Monday (9/July) -- Friday (13/July)
Description:
Zoubin Ghahramani Tutorials: Nonparametric_Methods_zg.pdf, Machine_Learning_zg.pdf, Unsupervised_Learning.pdf.
Week 1: Basic Methods and Simple Applications:
Monday, Week 1
Tuesday, Week 1
Wednesday, Week 1
Thursday, Week 1
Friday, Week 1
Possible evening meetings for Week 1:
Really Basic Bayes (no, too simple), Scale Invariance
(Chater), Kolmogorov Complexity. Learning to control dynamical systems
(Jacobs), “Are people really Bayesian”
debate (Chater, Fox, Tenenbaum, Griffiths). Project meeting,
Monday, Week 2
Tuesday, Week 2
Wednesday, Week 2
Thursday, Week 2
Friday, Week 2
Possible evening meetings for Week 2. - Softward for Bayesian modeling (Darwiche). How does cog sci relate to AI? (Russell; also Milch, Geman et al.)Connections to linguistics (UCLA linguists, plus Levy, Klein?)- Shiffrin: paradoxes of choice
Monday, Week 3
Tuesday, Week 3
Wednesday, Week 3
Thursday, Week 3
Possible evening meeting for Week 3 – Mathematical proofs – Rescorla-Wagner, limits of hierarchical
models.
Further
Ideas:
Student projects: - Optional,
introduced in first week by faculty with ideas (evening session?) - Have
students sign up to give talks on their research in the evening (Do this
*before* the conference so we can choose the good ones, and they can prepare!)
Maybe have recitations/discussions, led be permanent faculty (and other UCLA
folks)
Empower students to organize
activities (sports, hikes, ...) Noah (come as much as
possible?) Amy
Can students get library access? Or can we assemble a library at IPAM, from web sources and UCLA
Software: Get some software
packages together in advance. Who can help with this? Darwiche and students? Murphy?
Other speakers to line up? Mark Johnson. Nando de Freitas (week 3, near math psych).