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108
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ESANN
2003
15 years 1 months ago
Approximation of Function by Adaptively Growing Radial Basis Function Neural Networks
In this paper a neural network for approximating function is described. The activation functions of the hidden nodes are the Radial Basis Functions (RBF) whose parameters are learn...
Jianyu Li, Siwei Luo, Yingjian Qi
UAI
2001
15 years 1 months ago
Vector-space Analysis of Belief-state Approximation for POMDPs
We propose a new approach to value-directed belief state approximationfor POMDPs. The valuedirected model allows one to choose approximation methods for belief state monitoringtha...
Pascal Poupart, Craig Boutilier
82
Voted
ICML
2009
IEEE
16 years 1 months ago
On sampling-based approximate spectral decomposition
This paper addresses the problem of approximate singular value decomposition of large dense matrices that arises naturally in many machine learning applications. We discuss two re...
Sanjiv Kumar, Mehryar Mohri, Ameet Talwalkar
179
Voted
VLDB
2002
ACM
113views Database» more  VLDB 2002»
16 years 24 days ago
Searching in metric spaces by spatial approximation
We propose a new data structure to search in metric spaces. A metric space is formed by a collection of objects and a distance function de ned among them, which satis es the trian...
Gonzalo Navarro
109
Voted
ISAAC
2009
Springer
140views Algorithms» more  ISAAC 2009»
15 years 7 months ago
Tighter Approximation Bounds for Minimum CDS in Wireless Ad Hoc Networks
Abstract. Connected dominating set (CDS) has a wide range of applications in wireless ad hoc networks. A number of approximation algorithms for constructing a small CDS in wireless...
Minming Li, Peng-Jun Wan, F. Frances Yao