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» On-line Algorithms in Machine Learning
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ALT
2008
Springer
16 years 1 months ago
Exploiting Cluster-Structure to Predict the Labeling of a Graph
Abstract. The nearest neighbor and the perceptron algorithms are intuitively motivated by the aims to exploit the “cluster” and “linear separation” structure of the data to...
Mark Herbster
SEAL
1998
Springer
15 years 8 months ago
Robust Evolution Strategies
This paper empirically investigates the use and behaviour of Evolution Strategies (ES) algorithms on problems such as function optimisation and the use of evolutionary artificial ...
Kazuhiro Ohkura, Yoshiyuki Matsumura, Kanji Ueda
COLT
2006
Springer
15 years 8 months ago
Ranking with a P-Norm Push
We are interested in supervised ranking with the following twist: our goal is to design algorithms that perform especially well near the top of the ranked list, and are only requir...
Cynthia Rudin
COLT
2008
Springer
15 years 6 months ago
Regret Bounds for Sleeping Experts and Bandits
We study on-line decision problems where the set of actions that are available to the decision algorithm vary over time. With a few notable exceptions, such problems remained larg...
Robert D. Kleinberg, Alexandru Niculescu-Mizil, Yo...
COLT
2010
Springer
15 years 2 months ago
Deterministic Sparse Fourier Approximation via Fooling Arithmetic Progressions
A significant Fourier transform (SFT) algorithm, given a threshold and oracle access to a function f, outputs (the frequencies and approximate values of) all the -significant Fou...
Adi Akavia