataset for Just-In-Time Defect Prediction

Hossein Keshavarz, Meiyappan Nagappan

In this paper, we present ApacheJIT, a large dataset for Just-In-Time defect prediction. ApacheJIT consists of clean and bug-inducing software changes in popular Apache projects. A…

math.ST2020

Online detection of local abrupt changes in high-dimensional Gaussian graphical models

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…

cs.CL2019

A Deep Learning-Based Approach for Measuring the Domain Similarity of Persian Texts

Hossein Keshavarz, Shohreh Tabatabayi Seifi, Mohammad Izadi

In this paper, we propose a novel approach for measuring the degree of similarity between categories of two pieces of Persian text, which were published as descriptions of two sepa…

math.ST2018

Local inversion-free estimation of spatial Gaussian processes

Hossein Keshavarz, XuanLong Nguyen, Clayton Scott

Maximizing the likelihood has been widely used for estimating the unknown covariance parameters of spatial Gaussian processes. However, evaluating and optimizing the likelihood fun…

stat.ML2018

Sequential change-point detection in high-dimensional Gaussian graphical models

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, econ…