17 citations · 20 across the 4 of their papers we have counts for
6 papers
Adopting Automated Bug Assignment in Practice: A Longitudinal Case Study at Ericsson
Markus Borg, Leif Jonsson, Emelie Engström +2
The continuous inflow of bug reports is a considerable challenge in large development projects. Inspired by contemporary work on mining software repositories, we designed a prototy…
Adopting Automated Bug Assignment in Practice -- A Registered Report of an Industrial Case Study
Markus Borg, Leif Jonsson, Emelie Engström +2
[Background/Context] The continuous inflow of bug reports is a considerable challenge in large development projects. Inspired by contemporary work on mining software repositories,…
Sparse Parallel Training of Hierarchical Dirichlet Process Topic Models
Alexander Terenin, Måns Magnusson, Leif Jonsson
To scale non-parametric extensions of probabilistic topic models such as Latent Dirichlet allocation to larger data sets, practitioners rely increasingly on parallel and distribute…
Pólya Urn Latent Dirichlet Allocation: a doubly sparse massively parallel sampler
Alexander Terenin, Måns Magnusson, Leif Jonsson +1
Latent Dirichlet Allocation (LDA) is a topic model widely used in natural language processing and machine learning. Most approaches to training the model rely on iterative algorith…
DOLDA - a regularized supervised topic model for high-dimensional multi-class regression
Måns Magnusson, Leif Jonsson, Mattias Villani
Generating user interpretable multi-class predictions in data rich environments with many classes and explanatory covariates is a daunting task. We introduce Diagonal Orthant Laten…
Sparse Partially Collapsed MCMC for Parallel Inference in Topic Models
Måns Magnusson, Leif Jonsson, Mattias Villani +1
Topic models, and more specifically the class of Latent Dirichlet Allocation (LDA), are widely used for probabilistic modeling of text. MCMC sampling from the posterior distributio…