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» Approximate Policy Iteration using Large-Margin Classifiers
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IJCAI
2003
9 years 12 months ago
Approximate Policy Iteration using Large-Margin Classifiers
We present an approximate policy iteration algorithm that uses rollouts to estimate the value of each action under a given policy in a subset of states and a classifier to general...
Michail G. Lagoudakis, Ronald Parr
ICCV
2007
IEEE
11 years 16 days ago
An Invariant Large Margin Nearest Neighbour Classifier
The k-nearest neighbour (kNN) rule is a simple and effective method for multi-way classification that is much used in Computer Vision. However, its performance depends heavily on ...
M. Pawan Kumar, Philip H. S. Torr, Andrew Zisserma...
PRL
2008
118views more  PRL 2008»
9 years 10 months ago
A large margin approach for writer independent online handwriting classification
This paper proposes a new approach for classifying multivariate time-series with applications to the problem of writer independent online handwritten character recognition. Each t...
Karthik Kumara, Rahul Agrawal, Chiranjib Bhattacha...

Publication
334views
10 years 7 months ago
Rollout Sampling Approximate Policy Iteration
Several researchers have recently investigated the connection between reinforcement learning and classification. We are motivated by proposals of approximate policy iteration schem...
Christos Dimitrakakis, Michail G. Lagoudakis

Publication
222views
10 years 7 months ago
Algorithms and Bounds for Rollout Sampling Approximate Policy Iteration
Abstract: Several approximate policy iteration schemes without value functions, which focus on policy representation using classifiers and address policy learning as a supervis...
Christos Dimitrakakis, Michail G. Lagoudakis
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