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ICML
2009
IEEE
16 years 3 months ago
Learning spectral graph transformations for link prediction
We present a unified framework for learning link prediction and edge weight prediction functions in large networks, based on the transformation of a graph's algebraic spectru...
Andreas Lommatzsch, Jérôme Kunegis
ICDAR
2003
IEEE
15 years 7 months ago
A class-modular GLVQ ensemble with outlier learning for handwritten digit recognition
A class-modular generalized learning vector quantization (GLVQ) ensemble method with outlier learning for handwritten digit recognition is proposed. A GLVQ classifier is one of d...
Katsuhiko Takahashi, Daisuke Nishiwaki
COLT
2008
Springer
15 years 4 months ago
Competing in the Dark: An Efficient Algorithm for Bandit Linear Optimization
We introduce an efficient algorithm for the problem of online linear optimization in the bandit setting which achieves the optimal O ( T) regret. The setting is a natural general...
Jacob Abernethy, Elad Hazan, Alexander Rakhlin
ICML
2001
IEEE
16 years 3 months ago
Continuous-Time Hierarchical Reinforcement Learning
Hierarchical reinforcement learning (RL) is a general framework which studies how to exploit the structure of actions and tasks to accelerate policy learning in large domains. Pri...
Mohammad Ghavamzadeh, Sridhar Mahadevan
ICML
2002
IEEE
16 years 3 months ago
Learning to Share Distributed Probabilistic Beliefs
In this paper, we present a general machine learning approach to the problem of deciding when to share probabilistic beliefs between agents for distributed monitoring. Our approac...
Christopher Leckie, Kotagiri Ramamohanarao