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131
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ICML
2004
IEEE
16 years 4 months ago
Learning with non-positive kernels
In this paper we show that many kernel methods can be adapted to deal with indefinite kernels, that is, kernels which are not positive semidefinite. They do not satisfy Mercer...
Alexander J. Smola, Cheng Soon Ong, Stéphan...
166
Voted
ALT
2002
Springer
16 years 27 days ago
Optimally-Smooth Adaptive Boosting and Application to Agnostic Learning
We describe a new boosting algorithm that is the first such algorithm to be both smooth and adaptive. These two features make possible performance improvements for many learning ...
Dmitry Gavinsky
112
Voted
PKDD
2009
Springer
117views Data Mining» more  PKDD 2009»
15 years 10 months ago
New Regularized Algorithms for Transductive Learning
Abstract. We propose a new graph-based label propagation algorithm for transductive learning. Each example is associated with a vertex in an undirected graph and a weighted edge be...
Partha Pratim Talukdar, Koby Crammer
127
Voted
ROMAN
2007
IEEE
134views Robotics» more  ROMAN 2007»
15 years 10 months ago
Learning Reward Modalities for Human-Robot-Interaction in a Cooperative Training Task
—This paper proposes a novel method of learning a users preferred reward modalities for human-robot interaction through solving a cooperative training task. A learning algorithm ...
Anja Austermann, Seiji Yamada
160
Voted
ATAL
2005
Springer
15 years 9 months ago
Coordinated exploration in multi-agent reinforcement learning: an application to load-balancing
This paper is concerned with how multi-agent reinforcement learning algorithms can practically be applied to real-life problems. Recently, a new coordinated multi-agent exploratio...
Katja Verbeeck, Ann Nowé, Karl Tuyls