380 search results - page 15 / 76 » Models of active learning in group-structured state spaces |
94
Voted
NIPS
2003
14 years 11 months ago
2003
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...
ECML
2006
Springer
15 years 1 months ago
2006
Springer
Reinforcement learning in real-world domains suffers from three curses of dimensionality: explosions in state and action spaces, and high stochasticity. We present approaches that ...
163
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NEUROSCIENCE
2001
Springer
15 years 2 months ago
2001
Springer
Abstract. Finite-state machines are the most pervasive models of computation, not only in theoretical computer science, but also in all of its applications to real-life problems, a...
ICASSP
2011
IEEE
14 years 1 months ago
2011
IEEE
We present learning and inference algorithms for a versatile class of partially observed vector autoregressive (VAR) models for multivariate time-series data. VAR models can captu...
138
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CVPR
2009
IEEE
16 years 4 months ago
2009
IEEE
Scarcity and infeasibility of human supervision for large
scale multi-class classification problems necessitates active
learning. Unfortunately, existing active learning methods
...