sign up for your presentation: Difference between revisions
Jump to navigation
Jump to search
No edit summary |
(→Set B) |
||
Line 49: | Line 49: | ||
|Lisha Yu|| Maximum‐margin matrix factorization[http://ttic.uchicago.edu/~nati/Publications/MMMFnips04.pdf] | |Lisha Yu|| Maximum‐margin matrix factorization[http://ttic.uchicago.edu/~nati/Publications/MMMFnips04.pdf] | ||
|- | |- | ||
|Ryan Case|| Probabilistic non-linear principal component analysis with Gaussian process latent variable models [http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.66.8581&rep=rep1&type=pdf] | |Ryan Case|| Probabilistic non-linear principal component analysis with Gaussian process latent variable models [http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.66.8581&rep=rep1&type=pdf] [[Probabilistic_PCA_with_GPLVM | Summary]] | ||
|- | |- | ||
|- | |- |
Revision as of 00:20, 28 November 2010
Sign up for your presentation in the following table. Put your name and a link to the paper that you are going to present. Chose a date between Nov 16 and Dec 2 (inclusive).
Set A
Date | Presentation (1) | Presentation (2) |
Nov 16 | Sepideh Seifzadeh [1] Summary | Manda Winlaw [2], Summary |
Nov 18 | Rahul [3] Summary | Fatemeh Dorri [4],Summary |
Nov 23 | Pouria Fewzee | Lisha Yu[5]Summary |
Nov 25 | Laleh Ghoraie [6] Summary | Mehrdad Gangeh [7]Summary |
Nov 30 | Greg D'Cunha [8] Summary | Mohammad Derakhshani [9], |
Dec 2 | Yongpeng Sun [10] Summary | Ryan Case [11] Summary |
Set B
Name | Second paper (The paper that you are going to write a critic on it. This is different from the paper that you have chosen for presentation.) |
Greg D'Cunha | Probabilistic matrix factorization [12] Summary |
Fatemeh Dorri | Optimal Solutions forSparse Principal Component Analysis[13] |
Lisha Yu | Maximum‐margin matrix factorization[14] |
Ryan Case | Probabilistic non-linear principal component analysis with Gaussian process latent variable models [15] Summary |
Yongpeng Sun | Multi‐Task Feature Learning [16] |
Manda Winlaw | Consistency of trace norm minimization [17] |