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» The complexity of stochastic sequences
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DATE
2008
IEEE
136views Hardware» more  DATE 2008»
15 years 6 months ago
A Framework of Stochastic Power Management Using Hidden Markov Model
- The effectiveness of stochastic power management relies on the accurate system and workload model and effective policy optimization. Workload modeling is a machine learning proce...
Ying Tan, Qinru Qiu
CLEIEJ
2006
97views more  CLEIEJ 2006»
14 years 12 months ago
Prediction of RNA Pseudoknotted Secondary Structure using Stochastic Context Free Grammars (SCFG)
Pseudoknots are a frequent RNA structure that assumes essential roles for varied biocatalyst cell's functions. One of the most challenging fields in bioinformatics is the pre...
Rafael Garcia
CORR
2010
Springer
127views Education» more  CORR 2010»
14 years 12 months ago
Statistical and Computational Tradeoffs in Stochastic Composite Likelihood
Maximum likelihood estimators are often of limited practical use due to the intensive computation they require. We propose a family of alternative estimators that maximize a stoch...
Joshua Dillon, Guy Lebanon
MOR
2010
121views more  MOR 2010»
14 years 10 months ago
Customer Abandonment in Many-Server Queues
We study G/G/n + GI queues in which customer patience times are independent, identically distributed following a general distribution. When a customer’s waiting time in queue ex...
J. G. Dai, Shuangchi He
MP
2006
87views more  MP 2006»
14 years 11 months ago
Convexity and decomposition of mean-risk stochastic programs
Abstract. Traditional stochastic programming is risk neutral in the sense that it is concerned with the optimization of an expectation criterion. A common approach to addressing ri...
Shabbir Ahmed