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» Computationally Efficient Transductive Machines
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ICMLA
2009
13 years 5 months ago
Automatic Feature Selection for Model-Based Reinforcement Learning in Factored MDPs
Abstract--Feature selection is an important challenge in machine learning. Unfortunately, most methods for automating feature selection are designed for supervised learning tasks a...
Mark Kroon, Shimon Whiteson
CVPR
2010
IEEE
13 years 5 months ago
Growing semantically meaningful models for visual SLAM
Though modern Visual Simultaneous Localisation and Mapping (vSLAM) systems are capable of localising robustly and efficiently even in the case of a monocular camera, the maps prod...
Alexander Flint, Christopher Mei, Ian D. Reid, Dav...
BMCBI
2010
165views more  BMCBI 2010»
13 years 8 months ago
MTar: a computational microRNA target prediction architecture for human transcriptome
Background: MicroRNAs (miRNAs) play an essential task in gene regulatory networks by inhibiting the expression of target mRNAs. As their mRNA targets are genes involved in importa...
Vinod Chandra, Reshmi Girijadevi, Achuthsankar S. ...
ICML
2008
IEEE
14 years 8 months ago
An asymptotic analysis of generative, discriminative, and pseudolikelihood estimators
Statistical and computational concerns have motivated parameter estimators based on various forms of likelihood, e.g., joint, conditional, and pseudolikelihood. In this paper, we ...
Percy Liang, Michael I. Jordan
ICML
2001
IEEE
14 years 8 months ago
Multiple Instance Regression
This paper introduces multiple instance regression, a variant of multiple regression in which each data point may be described by more than one vector of values for the independen...
Soumya Ray, David Page