Learning topic models: Identifiability and finite-sample analysis
Topic models provide a useful text-mining tool for learning, extracting, and discovering latent
structures in large text corpora. Although a plethora of methods have been proposed for …
structures in large text corpora. Although a plethora of methods have been proposed for …
DOLDA: a regularized supervised topic model for high-dimensional multi-class regression
Generating user interpretable multi-class predictions in data-rich environments with many
classes and explanatory covariates is a daunting task. We introduce Diagonal Orthant Latent …
classes and explanatory covariates is a daunting task. We introduce Diagonal Orthant Latent …
Polya urn latent Dirichlet allocation: a doubly sparse massively parallel sampler
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 …
processing and machine learning. Most approaches to training the model rely on iterative …
The cambridge law corpus: a dataset for legal AI research
Abstract We introduce the Cambridge Law Corpus (CLC), a corpus for legal AI research. It
consists of over 250 000 court cases from the UK. Most cases are from the 21st century, but …
consists of over 250 000 court cases from the UK. Most cases are from the 21st century, but …
Automatic localization of bugs to faulty components in large scale software systems using bayesian classification
We suggest a Bayesian approach to the problem of reducing bug turn-around time in large
software development organizations. Our approach is to use classification to predict where …
software development organizations. Our approach is to use classification to predict where …
[图书][B] Machine learning-based bug handling in large-scale software development
L Jonsson - 2018 - books.google.com
This thesis investigates the possibilities of automating parts of the bug handling process in
large-scale software development organizations. The bug handling process is a large part of …
large-scale software development organizations. The bug handling process is a large part of …
Exploit latent Dirichlet allocation for collaborative filtering
Previous work on the one-class collaborative filtering (OCCF) problem can be roughly
categorized into pointwise methods, pairwise methods, and content-based methods. A …
categorized into pointwise methods, pairwise methods, and content-based methods. A …
Discovering medication patterns for high-complexity drug-using diseases through electronic medical records
An Electronic Medical Record (EMR) is a professional document that contains all data
generated during the treatment process. The EMR can utilize various data formats, such as …
generated during the treatment process. The EMR can utilize various data formats, such as …
Bayesian allocation model: Inference by sequential monte carlo for nonnegative tensor factorizations and topic models using polya urns
We introduce a dynamic generative model, Bayesian allocation model (BAM), which
establishes explicit connections between nonnegative tensor factorization (NTF), graphical …
establishes explicit connections between nonnegative tensor factorization (NTF), graphical …
DOLDA-a regularized supervised topic model for high-dimensional multi-class regression
M Magnusson, L Jonsson, M Villani - arXiv preprint arXiv:1602.00260, 2016 - arxiv.org
Generating user interpretable multi-class predictions in data rich environments with many
classes and explanatory covariates is a daunting task. We introduce Diagonal Orthant Latent …
classes and explanatory covariates is a daunting task. We introduce Diagonal Orthant Latent …