Machine Learning is evolving to utilize new hardware such as GPUs and large commodity clusters. University and industry researchers have been using these new computing platforms to scale machine learning across many dimensions.
Matroid is organizing this conference on Stanford University campus with the aim of bringing together researchers running machine learning algorithms on a variety of computing platforms to foster discussions between them. The goal is to encourage algorithm designers for these platforms to help each other scale and transplant ideas between the platforms.
