I encourage you all to come. Chris Williams is among the best researchers of our field and I always enjoy my exchanges with him.
-- Yoshua
On Sat, Oct 19, 2013 at 10:01 PM, Razvan Pascanu r.pascanu@gmail.comwrote:
Hi all,
Monday 28th October we will have Chris Williams giving to talks. Both of them will be in the rmm AA3195 (pavillon Andre-Aisendstandt, click herehttp://maps.google.ca/maps?q=2920,+chemin+de+la+tour&hl=en&z=16&iwloc=A for directions) at the Université de Montréal. Abstract and title below. Hope to see you there !
First talk at 10:30 in AA3195
Title: Missing Components in Visual Scene Understanding: Hierarchy and Perceptual Organization?
Chris Williams, School of Informatics, University of Edinburgh
There has been considerable progress in object recognition and scene understanding over the last decade. However, we argue that much of this work uses relatively shallow architectures, and that more attention needs to be paid to hierarchical models and to processes of perceptual organization, within a probabilistic inference framework.
Second talk at 13:30 in AA3195
Title: Switching Linear Dynamical Systems for Condition Monitoring in the Intensive Care Unit
Abstract:
Data drawn from an observed system is often usefully described by a number of hidden (or latent) factors. Given a sequence of observations, the task is to infer which latent factors are active at each time frame. In this talk I will describe the application of a switching linear dynamical model to monitoring the condition of a patient receiving intensive care. The state of health of a patient cannot be observed directly, but different underlying factors are associated with particular patterns of measurements, e.g. in the heart rate, blood pressure and temperature.
We demonstrate how to exploit knowledge of the structure of how the various latent factors interact so as to reduce the amount of training data needed for the system. A combination of domain knowledge engineering and learning is used to produce an effective solution. We use the model to infer the presence of two different types of factors: common, recognisable regimes (e.g. certain artifacts or common physiological phenomena), and novel patterns which are clinically significant but have unknown cause. Experimental results are given showing the potential of the system for the early detection of neonatal sepsis, a major clinical concern in the care of premature babies.
Chris Williams. Joint work with Yvonne Freer, Neil McIntosh, John Quinn, Ioan Stanculescu.
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