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ECML
2006
Springer
15 years 10 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
JMLR
2010
118views more  JMLR 2010»
15 years 1 months ago
Exploiting Within-Clique Factorizations in Junction-Tree Algorithms
It is probably fair to say that exact inference in graphical models is considered a solved problem, at least regarding its computational complexity: it is exponential in the treew...
Julian John McAuley, Tibério S. Caetano
ICIP
2006
IEEE
16 years 8 months ago
On the Information Rate of the Plenoptic Function
We study the compression problem of visual scenes acquired with a camera for transmission or storage. Our proposed model is general and includes two well-known cases: that of vide...
Arthur L. da Cunha, Minh N. Do, Martin Vetterli
EGH
2003
Springer
15 years 11 months ago
Mesh mutation in programmable graphics hardware
We show how a future graphics processor unit (GPU), enhanced with random read and write to video memory, can represent, refine and adjust complex meshes arising in modeling, simu...
Le-Jeng Shiue, Vineet Goel, Jörg Peters
ML
1998
ACM
139views Machine Learning» more  ML 1998»
15 years 6 months ago
The Hierarchical Hidden Markov Model: Analysis and Applications
We introduce, analyze and demonstrate a recursive hierarchical generalization of the widely used hidden Markov models, which we name Hierarchical Hidden Markov Models (HHMM). Our m...
Shai Fine, Yoram Singer, Naftali Tishby