Writing Unit Tests for Sampling | Graham's Research Blog
One popular method for estimating statistical models is sampling, and in particular Gibbs sampling. As I’ve written before, sampling is based on randomness, which makes it somewhat difficult to debug. On the other hand, one popular way to ensure the quality of code is through arrays of unit tests, which are designed to test your code at a very fine-grained level (e.g. one test for each function in
Graham Neubig
I am an Associate Professor at the Carnegie Mellon University Language Technology Institute in the School of Computer Science, and work with a bunch of great students in my lab NeuLab. Prospective Students/Visitors: Please see the contact info page for more info. Research My research focuses on machine learning and natural language processing. In particular, I am interested in basic research and a
Sampling: Random Order? Corpus Order? | Graham's Research Blog
Machine Translation, Speech Recognition, Machine Learning, and the like. Gibbs sampling is a common technique that is used in Bayesian learning that is used to find the true distribution of some distribution over probabilistic variables that we cannot calculate directly. I won’t cover the details here, but Wikipedia or Pattern Recognition and Machine Learning give good introductions. But the impor
SVM, Logistic Regression, and Precision | Graham's Research Blog
Machine Translation, Speech Recognition, Machine Learning, and the like. On twitter a little while ago, @mathieuen asked an interesting question about whether the fact that he was seeing support vector machines (SVM) get better precision than logistic regression (LR) was a result of the learning algorithm (specifically the hinge loss function). I answered off the top of my head that I thought that
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