Machine learning tutorials and papers; possibly interesting, hopefully helpful.


As I finish up my academic career in the next week, I thought it’d be fun to share some of the work I’ve done over the past few years. Several of these papers are already on Arxiv; others probably would’ve never seen another read after finishing up the class I wrote them for. Here I’ll be uploading some of these works, along with extended versions of previously written papers that show derivations and can provide somewhat of a tutorial in various topics (ex. variational inference/Gibbs sampling, soon to come). I’ll also be providing source code when possible to help others replicate (or correct) my results.

Now for the boring part, a bit about me. I’m a senior at Carnegie Mellon graduating in May 2016 with a BS in Computer Science and a minor in Machine Learning. I like building things. Software things. And some math is fun. After college I plan to keep working on some ML-related side projects, which hopefully will find their way to this blog.

Posted 3 weeks ago