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KDD
2005
ACM
153views Data Mining» more  KDD 2005»
14 years 10 months ago
Improving discriminative sequential learning with rare--but--important associations
Discriminative sequential learning models like Conditional Random Fields (CRFs) have achieved significant success in several areas such as natural language processing, information...
Xuan Hieu Phan, Minh Le Nguyen, Tu Bao Ho, Susumu ...
JAIR
2010
131views more  JAIR 2010»
13 years 8 months ago
Automatic Induction of Bellman-Error Features for Probabilistic Planning
Domain-specific features are important in representing problem structure throughout machine learning and decision-theoretic planning. In planning, once state features are provide...
Jia-Hong Wu, Robert Givan
CLOR
2006
14 years 1 months ago
Sequential Learning of Layered Models from Video
Abstract. A popular framework for the interpretation of image sequences is the layers or sprite model, see e.g. [1], [2]. Jojic and Frey [3] provide a generative probabilistic mode...
Michalis K. Titsias, Christopher K. I. Williams
LREC
2008
104views Education» more  LREC 2008»
13 years 11 months ago
Definition Extraction Using a Sequential Combination of Baseline Grammars and Machine Learning Classifiers
The paper deals with the task of definition extraction from a small and noisy corpus of instructive texts. Three approaches are presented: Partial Parsing, Machine Learning and a ...
Lukasz Degórski, Michal Marcinczuk, Adam Pr...
AIIA
2007
Springer
13 years 11 months ago
Tonal Harmony Analysis: A Supervised Sequential Learning Approach
We have recently presented CarpeDiem, an algorithm that can be used for speeding up the evaluation of Supervised Sequential Learning (SSL) classifiers. CarpeDiem provides impress...
Daniele P. Radicioni, Roberto Esposito