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» Complexities for generalized models of self-assembly
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138
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ECML
2006
Springer
15 years 8 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»
14 years 11 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
118
Voted
ICIP
2006
IEEE
16 years 6 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 9 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
148
Voted
ML
1998
ACM
139views Machine Learning» more  ML 1998»
15 years 4 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