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» TRUST-TECH based Methods for Optimization and Learning
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ICML
2000
IEEE
16 years 1 months ago
Rates of Convergence for Variable Resolution Schemes in Optimal Control
This paper presents a general method to derive tight rates of convergence for numerical approximations in optimal control when we consider variable resolution grids. We study the ...
Andrew W. Moore, Rémi Munos
KDD
2010
ACM
289views Data Mining» more  KDD 2010»
14 years 10 months ago
Exploitation and exploration in a performance based contextual advertising system
The dynamic marketplace in online advertising calls for ranking systems that are optimized to consistently promote and capitalize better performing ads. The streaming nature of on...
Wei Li 0010, Xuerui Wang, Ruofei Zhang, Ying Cui, ...
122
Voted
PAA
2010
14 years 11 months ago
Exploiting visual and text features for direct marketing learning in time and space constrained domains
Traditionally, direct marketing companies have relied on pre-testing to select the best offers to send to their audiences. Companies systematically dispatch the offers under consid...
Sebastiano Battiato, Giovanni Maria Farinella, Gio...
85
Voted
ATAL
2004
Springer
15 years 6 months ago
Decentralized Language Learning through Acting
This paper presents an algorithm for learning the meaning of messages communicated between agents that interact while acting optimally towards a cooperative goal. Our reinforcemen...
Claudia V. Goldman, Martin Allen, Shlomo Zilberste...
111
Voted
ICPR
2010
IEEE
15 years 27 days ago
Adaptive Incremental Learning with an Ensemble of Support Vector Machines
The incremental updating of classifiers implies that their internal parameter values can vary according to incoming data. As a result, in order to achieve high performance, incre...
Marcelo N. Kapp, Robert Sabourin, Patrick Maupin