![[Search]](/static/images/search.gif){kind=small}
![[A-Z Index]](/static/images/az.gif){kind=small}
![[Contact]](/static/images/contact.gif){kind=small}
![[University of Cambridge]](/static/images/identifier2.gif){kind=small}
![[Talks.cam]](/static/images/talkslogosmall.gif)
Silvia Chiappa
Monday 01 November 2010, 10:00-11:00
Probabilistic models for time-series with different underlying dynamics regimes with application to robot imitation learning
- đ¤ Speaker: Silvia Chiappa
- đ Date & Time: Monday 01 November 2010, 10:00 - 11:00
- đ Venue: Small public lecture room, Microsoft Research Ltd, 7 J J Thomson Avenue (Off Madingley Road), Cambridge
Abstract
In this talk I will describe several probabilistic models for analysing time-series containing different underlying dynamics regimes, and discuss approximation schemes for dealing with intractable inference. I will first present a Bayesian approach to switching and mixtures of linear dynamical systems (LDS) for incorporating prior domain knowledge and enforcing a sparse parametrisation. I will then introduce an extension of the switching LDS with regime-duration-distribution and time-warping modeling for extracting repeated occurrences of basic shapes. I will show how these models can be applied to robot imitation learning.
Series This talk is part of the Microsoft Research Cambridge, public talks series.
Included in Lists
- All Talks (aka the CURE list)
- bld31
- Cambridge Centre for Data-Driven Discovery (C2D3)
- Cambridge talks
- Chris Davis' list
- Guy Emerson's list
- Interested Talks
- Microsoft Research Cambridge, public talks
- ndk22's list
- ob366-ai4er
- Optics for the Cloud
- personal list
- PMRFPS's
- rp587
- School of Technology
- Small public lecture room, Microsoft Research Ltd, 7 J J Thomson Avenue (Off Madingley Road), Cambridge
- Trust & Technology Initiative - interesting events
- yk449
Note: Ex-directory lists are not shown.