Campuses:

Stationary processes

Tuesday, October 6, 2009 - 10:45am - 11:15am
Donald Geman (Johns Hopkins University)
Keywords: object
detection, invariant features, hierarchical search


Abstract:
This talk is about research in scene interpretation. Most algorithms
for detecting and describing instances from object categories consist
of looping over a partition of a pose space with dedicated binary
classifiers. This strategy is inefficient for a complex pose:
fragmenting the training data severely reduces accuracy, and the
computational cost is prohibitive due to visiting a massive pose
Thursday, November 29, 2012 - 2:00pm - 3:00pm
Hillel Furstenberg (Hebrew University)
Let G be a group and m a probability measure on G. One can speak of a stationary (rather than invariant) density on G, and for an action of G on a compact space X one can talk of a stationary (rather than invariant)
measure on X. One can also establish a correspondence principle in this setting, and also prove multiple recurrence for stationary actions. These ideas lead to a general Szemeredi-type theorem, which is quite explicit for finitely generated free groups as well as for certain infinite regular graphs.
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