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ICML
2008
IEEE
16 years 1 months ago
Reinforcement learning with limited reinforcement: using Bayes risk for active learning in POMDPs
Partially Observable Markov Decision Processes (POMDPs) have succeeded in planning domains that require balancing actions that increase an agent's knowledge and actions that ...
Finale Doshi, Joelle Pineau, Nicholas Roy
ICCS
2005
Springer
15 years 6 months ago
On the Need to Bootstrap Ontology Learning with Extraction Grammar Learning
The main claim of this paper is that machine learning can help integrate the construction of ontologies and extraction grammars and lead us closer to the Semantic Web vision. The p...
Georgios Paliouras
108
Voted
EMNLP
2004
15 years 1 months ago
Learning Hebrew Roots: Machine Learning with Linguistic Constraints
The morphology of Semitic languages is unique in the sense that the major word-formation mechanism is an inherently non-concatenative process of interdigitation, whereby two morph...
Ezra Daya, Dan Roth, Shuly Wintner
99
Voted
ALT
2009
Springer
15 years 9 months ago
Learning from Streams
Abstract. Learning from streams is a process in which a group of learners separately obtain information about the target to be learned, but they can communicate with each other in ...
Sanjay Jain, Frank Stephan, Nan Ye
CORR
2010
Springer
96views Education» more  CORR 2010»
15 years 17 days ago
Learning High-Dimensional Markov Forest Distributions: Analysis of Error Rates
The problem of learning forest-structured discrete graphical models from i.i.d. samples is considered. An algorithm based on pruning of the Chow-Liu tree through adaptive threshol...
Vincent Y. F. Tan, Animashree Anandkumar, Alan S. ...