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SIAMCO
2000
117views more  SIAMCO 2000»
13 years 9 months ago
The O.D.E. Method for Convergence of Stochastic Approximation and Reinforcement Learning
It is shown here that stability of the stochastic approximation algorithm is implied by the asymptotic stability of the origin for an associated ODE. This in turn implies convergen...
Vivek S. Borkar, Sean P. Meyn
ICRA
2009
IEEE
188views Robotics» more  ICRA 2009»
13 years 7 months ago
Onboard contextual classification of 3-D point clouds with learned high-order Markov Random Fields
Contextual reasoning through graphical models such as Markov Random Fields often show superior performance against local classifiers in many domains. Unfortunately, this performanc...
Daniel Munoz, Nicolas Vandapel, Martial Hebert
TCS
2011
13 years 4 months ago
Two faces of active learning
An active learner has a collection of data points, each with a label that is initially hidden but can be obtained at some cost. Without spending too much, it wishes to find a cla...
Sanjoy Dasgupta
ACL
2011
13 years 1 months ago
Learning Dependency-Based Compositional Semantics
Compositional question answering begins by mapping questions to logical forms, but training a semantic parser to perform this mapping typically requires the costly annotation of t...
Percy Liang, Michael I. Jordan, Dan Klein
ICANN
2011
Springer
13 years 1 months ago
Learning from Multiple Annotators with Gaussian Processes
Abstract. In many supervised learning tasks it can be costly or infeasible to obtain objective, reliable labels. We may, however, be able to obtain a large number of subjective, po...
Perry Groot, Adriana Birlutiu, Tom Heskes