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ICML
2006
IEEE
16 years 3 months ago
Bayesian regression with input noise for high dimensional data
This paper examines high dimensional regression with noise-contaminated input and output data. Goals of such learning problems include optimal prediction with noiseless query poin...
Jo-Anne Ting, Aaron D'Souza, Stefan Schaal
ICALP
2011
Springer
14 years 5 months ago
New Algorithms for Learning in Presence of Errors
We give new algorithms for a variety of randomly-generated instances of computational problems using a linearization technique that reduces to solving a system of linear equations...
Sanjeev Arora, Rong Ge
GECCO
2006
Springer
215views Optimization» more  GECCO 2006»
15 years 6 months ago
A multi-chromosome approach to standard and embedded cartesian genetic programming
Embedded Cartesian Genetic Programming (ECGP) is an extension of Cartesian Genetic Programming (CGP) that can automatically acquire, evolve and re-use partial solutions in the for...
James Alfred Walker, Julian Francis Miller, Rachel...
KDD
2007
ACM
197views Data Mining» more  KDD 2007»
16 years 2 months ago
Learning the kernel matrix in discriminant analysis via quadratically constrained quadratic programming
The kernel function plays a central role in kernel methods. In this paper, we consider the automated learning of the kernel matrix over a convex combination of pre-specified kerne...
Jieping Ye, Shuiwang Ji, Jianhui Chen
114
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ROBOCOMM
2007
IEEE
15 years 8 months ago
Distributed adaptive sampling using bounded-errors
—This paper presents a communication/coordination/ processing architecture for distributed adaptive observation of a spatial field using a fleet of autonomous mobile sensors. O...
Kévin Huguenin, Maria-João Rendas