April 23, 2013

Machine Learning Summit 2013

13:30–17:00 GMT

Location: Paris, France

April 22

Time	Session	Location
19:30	Welcome Drinks Reception	Concorde La Fayette

April 23

Time	Session	Speaker	Location
07:35	Coach Transfer to Microsoft Le Campus		Concorde La Fayette
08:15	Light Breakfast and Registration		Arc-en-Ciel
09:00	Opening/Welcome remarks	Alain Crozier, President, Microsoft France	Grand Bleu
09:10	Introductory Talk	Rick Rashid, Microsoft Research	Grand Bleu
09:30	Plenary 1 Keynote: Machines that (Learn to) See	Chair: Chris Bishop, Microsoft Research Andrew Blake, Microsoft Research
10:30	Break		Arc-en-Ciel
11:00	Parallel Sessions
	Session 1: Model-Based Machine Learning in Practice	Chair: John Bronskill, Microsoft Research Thomas Minka, Microsoft Research	Rubis
	Session 2: Large Scale Machine Learning	Chair: Leon Bottou, Microsoft Research Francis Bach, INRIA – Ecole Normale Superieure Anatoli Juditski, University J. Fourier of Grenoble Alekh Agarwal, Microsoft Research	Grand Bleu
	Session 3: Game Theory Meets Machine Learning	Chair: Laurent Massoulie, Microsoft Research-Inria Joint Centre Avrim Blum, Carnegie Mellon University Amos Storkey, University of Edinburgh Peter Key, Microsoft Research	Prairie
12:30	Lunch		Arc-en-Ciel
13:30	Parallel Sessions
13:30	Session 4: Learning with Millions of Categories	Chair: Yann LeCun, New York University Samy Bengio, Google Fei-Fei Li, Stanford University P. Anandan, Microsoft Research	Prairie
	Session 5: Model-Based Machine Learning Tutorial with Infer.NET	Chair: John Bronskill, Microsoft Research John Guiver, Microsoft Research	Rubis
	Session 6: Machine Learning and Social Data	Chair: Pushmeet Kohli, Microsoft Research Foster Provost, New York University Sharad Goel, Microsoft Research Elad Yom-Tov, Microsoft Research	Grand Bleu
15:00	DemoFest	Machine Learning for Xbox Live Noam Koenigstein, Microsoft Research; Ulrich Paquet, Microsoft Research Automatic Segmentation of High-grade Brain Tumours by Context-sensitive Decision Forests Darko Zikic, Microsoft Research Teaching Kinect to Read Your Body and Hands Jamie Shotton, Microsoft Research A weakly-supervised approach for building statistical conversational understanding models Dilek Hakkani-Tur, Microsoft Research; Larry Heck, Microsoft Research; Gokhan Tur, Microsoft Research; Asli Celikyilmaz, Microsoft Research Model-based Machine Learning Using Infer.Net John Bronskill, Microsoft Research Real-Time Business Metadata Extraction Dimitrios Lymberopoulos, Microsoft Research Juggling the Jigsaw: Towards Automated Problem Inference from Network Trouble Tickets Navendu Jain, Microsoft Research Querying Human Activities – Social Media Analytics Platform Emre Kiciman, Microsoft Research Probabilistic Programming with Try F# Christophe Poulain, Microsoft Research	Arc-en-Ciel
17:00	Plenary 2 Keynote: The Mathematics of Causal Inference: with Reflections on Machine Learning	Chair: Tony Hey Judea Pearl, University of California	Grand Bleu
18:00	Close
18:15	Coach Transfer to La Gare Restaurant		Microsoft Le Campus
19:00	Evening Dinner
22:00	Coach Transfer to Concorde La Fayette		La Gare Restaurant

April 24

Time	Session	Speaker	Location
07:35	Coach Transfer to Microsoft Le Campus		Concorde La Fayette
08:15	Light Breakfast		Arc-en-Ciel
09:00	Plenary 3 Keynote: Data is accumulating at such a rate that there are no longer enough qualified humans to analyse it	Chair: Peter Lee, Microsoft Research Hermann Hauser, Amadeus Capital Partners	Grand Bleu
10:00	Break		Arc-en-Ciel
10:30	Parallel Sessions
	Session 7: Machine Learning in Healthcare	Chair: Silvia Chiappa, Microsoft Research David Page, University of Wisconsin-Madison Antonio Criminisi, Microsoft Research Bert Kappen, University of Radboud	Grand Bleu
	Session 8: Machine Learning for Computer Vision	Chair: Sebastian Nowozin, Microsoft Research Carsten Rother, Microsoft Research Tomas Werner, Czech Technical University Bill Freeman, Massachusetts Institute of Technology	Prairie
	Session 9: Causality and Machine Learning	Chair: Zoubin Ghahramani, University of Cambridge Isabelle Guyon, ChaLearn. Thomas Richardson, University of Washington Leon Bottou, Microsoft Research	Rubis
12:00	Lunch		Arc-en-Ciel
13:00	Parallel Sessions
	Session 10: The Future of Probabilistic Programming	Chair: Thore Graepel, Microsoft Research Andy Gordon, Microsoft Research Vikash Mansinghka, Massachusetts Institute of Technology Avi Pfeffer, Charles River Analytics Christopher Re, University of Wisconsin-Madison	Prairie
	Session 11: Machine Learning and Natural Language	Chair: Ronan Collobert, Idiap Research Institute Steve Renals, University of Edinburgh Hermann Ney, RWTH Aachen University Alex Acero, Microsoft Research	Grand Bleu
	Session 12: Machine Learning and Crowdsourcing	Chair: Yoram Bachrach, Microsoft Research Emre Kiciman, Microsoft Research Eyal Amir, University of Illinois, Urbana-Champaign David Parkes, Harvard University	Rubis
14:30	Break		Arc-en-Ciel
	Plenary 4 Keynote: Data Challenges and Opportunities in the Next Decade	Chair: Jeannette Wing, Microsoft Research Panelists: Eric Horvitz, Microsoft Research Michel Cosnard, INRIA. Iain Buchan, Manchester University Lionel Tarassenko, University of Oxford	Grand Bleu
16:00	Closing Remarks	Chris Bishop, Microsoft Research Evelyne Viegas, Microsoft Research	Grand Bleu
16:10	Close of Day