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ICML
2004
IEEE
16 years 19 days ago
Convergence of synchronous reinforcement learning with linear function approximation
Synchronous reinforcement learning (RL) algorithms with linear function approximation are representable as inhomogeneous matrix iterations of a special form (Schoknecht & Merk...
Artur Merke, Ralf Schoknecht
ALT
2004
Springer
15 years 8 months ago
Learning r-of-k Functions by Boosting
We investigate further improvement of boosting in the case that the target concept belongs to the class of r-of-k threshold Boolean functions, which answer “+1” if at least r o...
Kohei Hatano, Osamu Watanabe
INFORMATICALT
2007
111views more  INFORMATICALT 2007»
14 years 11 months ago
Oblique Support Vector Machines
In this paper we propose a modified framework of support vector machines, called Oblique Support Vector Machines(OSVMs), to improve the capability of classification. The principl...
Chih-Chia Yao, Pao-Ta Yu
SIGIR
2004
ACM
15 years 5 months ago
Learning effective ranking functions for newsgroup search
Web communities are web virtual broadcasting spaces where people can freely discuss anything. While such communities function as discussion boards, they have even greater value as...
Wensi Xi, Jesper Lind, Eric Brill
ICML
2006
IEEE
16 years 19 days ago
On a theory of learning with similarity functions
Kernel functions have become an extremely popular tool in machine learning, with an attractive theory as well. This theory views a kernel as implicitly mapping data points into a ...
Maria-Florina Balcan, Avrim Blum