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ICML
2007
IEEE
16 years 7 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
13 years 8 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»
15 years 11 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»
15 years 6 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
15 years 11 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