搜索结果: 1-15 共查到“统计学 Optimization”相关记录30条 . 查询时间(0.098 秒)
Policies for Simultaneous Estimation and Optimization
Policies Simultaneous Estimation Optimization
2015/7/10
Policies for the joint identification and control of uncertain systems are presented. The discussion focuses on the case of a multiple input, single output linear system, with no dynamics and quadrati...
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...
Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
Distributed Optimization Statistical Learning via Alternating Direction Method Multipliers
2015/7/9
Many problems of recent interest in statistics and machine learning can be posed in the framework of convex optimization. Due to the explosion in size and complexity of modern datasets, it is increasi...
Complexity of Non-Adaptive Optimization Algorithms for a Class of Diffusions
Global optimization average-case complexity diffusion processes
2015/7/8
This paper is concerned with the analysis of the average error in approximating the global minimum of a 1-dimensional, time-homogeneous diffusion by non-adaptive methods. We derive the limiting distri...
A Large Deviations Perspective on Ordinal Optimization
Large Deviations Perspective Ordinal Optimization
2015/7/6
We consider the problem of optimal allocation of computing budget to maximize the probability of correct selection in the ordinal optimization setting. This problem has been studied in the literature ...
Global Optimization, the Gaussian Ensemble, and Universal Ensemble Equivalence
Unconstrained problem global optimization statistical mechanics the equivalent theory of convex function
2014/12/25
Given a constrained minimization problem, under what conditions does there exist a related, unconstrained problem having the same minimum points? This basic question in global optimization motivates t...
Robust portfolio optimization using pseudodistances
Robustness and sensitivity analysis portfolio optimization
2013/6/14
The presence of outliers in financial asset returns is a frequently occuring phenomenon and may lead to unreliable mean-variance optimized portfolios. This fact is due to the unbounded influence that ...
Optimization with First-Order Surrogate Functions
Optimization First-Order Surrogate Functions
2013/6/14
In this paper, we study optimization methods consisting of iteratively minimizing surrogates of an objective function. By proposing several algorithmic variants and simple convergence analyses, we mak...
GPfit: An R package for Gaussian Process Model Fitting using a New Optimization Algorithm
Computer experiments, clustering, near-singularity, nugget
2013/6/13
Gaussian process (GP) models are commonly used statistical metamodels for emulating expensive computer simulators. Fitting a GP model can be numerically unstable if any pair of design points in the in...
A General Iterative Shrinkage and Thresholding Algorithm for Non-convex Regularized Optimization Problems
A General Iterative Shrinkage Thresholding Algorithm Non-convex Regularized Optimization Problems
2013/5/2
Non-convex sparsity-inducing penalties have recently received considerable attentions in sparse learning. Recent theoretical investigations have demonstrated their superiority over the convex counterp...
Optimization viewpoint on Kalman smoothing, with applications to robust and sparse estimation
Optimization viewpoint Kalman smoothing applications robust sparse estimation
2013/4/28
In this paper, we present the optimization formulation of the Kalman filtering and smoothing problems, and use this perspective to develop a variety of extensions and applications. We first formulate ...
Matrix completion via max-norm constrained optimization
Compressed sensing low-rank matrix matrix completion max-norm con-strained minimization optimal rate of convergence sparsity
2013/4/28
This paper studies matrix completion under a general sampling model using the max-norm as a convex relaxation for the rank of the matrix. The optimal rate of convergence is established for the Frobeni...
On the Complexity of Bandit and Derivative-Free Stochastic Convex Optimization
Bandit Derivative-Free Stochastic Convex Optimization
2012/11/23
The problem of stochastic convex optimization with bandit feedback (in the learning community) or without knowledge of gradients (in the optimization community) has received much attention in recent y...
Spectral Risk Measures, With Adaptions For Stochastic Optimization
Spectral Risk Measures Adaptions Stochastic Optimization
2012/11/22
Stochastic optimization problems often involve the expectation in its objective. When risk is incorporated in the problem description as well, then risk measures have to be involved in addition to qua...
Query Complexity of Derivative-Free Optimization
Derivative-Free Optimization Query Complexity
2012/11/22
This paper provides lower bounds on the convergence rate of Derivative Free Optimization (DFO) with noisy function evaluations, exposing a fundamental and unavoidable gap between the performance of al...