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» The Measurable Space of Stochastic Processes
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GLVLSI
2005
IEEE
118views VLSI» more  GLVLSI 2005»
14 years 3 months ago
A continuous time markov decision process based on-chip buffer allocation methodology
We have presented an optimal on-chip buffer allocation and buffer insertion methodology which uses stochastic models of the architecture. This methodology uses finite buffer s...
Sankalp Kallakuri, Nattawut Thepayasuwan, Alex Dob...
IPMI
1999
Springer
14 years 10 months ago
Brain Morphometry by Distance Measurement in a Non-Euclidean, Curvilinear Space
Inspired by the discussion in neurological research about the callosal fiber connections with respect to brain asymmetry we developed a technique that measures distances between br...
Martin Styner, Thomas Coradi, Guido Gerig
AAAI
2008
14 years 4 days ago
Towards Faster Planning with Continuous Resources in Stochastic Domains
Agents often have to construct plans that obey resource limits for continuous resources whose consumption can only be characterized by probability distributions. While Markov Deci...
Janusz Marecki, Milind Tambe
SIGMETRICS
2000
ACM
105views Hardware» more  SIGMETRICS 2000»
14 years 2 months ago
Using the exact state space of a Markov model to compute approximate stationary measures
We present a new approximation algorithm based on an exact representation of the state space S, using decision diagrams, and of the transition rate matrix R, using Kronecker algeb...
Andrew S. Miner, Gianfranco Ciardo, Susanna Donate...
JMLR
2010
129views more  JMLR 2010»
13 years 8 months ago
On Finding Predictors for Arbitrary Families of Processes
The problem is sequence prediction in the following setting. A sequence x1, . . . , xn, . . . of discrete-valued observations is generated according to some unknown probabilistic ...
Daniil Ryabko