搜索结果: 1-15 共查到“理论统计学 Uncertainty”相关记录16条 . 查询时间(0.137 秒)
OPERA: Optimization with Ellipsoidal Uncertainty for Robust Analog IC Design
Statistical optim ization
2015/7/10
As the design-manufacturing interface becomes increasingly complicated with IC technology scaling, the corresponding process variability poses great challenges for nanoscale analog/RF design. Design o...
Likelihood Bounds for Constrained Estimation with Uncertainty
Likelihood Bounds Constrained Estimation Uncertainty
2015/7/10
This paper addresses the problem of finding bounds on the optimal maximum a posteriori (or maximum likelihood) estimate in a linear model under the presence of model uncertainty. We introduce the nove...
Capturing Data Uncertainty in HighVolume Stream Processing
Data flow system data collection data modeling the sensor data
2014/12/24
We present the design and development of a data stream system that captures data uncertainty from data collection to query processing to final result generation. Our system focuses on data that is nat...
Model-based dose finding under model uncertainty using general parametric models
Model-based model uncertainty parametric models
2013/6/13
Statistical methodology for the design and analysis of clinical Phase II dose response studies, with related software implementation, are well developed for the case of a normally distributed, homosce...
Consider approximating a function $f$ by an emulator $\hat{f}$ based on $n$ observations of $f$. This problem is a common when observing $f$ requires a computationally demanding simulation or an actua...
Approximate Propagation of both Epistemic and Aleatory Uncertainty through Dynamic Systems
Uncertainty Propagation Epistemic Uncertainty Aleatory Uncertainty Dempster-Shafer
2011/7/19
When ignorance due to the lack of knowledge, modeled as epistemic uncertainty using Dempster-Shafer structures on closed intervals, is present in the model parameters, a new uncertainty propagation me...
Generalized Likelihood Ratio Statistics and Uncertainty Adjustments in Efficient Adaptive Design of Clinical Trials
Hoeffding’s information bound Internal pilot Kullback-Leibler information Modified Haybittle-Peto test Multiparameter exponential family Sample size re-estimation
2011/6/20
A new approach to adaptive design of clinical trials is proposed in a general multi-
parameter exponential family setting, based on generalized likelihood ratio statistics and optimal
sequential tes...
Multiple testing, uncertainty and realistic pictures
Image analysis signal detection image recon-struction percolation noisy image shape constraints unsupervised ma-chine learning spatial statistics multiple testing
2011/3/24
We study statistical detection of grayscale objects in noisy images. The object of interest is of unknown shape and has an unknown intensity, that can be varying over the object and can be negative. N...
Uncertainty quantification and weak approximation of an elliptic inverse problem
Uncertainty quantification weak approximation elliptic inverse problem
2011/3/18
We consider the inverse problem of determining the permeability from the pressure in a Darcy model of flow in a porous medium. Mathematically the problem is to find the diffusion coefficient for a lin...
Reconstruction of signals with unknown spectra in information field theory with parameter uncertainty
Reconstruction signals unknown spectra information field theory parameter uncertainty
2010/3/11
The optimal reconstruction of cosmic metric perturbations and other signals requires knowledge
of their power spectra and other parameters. If these are not known a priori, they have to be
measured ...
在运筹学、管理科学、决策科学、信息科学、系统科学、计算机科学、工业工程、金融等众多领域都存在着客观的或人为的不确定性，其表现形式也多种多样，如随机性与模糊性。不确定系统研究的对象主要是不确定理论及其应用。为了推动不确定理论的发展，活跃该领域的研究，交流总结近年来我国不确定系统研究工作者的最新成果，由中国运筹学会不确定系统分会主办和重庆大学承办的第七届中国不确定系统年会将于2009年8月20-24日...
Bayesian projection approaches to variable selection and exploring model uncertainty
Bayesian variable selection Kullback-Leibler projection lasso non-negative garotte preconditioning
2010/3/17
A Bayesian approach to variable selection which is based on the expected Kullback-
Leibler divergence between the full model and its projection onto a submodel has
recently been suggested in the lit...
Scaling factors for ab initio vibrational frequencies：comparison of uncertainty models for quantified prediction
Bayesian data analysis Model calibration Scaling factor Vibrational frequency
2010/3/17
Bayesian Model Calibration is used to revisit the problem of scaling factor calibration for
semi-empirical correction of ab initio calculations. A particular attention is devoted to
uncertainty eval...
Uncertainty quantification in complex systems using approximate solvers
uncertainty quantification Monte Carlo Bayesian nonparametric regression
2010/4/30
This paper proposes a novel uncertainty quantification framework for computationally
demanding systems characterized by a large vector of non-Gaussian uncertainties. It combines
state-of-the-art tec...
A Robertson-type Uncertainty Principle and Quantum Fisher Information
Generalized variance uncertainty principle operator monotone functions matrix means quantum Fisher information
2010/4/30
Let A1, ..., AN be complex selfadjoint matrices and let be a density matrix. The Robertson
uncertainty principledet {Cov(Ah,Aj)} ≥ det−i2Tr([Ah,Aj ])ff gives a bound for the quantum...