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ICML
2007
IEEE
14 years 9 months ago
Multi-task reinforcement learning: a hierarchical Bayesian approach
We consider the problem of multi-task reinforcement learning, where the agent needs to solve a sequence of Markov Decision Processes (MDPs) chosen randomly from a fixed but unknow...
Aaron Wilson, Alan Fern, Soumya Ray, Prasad Tadepa...
AAAI
2012
11 years 11 months ago
Model Learning and Real-Time Tracking Using Multi-Resolution Surfel Maps
For interaction with its environment, a robot is required to learn models of objects and to perceive these models in the livestreams from its sensors. In this paper, we propose a ...
Jörg Stückler, Sven Behnke
ACSD
2003
IEEE
151views Hardware» more  ACSD 2003»
14 years 2 months ago
Communicating Transaction Processes
Message Sequence Charts (MSC) have been traditionally used to depict execution scenarios in the early stages of design cycle. MSCs portray inter-process ( inter-object) interactio...
Abhik Roychoudhury, P. S. Thiagarajan
IJDMB
2008
128views more  IJDMB 2008»
13 years 9 months ago
Protein homology detection with biologically inspired features and interpretable statistical models
: Computational classification of proteins using methods such as string kernels and Fisher-SVM has demonstrated great success. However, the resulting models do not offer an immedia...
Pai-Hsi Huang, Vladimir Pavlovic
ECAI
2004
Springer
14 years 2 months ago
Automatic Recognition of Famous Artists by Machine
The paper addresses the question whether it is possible for a machine to learn to distinguish and recognise famous musicians (concert pianists), based on their style of playing. We...
Gerhard Widmer, Patrick Zanon