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» Randomness, Stochasticity and Approximations
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BMCBI
2010
108views more  BMCBI 2010»
15 years 3 months ago
Prediction of RNA secondary structure by maximizing pseudo-expected accuracy
Background: Recent studies have revealed the importance of considering the entire distribution of possible secondary structures in RNA secondary structure predictions; therefore, ...
Michiaki Hamada, Kengo Sato, Kiyoshi Asai
CMSB
2007
Springer
16 years 9 days ago
Expressive Models for Synaptic Plasticity
We explore some presynaptic mechanisms of the calyx of Held synapse through a stochastic model. The model, drawn from a kinetic approach developed in literature, exploits process c...
Andrea Bracciali, Marcello Brunelli, Enrico Catald...
AIPS
2010
15 years 8 months ago
When Policies Can Be Trusted: Analyzing a Criteria to Identify Optimal Policies in MDPs with Unknown Model Parameters
Computing a good policy in stochastic uncertain environments with unknown dynamics and reward model parameters is a challenging task. In a number of domains, ranging from space ro...
Emma Brunskill
165
Voted
NIPS
1998
15 years 7 months ago
Learning Nonlinear Dynamical Systems Using an EM Algorithm
The Expectation Maximization EM algorithm is an iterative procedure for maximum likelihood parameter estimation from data sets with missing or hidden variables 2 . It has been app...
Zoubin Ghahramani, Sam T. Roweis
176
Voted
NIPS
1996
15 years 7 months ago
Reinforcement Learning for Dynamic Channel Allocation in Cellular Telephone Systems
In cellular telephone systems, an important problem is to dynamically allocate the communication resource channels so as to maximize service in a stochastic caller environment. Th...
Satinder P. Singh, Dimitri P. Bertsekas