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» Approximation Methods for Supervised Learning
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113
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COLING
2010
14 years 7 months ago
Improved Discriminative ITG Alignment using Hierarchical Phrase Pairs and Semi-supervised Training
While ITG has many desirable properties for word alignment, it still suffers from the limitation of one-to-one matching. While existing approaches relax this limitation using phra...
Shujie Liu, Chi-Ho Li, Ming Zhou
97
Voted
ILP
2001
Springer
15 years 5 months ago
Learning Functions from Imperfect Positive Data
The Bayesian framework of learning from positive noise-free examples derived by Muggleton [12] is extended to learning functional hypotheses from positive examples containing norma...
Filip Zelezný
104
Voted
ICANN
2009
Springer
15 years 4 months ago
Efficient Uncertainty Propagation for Reinforcement Learning with Limited Data
In a typical reinforcement learning (RL) setting details of the environment are not given explicitly but have to be estimated from observations. Most RL approaches only optimize th...
Alexander Hans, Steffen Udluft
86
Voted
ICCV
1999
IEEE
16 years 2 months ago
Higher Order Statistical Learning for Vehicle Detection in Images
The paper describes a scheme for detecting vehicles in images. The proposed method approximately models the unknown distribution of the images of vehicles by learning higher order...
A. N. Rajagopalan, Philippe Burlina, Rama Chellapp...
195
Voted
BDA
2007
15 years 2 months ago
Hyperplane Queries in a Feature-Space M-tree for Speeding up Active Learning
In content-based retrieval, relevance feedback (RF) is a noticeable method for reducing the “semantic gap” between the low-level features describing the content and the usually...
Michel Crucianu, Daniel Estevez, Vincent Oria, Jea...