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KES
2006
Springer
13 years 9 months ago
Sensor Network Localization Using Least Squares Kernel Regression
Abstract. This paper considers the sensor network localization problem using signal strength. Unlike range-based methods signal strength information is stored in a kernel matrix. L...
Anthony Kuh, Chaopin Zhu, Danilo P. Mandic
NIPS
1998
13 years 11 months ago
Lazy Learning Meets the Recursive Least Squares Algorithm
Lazy learning is a memory-based technique that, once a query is received, extracts a prediction interpolating locally the neighboring examples of the query which are considered re...
Mauro Birattari, Gianluca Bontempi, Hugues Bersini
ICUMT
2009
13 years 7 months ago
sDLS - Distributed Least Squares localization for large Wireless Sensor Networks
Wireless Sensor Networks (WSNs) have been of high interest during the past couple of years. One of the most important aspect of WSN research is location estimation. As a good solut...
Ralf Behnke, Jakob Salzmann, Dominik Lieckfeldt, D...
ICASSP
2011
IEEE
13 years 1 months ago
A partial least squares framework for speaker recognition
Modern approaches to speaker recognition (verification) operate in a space of “supervectors” created via concatenation of the mean vectors of a Gaussian mixture model (GMM) a...
Balaji Vasan Srinivasan, Dmitry N. Zotkin, Ramani ...
NIPS
2001
13 years 11 months ago
Model-Free Least-Squares Policy Iteration
We propose a new approach to reinforcement learning which combines least squares function approximation with policy iteration. Our method is model-free and completely off policy. ...
Michail G. Lagoudakis, Ronald Parr