[Posgrados-invop] ATENCION - cambio de fecha Fwd: Re: [Novedades_inco] Fwd: Charla sobre Clustering - M. Tepper - martes 21/11-16hs (CAMBIO DE FECHA)

[Héctor Cancela]

-------- Mensaje reenviado --------
Asunto: 	Re: [Novedades_inco] Fwd: Charla sobre Clustering - M. Tepper - 
martes 21/11-16hs (CAMBIO DE FECHA)
Fecha: 	Mon, 13 Nov 2017 11:45:45 -0300
De: 	Lorena Etcheverry <lorenae at fing.edu.uy>
Para: 	novedades_inco at fing.edu.uy



ATENCIÓN: La charla se mueve para el lunes 20/11 para evitar una
colisión con los festejos de los primeros 50 años del INCO.

"Clustering is semidefinitely not that hard",  lunes 20/11 a las 16hs.
Sala de seminarios del Instituto de Física (7mo piso FING)

Favor reenviar (nuevamente).

m-


On 11/13/17 10:35, Lorena Etcheverry wrote:
>
> Estimados
>
> reenvio información de charla.
>
> saludos!
>
> Lorena
>
>
>
> -------- Forwarded Message --------
> Subject: 	Charla sobre Clustering - M. Tepper - martes 21/11-16hs
> Date: 	Mon, 13 Nov 2017 10:04:37 -0300
> From: 	Mauricio Delbracio <mdelbra at gmail.com>
> To: 	todos iie <todos_iie at fing.edu.uy>, Marcelo Fiori - IIE - IMERL 
> <mfiori at fing.edu.uy>, Santiago Castro - InCo <sacastro at fing.edu.uy>, 
> Hector Cancela - INCO <cancela at fing.edu.uy>, Matias Di Martino 
> <matiasdm at fing.edu.uy>, Diego Armentano <diego at cmat.edu.uy>, Guillermo 
> Moncecchi <gmonce at fing.edu.uy>, Paola Bermolen <paola at fing.edu.uy>, 
> lorena etcheverry <lorenae at fing.edu.uy>
>
>
>
> Tenemos el agrado de tener de visita a Mariano Tepper, investigador
> del grupo de neurociencia del Flatiron Institute (Simons Foundation) y
> amigo de la casa.
>
> Mariano dará una charla sobre su trabajo actual, que muchos de ustedes
> (espero) encontrarán de interés.
>
> "Clustering is semidefinitely not that hard",  martes 21/11 a las 16hs.
> Sala de seminarios del Instituto de Física (7mo piso FING)
>
> Abajo +información. Favor reenviar a interesados.
>
> saludos,
> mauricio
>
> ---
>
> Title:
> Clustering is semidefinitely not that hard
>
> Abstract:
> In recent years, semidefinite programs (SDP) have been the subject of
> interesting research in the field of clustering. In many cases, these
> convex programs deliver the same answers as non-convex alternatives
> and come with a guarantee of optimality. In this talk, I will argue
> that SDP-KM, a popular semidefinite relaxation of K-means, can learn
> manifolds present in the data, something not possible with the
> original K-means formulation. To build an intuitive understanding of
> SDP-KM's manifold learning capabilities, I will present a theoretical
> analysis on an idealized dataset. Additionally, SDP-KM even segregates
> linearly non-separable manifolds. As generic SDP solvers are slow on
> large datasets, I will also discuss the suitability of efficient
> algorithms to SDP-KM. These features render SDP-KM a versatile and
> interesting tool for manifold learning while remaining amenable to
> theoretical analysis.
>
> Bio:
> Mariano Tepper is currently a member of the neuroscience group at the
> Center for Computational Biology, Flatiron Institute. His research
> focuses on image processing, computer vision, pattern recognition, and
> machine learning. Previously, he was a research scientist at Duke
> University. Prior to working at Duke, he was postdoctoral research
> associate at the University of Minnesota. Tepper holds a Ph.D. and
> licentiate degree in computer science from the Universidad de Buenos
> Aires in Argentina and an M.S. in applied mathematics from the École
> Normale Supérieure de Cachan in France.

-- 
Dr. Ing. Lorena Etcheverry
Profesor Adjunto
Instituto de Computación
Facultad de Ingeniería, Universidad de la República
J. Herrera y Reissig 565
Montevideo 11300, Uruguay

tel  :: (+ 598) 2711 4244  ext. 1148



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