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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
CMSB
2009
Springer
16 years 25 days 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 25 days 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