Philosophy and Machine Learning

Philosophy and Machine Learning - Workshop @ NIPS 2011

Sierra Nevada, Spain - 17 December 2011

 

Program

07:30 - 07:40 Introduction
Organizers
07:40 - 08:40 Invited talk: Between the Philosophy of Science and Machine Learning
David Corfield (University of Kent)
08:40 - 09:10 Information, Learning and Falsification
David Balduzzi (MPI for Intelligent Systems)
09:10 - 09:30 Coffee break
09:30 - 10:00 On the Computability and Complexity of Bayesian Reasoning
Daniel Roy (University of Cambridge)
10:00 - 10:15 A Neural-Symbolic Approach to the Contemporary Theory of Metaphor
Artur dAvila Garcez (City University London), Guido Boella (Università di Torino), Alan Perotti(Università di Torino)
10:15 - 10:30 Bayesian Causal Induction
Pedro Ortega (MPI for Biological Cybernetics)
10:30 - 16:00 Ski Break
16:00 - 17:00 Invited talk: Foundations of Induction
Marcus Hutter (Australian National University)
17:00 - 17:30 Beyond calculation: probabilistic computing machines and universal stochastic inference
Vikash Mansinghka (MIT)
17:30 - 17:45 Coffee Break
17:45 - 18:15 Universal Learning vs. No Free Lunch Results
Shai Ben-David (University of Waterloo), Nathan Srebro (TTI-Chicago), Ruth Urner (University of Waterloo)
18:15 - 18:45 Are Mental Properties Supervenient on Brain Properties?
Joshua T. Vogelstein (Johns Hopkins University), R. Jacob Vogelstein (Johns Hopkins University), Carey E. Priebe (Johns Hopkins University)
18:45 - 19:00 Toward a New Representation for Causation in Dynamic Systems
Denver Dash (Intel Labs), Mark Voortman (University of Pittsburgh)
19:00 - 20:00 Panel and Group Discussion
(Joachim Buhmann, Tiberio Caetano, Nello Cristianini, Marcello Pelillo, Bob Williamson)