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» Missing Data Estimation Using Polynomial Kernels
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ICPP
2009
IEEE
15 years 7 months ago
Generalizing k-Betweenness Centrality Using Short Paths and a Parallel Multithreaded Implementation
We present a new parallel algorithm that extends and generalizes the traditional graph analysis metric of betweenness centrality to include additional non-shortest paths according...
Karl Jiang, David Ediger, David A. Bader
101
Voted
ICML
2006
IEEE
16 years 1 months ago
Kernel Predictive Linear Gaussian models for nonlinear stochastic dynamical systems
The recent Predictive Linear Gaussian model (or PLG) improves upon traditional linear dynamical system models by using a predictive representation of state, which makes consistent...
David Wingate, Satinder P. Singh
ICANN
2001
Springer
15 years 5 months ago
Incremental Support Vector Machine Learning: A Local Approach
Abstract. In this paper, we propose and study a new on-line algorithm for learning a SVM based on Radial Basis Function Kernel: Local Incremental Learning of SVM or LISVM. Our meth...
Liva Ralaivola, Florence d'Alché-Buc
118
Voted
AMW
2010
15 years 2 months ago
Multiresolution Cube Estimators for Sensor Network Aggregate Queries
In this work we present in-network techniques to improve the efficiency of spatial aggregate queries. Such queries are very common in a sensornet setting, demanding more targeted t...
Alexandra Meliou, Carlos Guestrin, Joseph M. Helle...
TIP
2008
113views more  TIP 2008»
15 years 13 days ago
Phase Local Approximation (PhaseLa) Technique for Phase Unwrap From Noisy Data
The local polynomial approximation (LPA) is a nonparametric regression technique with pointwise estimation in a sliding window. We apply the LPA of the argument of cos and sin in o...
Vladimir Katkovnik, Jaakko Astola, Karen O. Egiaza...