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[nl-uiuc] Reminder: NathaSrebro talk **now*** (4pm) in 3405


Chronological Thread 
  • From: "Hockenmaier, Julia Constanze" <juliahmr AT cs.uiuc.edu>
  • To: "Klementiev, Alexandre" <klementi AT uiuc.edu>, "nl-uiuc AT cs.uiuc.edu" <nl-uiuc AT cs.uiuc.edu>, "aivr AT cs.uiuc.edu" <aivr AT cs.uiuc.edu>, "dais AT cs.uiuc.edu" <dais AT cs.uiuc.edu>, "cogcomp AT cs.uiuc.edu" <cogcomp AT cs.uiuc.edu>, "vision AT cs.uiuc.edu" <vision AT cs.uiuc.edu>, "krr-group AT cs.uiuc.edu" <krr-group AT cs.uiuc.edu>, "group AT vision2.ai.uiuc.edu" <group AT vision2.ai.uiuc.edu>
  • Subject: [nl-uiuc] Reminder: NathaSrebro talk **now*** (4pm) in 3405
  • Date: Thu, 11 Sep 2008 15:55:16 -0500
  • Accept-language: en-US
  • Acceptlanguage: en-US
  • List-archive: <http://lists.cs.uiuc.edu/pipermail/nl-uiuc>
  • List-id: Natural language research announcements <nl-uiuc.cs.uiuc.edu>


> Dear faculty and students,
>
> We are re-starting our AIIS seminar <http://nlp.cs.uiuc.edu/seminar/> this
> semester with a talk by Nathan Srebro (details below) next Thursday.
>
> Hope to see you there,
> Alex.
>
> Title: More Data Less Work: SVM Training in Time Decreasing with Larger Data
> Sets
> Speaker: Nathan Srebro, TTI Chicago
>
> Date: September 11, 4:00pm
> Location: Siebel 3405
>
> Abstract:
>
> Traditional runtime analysis of training Support Vector Machines, and indeed
> most learning methods, shows how the training runtime increases as more
> training examples are available. Considering the true objective of training,
> which is to obtain a good predictor, I will argue that training time should
> be
> studied as a decreasing function of training set size. I will then present
> both theoretical and empirical results demonstrating how a simple stochastic
> subgradient descent approach for training SVMs indeed displays such
> monotonic
> decreasing behavior.
>
> I will also discuss a similar phenomena in the context of Gaussian mixture
> clustering, where it appears that excess data turns the problem from
> computationally intractable to computationally tractable.
>
> Joint work with Shai Shalev-Shwartz, Yoram Singer, Greg Shakhnarovich and
> Sam
> Roweis.
>
>






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