[seminarios-mlpb] Reminder: seminar talk next Tuesday, Nov. 25

  • From: Miguel Almeida <miguel.almeida@xxxxxxxxxxx>
  • To: "seminarios-mlpb@xxxxxxxxxxxxx" <seminarios-mlpb@xxxxxxxxxxxxx>
  • Date: Fri, 21 Nov 2014 16:26:42 +0000

Hello all,

Here is the announcement for our seminar next Tuesday, by Renato Negrinho from 
IT. See you there!

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TALK ANNOUNCEMENT  --  Anfiteatro do Complexo Interdisciplinar
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Priberam Machine Learning Lunch Seminar
Speaker: Renato Negrinho (IT)
Venue: IST Alameda, Anfiteatro do Complexo Interdisciplinar
Date: Tuesday, November 25th, 2014
Time: 13:00
Lunch will be provided


Title:
Orbit Regularization

Abstract:
We propose a general framework for regularization based on group-induced 
majorization. In this framework, a group is defined to act on the parameter 
space and an orbit is fixed; to control complexity, the model parameters are 
confined to the convex hull of this orbit (the orbitope). We recover several 
well-known regularizers as particular cases, and reveal a connection between 
the hyperoctahedral group and the recently proposed sorted l1-norm. We derive 
the properties a group must satisfy for being amenable to optimization with 
conditional and projected gradient algorithms. Finally, we suggest a 
continuation strategy for orbit exploration, presenting simulation results for 
the symmetric and hyperoctahedral groups.

Bio:
Renato Negrinho received a M.Sc degree in Electrical and Computer Engineering 
from Instituto Superior Técnico, Portugal, in 2013. He currently holds a 
research scholarship and is working on natural language processing and machine 
learning problems under the supervision of André Martins at Priberam. He is 
interested in machine learning, optimization and the application of mathematics 
in general to solve difficult problems in science.

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General info about our seminars:  
http://labs.priberam.com/Academia-Partnerships/Seminars.aspx
Please forward this link to whoever might be interested in attending the 
seminars.

Miguel Almeida

Research Scientist

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Email: mba@xxxxxxxxxxx<mailto:mba@xxxxxxxxxxx>
URL: http://labs.priberam.com


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