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ECML
2006
Springer
14 years 1 months ago
Scaling Model-Based Average-Reward Reinforcement Learning for Product Delivery
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 ...
Scott Proper, Prasad Tadepalli
AAAI
2010
13 years 11 months ago
A Restriction of Extended Resolution for Clause Learning SAT Solvers
Modern complete SAT solvers almost uniformly implement variations of the clause learning framework introduced by Grasp and Chaff. The success of these solvers has been theoretical...
Gilles Audemard, George Katsirelos, Laurent Simon
FLAIRS
2007
14 years 7 days ago
Learning to Identify Global Bottlenecks in Constraint Satisfaction Search
Using information from failures to guide subsequent search is an important technique for solving combinatorial problems in domains such as boolean satisfiability (SAT) and constr...
Diarmuid Grimes, Richard J. Wallace
ECCV
2006
Springer
14 years 11 months ago
Tracking Objects Across Cameras by Incrementally Learning Inter-camera Colour Calibration and Patterns of Activity
This paper presents a scalable solution to the problem of tracking objects across spatially separated, uncalibrated, non-overlapping cameras. Unlike other approaches this technique...
Andrew Gilbert, Richard Bowden
READING
2004
Springer
14 years 3 months ago
Improving Document Transformation Techniques with Collaborative Learned Term-Based Concepts
Document Transformation techniques have been studied for decades. In this paper, a new approach for a significant improvement is presented based on using a new query expansion met...
Stefan Klink