Plenary 2: The Mathematics of Causal Inference: with Reflections on Machine Learning
The development of graphical models and the logic of counterfactuals have had a marked effect on the way scientists treat problems involving cause-effect relationships. Practical problems requiring causal information, which long were regarded as either…
Research in Focus – Building an Automated Statistician
Zoubin Ghahramani, Professor of Information Engineering, University of Cambridge The application of Bayesian models has opened up new possiblities for teaching computers to draw inferences from data, with little or no intervention on the part…
Machine Learning Summit 2013
The Machine Learning Summit 2013, held in Paris, brought together thought leaders and researchers from a broad range of disciplines. Together they highlighted some of the key challenges posed by the new era of machine…
Machine Learning Welcome and Introductory Talk
Alan Crozier, Vice President, Microsoft France, welcomes everyone to the Microsoft Machine Learning Summit 2013. Rick Rashid, Chief Research Office, Microsoft Research Redmond, provides the introductory talk.
Research in Focus – Teaching Machines to See
Fei Fei Li, Associate Professor, Stanford University and Sebastian Nowozin, Researcher, Microsoft Research Cambridge. When we visually perceive the world, we intuitively recognize objects, scene categories, human motions—all sorts of semantically meaningful interpretations of what…
Plenary 1: Machines (that learn) to See
Andrew Blake, Distinguished Scientist, Lab Director of Microsoft Research Cambridge. Discusses the question of whether intelligent systems will turn out to depend more on theories and models, or simply on largely amorphous networks trained on…
Focus in France on Machine Learning
From April 22 to 24, Microsoft Research will host the Machine Learning Summit 2013 at Microsoft’s Le Campus in Issy-les-Moulineaux, just outside of Paris. The event gathers thought leaders and researchers who will discuss key…