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ICML
2005
IEEE
16 years 2 months ago
Bayesian sparse sampling for on-line reward optimization
We present an efficient "sparse sampling" technique for approximating Bayes optimal decision making in reinforcement learning, addressing the well known exploration vers...
Tao Wang, Daniel J. Lizotte, Michael H. Bowling, D...
ACL
2012
13 years 4 months ago
Selective Sharing for Multilingual Dependency Parsing
We present a novel algorithm for multilingual dependency parsing that uses annotations from a diverse set of source languages to parse a new unannotated language. Our motivation i...
Tahira Naseem, Regina Barzilay, Amir Globerson
AAAI
2000
15 years 3 months ago
Information Extraction with HMM Structures Learned by Stochastic Optimization
Recent research has demonstrated the strong performance of hidden Markov models applied to information extraction--the task of populating database slots with corresponding phrases...
Dayne Freitag, Andrew McCallum
DAGM
2010
Springer
15 years 2 months ago
Learning of Optimal Illumination for Material Classification
We present a method to classify materials in illumination series data. An illumination series is acquired using a device which is capable to generate arbitrary lighting environment...
Markus Jehle, Christoph Sommer, Bernd Jähne
JMLR
2010
143views more  JMLR 2010»
15 years 12 days ago
A Quasi-Newton Approach to Nonsmooth Convex Optimization Problems in Machine Learning
We extend the well-known BFGS quasi-Newton method and its memory-limited variant LBFGS to the optimization of nonsmooth convex objectives. This is done in a rigorous fashion by ge...
Jin Yu, S. V. N. Vishwanathan, Simon Günter, ...