Research

I am interested in machine learning and its applications to systems and security problems.

My projects include:
     A Gaussian Latent Variable Model for Large Margin Classification of Labeled and Unlabeled Data
     Topic Modeling of Freelance Job Postings to Monitor Web Service Abuse.

Publication

Do-kyum Kim, Geoffrey M. Voelker and Lawrence K. Saul.
Topic Modeling of Hierarchical Corpora.
Submitted for publication.
[arXiv]

Karl Stratos, Do-kyum Kim, Daniel Hsu and Michael Collins.
A Spectral Algorithm for Learning Class-Based n-gram Models of Natural Language.
In Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence (UAI 2014). Quebec City, Canada.
[paper]

Do-kyum Kim, Matthew Der and Lawrence K. Saul.
A Gaussian Latent Variable Model for Large Margin Classification of Labeled and Unlabeled Data.
In Proceedings of the 17th International Conference on Artificial Intelligence and Statistics (AISTATS 2014). Reykjavik, Iceland.
[paper] [supplement] [bib] [webpage]

Do-kyum Kim, Geoffrey M. Voelker and Lawrence K. Saul.
A Variational Approximation for Topic Modeling of Hierarchical Corpora.
In Proceedings of the 30th International Conference on Machine Learning (ICML 2013). Atlanta, GA.
[paper] [supplement] [bib]

Do-kyum Kim, Marti Motoyama, Geoffrey M. Voelker and Lawrence K. Saul.
Topic Modeling of Freelance Job Postings to Monitor Web Service Abuse.
In Proceedings of the 4th ACM workshop on Artificial Intelligence and Security (AISec 2011). Chicago, IL.
[paper] [slides] [bib] [webpage]