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LION
2010
Springer
190views Optimization» more  LION 2010»
14 years 2 months ago
Algorithm Selection as a Bandit Problem with Unbounded Losses
Abstract. Algorithm selection is typically based on models of algorithm performance learned during a separate offline training sequence, which can be prohibitively expensive. In r...
Matteo Gagliolo, Jürgen Schmidhuber
ICCV
2009
IEEE
13 years 8 months ago
Local distance functions: A taxonomy, new algorithms, and an evaluation
We present a taxonomy for local distance functions where most existing algorithms can be regarded as approximations of the geodesic distance defined by a metric tensor. We categor...
Deva Ramanan, Simon Baker
ITNG
2010
IEEE
14 years 3 months ago
A Fast and Stable Incremental Clustering Algorithm
— Clustering is a pivotal building block in many data mining applications and in machine learning in general. Most clustering algorithms in the literature pertain to off-line (or...
Steven Young, Itamar Arel, Thomas P. Karnowski, De...
CEC
2005
IEEE
14 years 4 months ago
A study on polynomial regression and Gaussian process global surrogate model in hierarchical surrogate-assisted evolutionary alg
This paper presents a study on Hierarchical Surrogate-Assisted Evolutionary Algorithm (HSAEA) using different global surrogate models for solving computationally expensive optimiza...
Zongzhao Zhou, Yew-Soon Ong, My Hanh Nguyen, Dudy ...
IJCAI
2007
14 years 7 days ago
Fast Image Alignment Using Anytime Algorithms
Image alignment refers to finding the best transformation from a fixed reference image to a new image of a scene. This process is often guided by similarity measures between ima...
Rupert Brooks, Tal Arbel, Doina Precup