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JMLR
2010
154views more  JMLR 2010»
15 years 1 months ago
Infinite Predictor Subspace Models for Multitask Learning
Given several related learning tasks, we propose a nonparametric Bayesian model that captures task relatedness by assuming that the task parameters (i.e., predictors) share a late...
Piyush Rai, Hal Daumé III
FTCGV
2011
122views more  FTCGV 2011»
14 years 10 months ago
Structured Learning and Prediction in Computer Vision
Powerful statistical models that can be learned efficiently from large amounts of data are currently revolutionizing computer vision. These models possess a rich internal structur...
Sebastian Nowozin, Christoph H. Lampert
ICCV
2011
IEEE
14 years 6 months ago
Human Action Recognition by Learning Bases of Action Attributes and Parts
In this work, we propose to use attributes and parts for recognizing human actions in still images. We define action attributes as the verbs that describe the properties of human...
Bangpeng Yao, Xiaoye Jiang, Aditya Khosla, Andy La...
AAAI
2011
14 years 6 months ago
Coarse-to-Fine Inference and Learning for First-Order Probabilistic Models
Coarse-to-fine approaches use sequences of increasingly fine approximations to control the complexity of inference and learning. These techniques are often used in NLP and visio...
Chloe Kiddon, Pedro Domingos
CVPR
2007
IEEE
16 years 8 months ago
Learning Object Material Categories via Pairwise Discriminant Analysis
In this paper, we investigate linear discriminant analysis (LDA) methods for multiclass classification problems in hyperspectral imaging. We note that LDA does not consider pairwi...
Zhouyu Fu, Antonio Robles-Kelly