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SDM
2011
SIAM
241views Data Mining» more  SDM 2011»
12 years 10 months ago
A Fast Algorithm for Sparse PCA and a New Sparsity Control Criteria
Sparse principal component analysis (PCA) imposes extra constraints or penalty terms to the standard PCA to achieve sparsity. In this paper, we first introduce an efficient algor...
Yunlong He, Renato Monteiro, Haesun Park
UAI
2008
13 years 8 months ago
Sparse Stochastic Finite-State Controllers for POMDPs
Bounded policy iteration is an approach to solving infinitehorizon POMDPs that represents policies as stochastic finitestate controllers and iteratively improves a controller by a...
Eric A. Hansen
ICASSP
2011
IEEE
12 years 11 months ago
Fast adaptive variational sparse Bayesian learning with automatic relevance determination
In this work a new adaptive fast variational sparse Bayesian learning (V-SBL) algorithm is proposed that is a variational counterpart of the fast marginal likelihood maximization ...
Dmitriy Shutin, Thomas Buchgraber, Sanjeev R. Kulk...
ATAL
2007
Springer
14 years 1 months ago
Sharing experiences to learn user characteristics in dynamic environments with sparse data
This paper investigates the problem of estimating the value of probabilistic parameters needed for decision making in environments in which an agent, operating within a multi-agen...
David Sarne, Barbara J. Grosz
ICRA
2010
IEEE
158views Robotics» more  ICRA 2010»
13 years 5 months ago
Real-time monocular SLAM: Why filter?
Abstract— While the most accurate solution to off-line structure from motion (SFM) problems is undoubtedly to extract as much correspondence information as possible and perform g...
Hauke Strasdat, J. M. M. Montiel, Andrew J. Daviso...