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» A Framework for Machine Learning with Ambiguous Objects
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ICML
2005
IEEE
14 years 8 months ago
Dynamic preferences in multi-criteria reinforcement learning
The current framework of reinforcement learning is based on maximizing the expected returns based on scalar rewards. But in many real world situations, tradeoffs must be made amon...
Sriraam Natarajan, Prasad Tadepalli
ICDM
2008
IEEE
136views Data Mining» more  ICDM 2008»
14 years 1 months ago
Generalized Framework for Syntax-Based Relation Mining
Supervised approaches to Data Mining are particularly appealing as they allow for the extraction of complex relations from data objects. In order to facilitate their application i...
Bonaventura Coppola, Alessandro Moschitti, Daniele...
PRL
2008
198views more  PRL 2008»
13 years 7 months ago
Pose estimation and tracking using multivariate regression
This paper presents an extension of the relevance vector machine (RVM) algorithm to multivariate regression. This allows the application to the task of estimating the pose of an a...
Arasanathan Thayananthan, Ramanan Navaratnam, Bj&o...
ECCV
2004
Springer
14 years 9 months ago
Reliable Fiducial Detection in Natural Scenes
Reliable detection of fiducial targets in real-world images is addressed in this paper. We show that even the best existing schemes are fragile when exposed to other than laborator...
David Claus, Andrew W. Fitzgibbon
CVPR
2008
IEEE
14 years 9 months ago
A hierarchical and contextual model for aerial image understanding
In this paper we present a novel method for parsing aerial images with a hierarchical and contextual model learned in a statistical framework. We learn hierarchies at the scene an...
Jake Porway, Kristy Wang, Benjamin Yao, Song Chun ...