搜索结果: 1-15 共查到“stochastic”相关记录346条 . 查询时间(0.125 秒)
Determining the optimal selling time of cattle:A stochastic dynamic programming approach
decision analysis farm management simulation
2016/11/11
The world meat market demands competitiveness, and optimal livestock replacement decisions can help to achieve this goal. In the article, there is introduced a novel discrete stochastic dynamic progra...
Stochastic Superoptimization
64-bit x86 x86-64 Binary Markov Chain Monte Carlo MCMC Stochastic Search Superoptimization SMT
2016/5/24
We formulate the loop-free binary superoptimization task as a stochastic search problem. The competing constraints of transformation correctness and performance improvement are encoded as terms in a c...
Stochastic Optimization of Floating Point Programs with Tunable Precision
64-bit x86 x86-64, Binary Markov Chain Monte Carlo MCMC Stochastic Search SMT Floating-Point Precision
2016/5/24
The aggressive optimization of floating-point computations is an important problem in high-performance computing. Unfortunately,floating-point instruction sets have complicated semantics that often fo...
The optimization of short sequences of loop-free, fixed-point assembly code sequences is an important problem in highperformance computing. However, the competing constraints of transformation correct...
High Dimensional Stochastic Regression with Latent Factors, Endogeneity and Nonlinearity
α-mixing dimension reduction instrument variables nonstationarity time series
2016/1/26
We consider a multivariate time series model which represents a high dimensional vector process as a sum of three terms: a linear regression of some observed regressors, a linear com-bination of some ...
High dimensional stochastic regression with latent factors, endogeneity and nonlinearity
α-mixing dimension reduction instrument variables nonstationarity time series
2016/1/25
We consider a multivariate time series model which represents a high dimensional vector process as a sum of three terms: a linear regression of some observed regressors,a linear combination of some la...
Bessel Processes, Stochastic Volatility, and Timer Options
Bessel Processes Stochastic Volatility Timer Options
2016/1/25
Motivated by analytical valuation of timer options (an important innovation in realized variance based derivatives), we explore their novel mathematical connection with stochastic volatility and Besse...
Stochastic Combinatorial Optimization via Poisson Approximation
Stochastic Knapsack Stochastic Bin Packing Expected Util- ity Maximization
2016/1/23
We study several stochastic combinatorial problems, includ-ing the expected utility maximization problem, the stochas-tic knapsack problem and the stochastic bin packing prob-lem. A common technical c...
The Power of Online Learning in Stochastic Network Optimization
Power Online Learning Stochastic Network Optimization
2016/1/22
In this paper, we investigate the power of online learning in stochastic network optimization with unknown system statistics a priori. We are interested in understanding how information and learning c...
Approximating the Expected Values for Combinatorial Optimization Problems over Stochastic Points
Approximating Expected Values Combinatorial Optimization Problems Stochastic Points
2016/1/22
We consider the stochastic geometry model where the location of each node is a random point in a given metric space,or the existence of each node is uncertain. We study the problem-s of computing the ...
Receding Learning-aided Control in Stochastic Networks
Receding learning-aided control Detection Network optimization Queueing
2016/1/22
In this paper, we develop the Receding Learning-aided Control algorithm ( RLC ) for solving optimization problems in general stochastic networks with potentially non-stationary system dynamics. RLC is...
Stochastic Online Greedy Learning with Semi-bandit Feedbacks
Stochastic Online Greedy Learning Semi-bandit Feedbacks
2016/1/22
The greedy algorithm is extensively studied in the field of combinatorial optimiza-tion for decades. In this paper, we address the online learning problem when the input to the greedy algorithm is sto...
High dimensional stochastic regression with latent factors, endogeneity and nonlinearity
α-mixing, dimension reduction instrument variables nonstationarity time series
2016/1/20
We consider a multivariate time series model which represents a high dimensional vector process as a sum of three terms: a linear regression of some observed regressors,a linear combination of some la...
Bessel Processes, Stochastic Volatility, and Timer Options
Bessel Processes Stochastic Volatility Timer Options
2016/1/20
Motivated by analytical valuation of timer options (an important innovation in realized variance based derivatives), we explore their novel mathematical connection with stochastic volatility and Besse...
A Stochastic Model of Mortality, Fertility, and Human Capital Investment
Uncertainty Precautionary demand Quality-Quantity trade off
2015/9/21
This paper examines the relationship between fertility and human capital investment,
and it’s implications for economic growth, focusing on the effects of declining mortality.
Unlike the exist...