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PRL
2011
15 years 1 months ago
Efficient approximate Regularized Least Squares by Toeplitz matrix
Machine Learning based on the Regularized Least Square (RLS) model requires one to solve a system of linear equations. Direct-solution methods exhibit predictable complexity and s...
Sergio Decherchi, Paolo Gastaldo, Rodolfo Zunino
AUTOMATICA
2011
14 years 10 months ago
A hierarchy of LMI inner approximations of the set of stable polynomials
Exploiting spectral properties of symmetric banded Toeplitz matrices, we describe simple sufficient conditions for positivity of a trigonometric polynomial formulated as linear ma...
Mustapha Ait Rami, Didier Henrion
ICML
2007
IEEE
16 years 7 months ago
Constructing basis functions from directed graphs for value function approximation
Basis functions derived from an undirected graph connecting nearby samples from a Markov decision process (MDP) have proven useful for approximating value functions. The success o...
Jeffrey Johns, Sridhar Mahadevan
186
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CMSB
2009
Springer
16 years 1 months ago
Probabilistic Approximations of Signaling Pathway Dynamics
Systems of ordinary differential equations (ODEs) are often used to model the dynamics of complex biological pathways. We construct a discrete state model as a probabilistic appro...
Bing Liu, P. S. Thiagarajan, David Hsu
ICAPR
2009
Springer
16 years 1 months ago
Hierarchical Local Maps for Robust Approximate Nearest Neighbor Computation
In this paper, we propose a novel method for fast nearest neighbors retrieval in non-Euclidean and non-metric spaces. We organize the data into a hierarchical fashion that preserv...
Pratyush Bhatt, Anoop M. Namboodiri