Machine Learning in High Energy Physics

I begin with a brief discussion of the nature of high energy physics, and follow with a review of a few real-world examples of the application of machine learning methods in this field. I focus on the common, but difficult task, of extracting small signals masked by enormous backgrounds. The talk ends with a discussion of the computational challenges we expect to face in the very near future at the Large Hadron Collider and an enumeration of what my colleagues and I see as open questions.