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» Machine Learning by Function Decomposition
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ICML
2000
IEEE
16 years 20 days ago
Rates of Convergence for Variable Resolution Schemes in Optimal Control
This paper presents a general method to derive tight rates of convergence for numerical approximations in optimal control when we consider variable resolution grids. We study the ...
Andrew W. Moore, Rémi Munos
ICML
2009
IEEE
16 years 20 days ago
Bandit-based optimization on graphs with application to library performance tuning
The problem of choosing fast implementations for a class of recursive algorithms such as the fast Fourier transforms can be formulated as an optimization problem over the language...
Arpad Rimmel, Frédéric de Mesmay, Ma...
ICML
2009
IEEE
16 years 20 days ago
Tractable nonparametric Bayesian inference in Poisson processes with Gaussian process intensities
The inhomogeneous Poisson process is a point process that has varying intensity across its domain (usually time or space). For nonparametric Bayesian modeling, the Gaussian proces...
Ryan Prescott Adams, Iain Murray, David J. C. MacK...
ICML
2007
IEEE
16 years 20 days ago
A novel orthogonal NMF-based belief compression for POMDPs
High dimensionality of POMDP's belief state space is one major cause that makes the underlying optimal policy computation intractable. Belief compression refers to the method...
Xin Li, William Kwok-Wai Cheung, Jiming Liu, Zhili...
ICML
2007
IEEE
16 years 20 days ago
Asymmetric boosting
A cost-sensitive extension of boosting, denoted as asymmetric boosting, is presented. Unlike previous proposals, the new algorithm is derived from sound decision-theoretic princip...
Hamed Masnadi-Shirazi, Nuno Vasconcelos