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» Combining Learned Discrete and Continuous Action Models
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UAI
2004
15 years 5 months ago
Dynamical Systems Trees
We propose dynamical systems trees (DSTs) as a flexible model for describing multiple processes that interact via a hierarchy of aggregating processes. DSTs extend nonlinear dynam...
Andrew Howard, Tony Jebara
CCECE
2006
IEEE
15 years 10 months ago
A Dynamic Associative E-Learning Model based on a Spreading Activation Network
Presenting information to an e-learning environment is a challenge, mostly, because ofthe hypertextlhypermedia nature and the richness ofthe context and information provides. This...
Phongchai Nilas, Nilamit Nilas, Somsak Mitatha
ECAI
2010
Springer
15 years 2 months ago
Continuous Conditional Random Fields for Regression in Remote Sensing
Conditional random fields (CRF) are widely used for predicting output variables that have some internal structure. Most of the CRF research has been done on structured classificati...
Vladan Radosavljevic, Slobodan Vucetic, Zoran Obra...
ICML
2003
IEEE
16 years 5 months ago
Hierarchical Policy Gradient Algorithms
Hierarchical reinforcement learning is a general framework which attempts to accelerate policy learning in large domains. On the other hand, policy gradient reinforcement learning...
Mohammad Ghavamzadeh, Sridhar Mahadevan
MICAI
2010
Springer
15 years 2 months ago
Supervised Machine Learning for Predicting the Meaning of Verb-Noun Combinations in Spanish
The meaning of such verb-noun combinations as take care, undertake work, pay attention can be generalized as DO what is designated by the noun. Likewise, the meaning of make a deci...
Olga Kolesnikova, Alexander F. Gelbukh