509 search results - page 48 / 102 » Using Learning for Approximation in Stochastic Processes |
195
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CVPR
2009
IEEE
17 years 1 months ago
2009
IEEE
Graph-based methods form a main category of semisupervised
learning, offering flexibility and easy implementation
in many applications. However, the performance of
these methods...
162
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ECML
2007
Springer
16 years 3 days ago
2007
Springer
We present Policy Gradient Actor-Critic (PGAC), a new model-free Reinforcement Learning (RL) method for creating limited-memory stochastic policies for Partially Observable Markov ...
158
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IJCAI
1989
15 years 7 months ago
1989
In many applications in mobile robotics, it is important for a robot to explore its environment in order to construct a representation of space useful for guiding movement. We refe...
326
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ICDE
2004
IEEE
16 years 7 months ago
2004
IEEE
Moving objects (e.g., vehicles in road networks) continuously generate large amounts of spatio-temporal information in the form of data streams. Efficient management of such strea...
206
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ICALP
2001
Springer
15 years 10 months ago
2001
Springer
We present a probabilistic algorithm that, given a connected graph G (represented by adjacency lists) of average degree d, with edge weights in the set {1, . . . , w}, and given a ...