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» Flexible latent variable models for multi-task learning
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CIKM
2011
Springer
13 years 9 months ago
Toward interactive training and evaluation
Machine learning often relies on costly labeled data, and this impedes its application to new classification and information extraction problems. This has motivated the developme...
Gregory Druck, Andrew McCallum
ICA
2007
Springer
15 years 1 months ago
Conjugate Gamma Markov Random Fields for Modelling Nonstationary Sources
In modelling nonstationary sources, one possible strategy is to define a latent process of strictly positive variables to model variations in second order statistics of the underly...
Ali Taylan Cemgil, Onur Dikmen
NAACL
2010
14 years 7 months ago
Context-free reordering, finite-state translation
We describe a class of translation model in which a set of input variants encoded as a context-free forest is translated using a finitestate translation model. The forest structur...
Christopher Dyer, Philip Resnik
ICPR
2010
IEEE
14 years 8 months ago
Learning Non-Linear Dynamical Systems by Alignment of Local Linear Models
Abstract—Learning dynamical systems is one of the important problems in many fields. In this paper, we present an algorithm for learning non-linear dynamical systems which works...
Masao Joko, Yoshinobu Kawahara, Takehisa Yairi
AAAI
2012
12 years 12 months ago
A Sequential Decision Approach to Ordinal Preferences in Recommender Systems
We propose a novel sequential decision approach to modeling ordinal ratings in collaborative filtering problems. The rating process is assumed to start from the lowest level, eva...
Truyen Tran, Dinh Q. Phung, Svetha Venkatesh