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SIGIR
2006
ACM
16 years 1 months ago
Large scale semi-supervised linear SVMs
Large scale learning is often realistic only in a semi-supervised setting where a small set of labeled examples is available together with a large collection of unlabeled data. In...
Vikas Sindhwani, S. Sathiya Keerthi
AICCSA
2005
IEEE
168views Hardware» more  AICCSA 2005»
16 years 1 months ago
A dynamic range resource reservation protocol for QoS support in wireless networks
— Mobile ad hoc networks (MANETs) provide a powerful and dynamic platform to enable mobile computers to establish communications without an existing infrastructure. In order to p...
Imad Jawhar, Jie Wu
PLDI
2005
ACM
16 years 1 months ago
Programming ad-hoc networks of mobile and resource-constrained devices
Ad-hoc networks of mobile devices such as smart phones and PDAs represent a new and exciting distributed system architecture. Building distributed applications on such an architec...
Yang Ni, Ulrich Kremer, Adrian Stere, Liviu Iftode
ATAL
2005
Springer
16 years 1 months ago
Improving reinforcement learning function approximators via neuroevolution
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Shimon Whiteson
CIKM
2005
Springer
16 years 1 months ago
Internet scale string attribute publish/subscribe data networks
With this work we aim to make a three-fold contribution. We first address the issue of supporting efficiently queries over string-attributes involving prefix, suffix, containmen...
Ioannis Aekaterinidis, Peter Triantafillou
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