Monday, November 19, 2007

NIPS 08 proceeding available

Here are some interesting paper I'm planning to read or browse.
My biggest concern is how effective is the work. It seems currently most are beautiful with formulas, but can not even beat the simplest method.

It's always human who make the world so complicated.
My belief is "The World is Simple!"


Heterogeneous Component Analysis
Shigeyuki Oba, Motoaki Kawanabe, Klaus-Robert Müller, Shin Ishii

Neural characterization in partially observed populations of spiking neurons
Jonathan Pillow, Peter Latham

Probabilistic Matrix Factorization
Ruslan Salakhutdinov, Andriy Mnih

Hidden Common Cause Relations in Relational Learning
Ricardo Silva, Wei Chu, Zoubin Ghahramani

Hierarchical Penalization
Marie Szafranski, Yves Grandvalet, Pierre Morizet-Mahoudeaux

Learning with Transformation Invariant Kernels
Christian Walder

A Spectral Regularization Framework for Multi-Task Structure Learning
Andreas Argyriou, Charles A. Micchelli, Massimiliano Pontil, Yiming Ying


Supervised Topic Models
David Blei, Jon McAuliffe

Learning Bounds for Domain Adaptation
John Blitzer, Koby Crammer, Alex Kulesza, Fernando Pereira, Jennifer Wortman

Multi-task Gaussian Process Prediction
Edwin Bonilla, Kian Ming Chai, Chris Williams

Automatic Generation of Social Tags for Music Recommendation
Douglas Eck, Paul Lamere, Thierry Bertin-Mahieux, Stephen Green

Kernel Measures of Conditional Dependence
Kenji Fukumizu, Arthur Gretton, Xiaohai Sun, Bernhard Sch??lkopf

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