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ICML
2010
IEEE
15 years 2 months ago
Bayesian Multi-Task Reinforcement Learning
We consider the problem of multi-task reinforcement learning where the learner is provided with a set of tasks, for which only a small number of samples can be generated for any g...
Alessandro Lazaric, Mohammad Ghavamzadeh
ICDAR
2009
IEEE
14 years 11 months ago
Off-Line Multi-Script Writer Identification Using AR Coefficients
The problem of writer identification in a multiscript environment is attempted using a twodimensional (2D) autoregressive (AR) modelling technique. Each writer is represented by a...
Utpal Garain, Thierry Paquet
NIPS
2004
15 years 2 months ago
Modelling Uncertainty in the Game of Go
Go is an ancient oriental game whose complexity has defeated attempts to automate it. We suggest using probability in a Bayesian sense to model the uncertainty arising from the va...
David H. Stern, Thore Graepel, David J. C. MacKay
CVPR
1999
IEEE
16 years 3 months ago
A Multiple Hypothesis Approach to Figure Tracking
This paper describes a probabilistic multiple-hypothesis framework for tracking highly articulated objects. In this framework, the probability density of the tracker state is repr...
Tat-Jen Cham, James M. Rehg
RECOMB
2001
Springer
16 years 1 months ago
Fast recovery of evolutionary trees with thousands of nodes
We present a novel distance-based algorithm for evolutionary tree reconstruction. Our algorithm reconstructs the topology of a tree with n leaves in O(n2 ) time using O(n) working...
Miklós Csürös