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 Events
Wed 29 Nov 2017, 2:45pm SPECIAL
ESB 4133 (PIMS Lounge)
Nov. 29th PIMS Afternoon Tea has been moved to 4:30pm-5:00pm
ESB 4133 (PIMS Lounge)
Wed 29 Nov 2017, 2:45pm-3:15pm

Details

The last PIMS Afternoon Tea of the fall semester will take place before Marco Cuturi's 5:00 pm PIMS Distinguished Colloquium.
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Université Paris-Saclay
Thu 30 Nov 2017, 5:00pm SPECIAL
ESB 2012
UBC Mathematics Lecture Series:: Regularized Optimal Transport. Part I.
ESB 2012
Thu 30 Nov 2017, 5:00pm-6:30pm

Details

 Optimal transport theory provides practitioners from statistics, imaging, graphics or machine learning with a very powerful toolbox to compare probability measures. These tools translate however in their original form into computational schemes that can become intractable or suffer from instability (such as non-differentiability or estimation bias). We will present in these two lectures how a few insights from optimization theory and in particular a careful regularization can result in tools that are considerably easier to implement, run faster because they can take advantage of parallel hardware and behave better from a statistical perspective. We will highlight applications from diverse areas, from graphics and brain imaging to text analysis and parametric estimation.

Note for Attendees

 This is the first of a two part lecture. The second part will be given on Dec, 1 2017, in ESB 2012 at the same time. Details for Part II are available here
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Université Paris-Saclay
Fri 1 Dec 2017, 5:00pm SPECIAL
ESB 2012
UBC Mathematics Lecture Series: Regularized Optimal Transport. Part II
ESB 2012
Fri 1 Dec 2017, 5:00pm-6:30pm

Details

 Optimal transport theory provides practitioners from statistics, imaging, graphics or machine learning with a very powerful toolbox to compare probability measures. These tools translate however in their original form into computational schemes that can become intractable or suffer from instability (such as non-differentiability or estimation bias). We will present in these two lectures how a few insights from optimization theory and in particular a careful regularization can result in tools that are considerably easier to implement, run faster because they can take advantage of parallel hardware and behave better from a statistical perspective. We will highlight applications from diverse areas, from graphics and brain imaging to text analysis and parametric estimation.

Note for Attendees

 This is the second of a two part lecture. The first part will be given on Nov 30 2017, in ESB 2012 at the same time. Details for Part I are available here.
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Harvard
Thu 25 Jan 2018, 4:00pm SPECIAL
TBA
TBA
TBA
Thu 25 Jan 2018, 4:00pm-5:00pm

Details


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