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COLT
2008
Springer
15 years 1 months ago
Learning Rotations
An algorithm is presented for online learning of rotations. The proposed algorithm involves matrix exponentiated gradient updates and is motivated by the von Neumann divergence. T...
Adam M. Smith, Manfred K. Warmuth
AAAI
2010
15 years 1 months ago
Multi-Agent Learning with Policy Prediction
Due to the non-stationary environment, learning in multi-agent systems is a challenging problem. This paper first introduces a new gradient-based learning algorithm, augmenting th...
Chongjie Zhang, Victor R. Lesser
NAACL
2007
15 years 1 months ago
Using "Annotator Rationales" to Improve Machine Learning for Text Categorization
We propose a new framework for supervised machine learning. Our goal is to learn from smaller amounts of supervised training data, by collecting a richer kind of training data: an...
Omar Zaidan, Jason Eisner, Christine D. Piatko
NIPS
2007
15 years 1 months ago
An online Hebbian learning rule that performs Independent Component Analysis
Independent component analysis (ICA) is a powerful method to decouple signals. Most of the algorithms performing ICA do not consider the temporal correlations of the signal, but o...
Claudia Clopath, André Longtin, Wulfram Ger...
NIPS
2003
15 years 1 months ago
Gaussian Processes in Reinforcement Learning
We exploit some useful properties of Gaussian process (GP) regression models for reinforcement learning in continuous state spaces and discrete time. We demonstrate how the GP mod...
Carl Edward Rasmussen, Malte Kuss