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» Learning Complex Population-Coded Sequences
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JAIR
2002
134views more  JAIR 2002»
13 years 8 months ago
Specific-to-General Learning for Temporal Events with Application to Learning Event Definitions from Video
We develop, analyze, and evaluate a novel, supervised, specific-to-general learner for a simple temporal logic and use the resulting algorithm to learn visual event definitions fr...
Alan Fern, Robert Givan, Jeffrey Mark Siskind
AAIP
2009
13 years 10 months ago
Incremental Learning in Inductive Programming
Inductive programming systems characteristically exhibit an exponential explosion in search time as one increases the size of the programs to be generated. As a way of overcoming ...
Robert Henderson
ICML
2004
IEEE
14 years 10 months ago
Dynamic conditional random fields: factorized probabilistic models for labeling and segmenting sequence data
In sequence modeling, we often wish to represent complex interaction between labels, such as when performing multiple, cascaded labeling tasks on the same sequence, or when longra...
Charles A. Sutton, Khashayar Rohanimanesh, Andrew ...
ICML
2009
IEEE
14 years 3 months ago
Sparse higher order conditional random fields for improved sequence labeling
In real sequence labeling tasks, statistics of many higher order features are not sufficient due to the training data sparseness, very few of them are useful. We describe Sparse H...
Xian Qian, Xiaoqian Jiang, Qi Zhang, Xuanjing Huan...
NAACL
2010
13 years 7 months ago
Distributed Training Strategies for the Structured Perceptron
Perceptron training is widely applied in the natural language processing community for learning complex structured models. Like all structured prediction learning frameworks, the ...
Ryan T. McDonald, Keith Hall, Gideon Mann