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AAAI
2008
15 years 4 months ago
Active Learning for Pipeline Models
For many machine learning solutions to complex applications, there are significant performance advantages to decomposing the overall task into several simpler sequential stages, c...
Dan Roth, Kevin Small
NIPS
2008
15 years 3 months ago
Posterior Consistency of the Silverman g-prior in Bayesian Model Choice
Kernel supervised learning methods can be unified by utilizing the tools from regularization theory. The duality between regularization and prior leads to interpreting regularizat...
Zhihua Zhang, Michael I. Jordan, Dit-Yan Yeung
ACL
2010
14 years 11 months ago
Open-Domain Semantic Role Labeling by Modeling Word Spans
Most supervised language processing systems show a significant drop-off in performance when they are tested on text that comes from a domain significantly different from the domai...
Fei Huang, Alexander Yates
ICMLA
2009
14 years 11 months ago
Automatic Feature Selection for Model-Based Reinforcement Learning in Factored MDPs
Abstract--Feature selection is an important challenge in machine learning. Unfortunately, most methods for automating feature selection are designed for supervised learning tasks a...
Mark Kroon, Shimon Whiteson
ICONIP
2009
14 years 11 months ago
Learning Gaussian Process Models from Uncertain Data
It is generally assumed in the traditional formulation of supervised learning that only the outputs data are uncertain. However, this assumption might be too strong for some learni...
Patrick Dallaire, Camille Besse, Brahim Chaib-draa