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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...
Distributed Estimation via Dual Decomposition
Distributed Estimation via Dual Decomposition
2015/7/10
The focus of this paper is to develop a framework for distributed estimation via convex optimization. We deal with a network of complex sensor subsystems with local estimation and signal processing. M...
Mixed State Estimation for a Linear Gaussian Markov Model
Mixed State Estimation Linear Gaussian Markov Model
2015/7/9
We consider a discrete-time dynamical system with Boolean and continuous states, with the continuous state propagating linearly in the continuous and Boolean state variables, and an additive Gaussian ...
Optimal Estimation of Deterioration from Diagnostic Image Sequence
Damage interior-point methods optimal estimation regularization
2015/7/9
Estimation of mechanical structure damage can greatly benefit from the knowledge that the damage accumulates irreversibly over time. This paper formulates a problem of estimation of a pixel-wise monot...
Estimation of Faults in DC Electrical Power System
Estimation Faults DC Electrical Power System
2015/7/9
This paper demonstrates a novel optimization-based approach to estimating fault states in a DC power system. The model includes faults changing the circuit topology along with sensor faults. Our appro...
Mixed Linear System Estimation and Identification
Statistical estimation Convex relaxation Interior-point methods
2015/7/9
We consider a mixed linear system model, with both continuous and discrete inputs and outputs, described by a coefficient matrix and a set of noise variances. When the discrete inputs and outputs are ...
Nonparametric Estimation of Tail Probabilities for the Single-Server Queue
Nonparametric Estimation Tail Probabilities Single-Server Queue
2015/7/8
We consider the estimation of tail probabilities in queues via the nonparametric estimator constructed by simple computing the observed fraction of time that the queue is out in the tail. We show that...
On the Validity of Long-Run Estimation Methods for Discrete-Event Systems
Validity Long-Run Estimation Methods Discrete-Event Systems
2015/7/8
On the Validity of Long-Run Estimation Methods for Discrete-Event Systems.
In this paper, we introduce a new approach to constructing unbiased estimators when computing expectations of path functionals associated with stochastic differential equations (SDEs). Our randomizati...
The Cross-Entropy Method for Estimation
cross-entropy estimation rare events importance sampling adaptive Monte Carlo zero-variance distribution
2015/7/6
This chapter describes how difficult statistical estimation problems can often be solved efficiently by means of the cross-entropy (CE) method. The CE method can be viewed as an adaptive importance sa...
The Dantzig selector:statistical estimation when p is much larger than n
Statistical linear model model selection ideal estimation oracle inequalities sparse solutions to underdetermined systems `1-minimization linear programming restricted orthonormality geometry in high dimensions random matrices
2015/6/17
In many important statistical applications, the number of variables or parameters p is much larger than the number of observations n. Suppose then that we have observations y = Xβ + z, where β ∈ Rp is...
Modern statistical estimation via oracle inequalities
Modern statistical estimation oracle inequalities
2015/6/17
A number of fundamental results in modern statistical theory involve thresholding estimators. This survey paper aims at reconstructing the history of how thresholding rules came to be popular in stati...
REJOINDER: THE DANTZIG SELECTOR:STATISTICAL ESTIMATION WHEN P IS MUCH LARGER THAN N
DANTZIG SELECTOR STATISTICAL ESTIMATION MUCH LARGER THAN N
2015/6/17
First of all, we would like to thank all the discussants for their interest and comments, as well as for their thorough investigation. The comments all underlie the importance and timeliness of the to...
Supplementary materials for Statistical Estimation and Testing via the Sorted 1 Norm
Supplementary materials Statistical Estimation Sorted 1 Norm
2015/6/17
In this note we give a proof showing that even though the number of false discoveries and the total number of discoveries are not continuous functions of the parameters, the formulas we obtain for the...
Non-linear dimensionality reduction: Riemannian metric estimation and the problem of geometric discovery
Non-linear dimensionality reduction Riemannian metric estimation the problem geometric discovery
2013/6/14
In recent years, manifold learning has become increasingly popular as a tool for performing non-linear dimensionality reduction. This has led to the development of numerous algorithms of varying degre...