New Spearmint Release

 

After many months of updates and new research, we're announcing a completely updated version of Spearmint, our tool for Bayesian optimization. It is available for use under a non-commercial license. This is a long-term collaboration between Jasper Snoek, Kevin Swersky, Hugo Larochelle, Michael Gelbart, and Ryan Adams. This includes implementations of the following papers:

MICMAT: Python Scientific Computing on Intel Xeon Phi

 

Oren Rippel has recently released the first version of his new Python library MICMAT. This library has a similar functionality to cudamat, but is focused on Intel's newXeon Phi (MIC) architecture, rather than nVidia's CUDA. MICMAT allows you to perform useful memory management and dense linear algebra computations on the MIC coprocessor, from a Python interface.

"Firefly Monte Carlo" Wins Best Paper at UAI

 

Dougal Maclaurin's paper Firefly Monte Carlo: Exact MCMC with Subset of Data has won the Microsoft Best Paper Award at this year's Conference on Uncertainty in Artificial Intelligence (UAI). Congrats Dougal!

Five Papers at ICML 2014

 

The HIPS group co-authored five papers to appear at this year's International Conference on Machine Learning (ICML).