搜索结果: 1-15 共查到“D-norm”相关记录42条 . 查询时间(0.058 秒)
On computing the H_infinity-norm of a transfer matrix
Transfer matrix the bisection algorithm computation the transfer matrix the norm
2015/8/13
We present a simple bisection algorithm to compute the H_infinity norm of a transfer matrix. The bisection method is far more efficient than algorithms which involve a search over frequencies, and mor...
Computation of the Maximum H_infinity-norm of Parameter-Dependent Linear Systems by a Branch and Bound Algorithm
Computation Maximum H_infinity-norm Parameter-Dependent Linear Systems Bound Algorithm
2015/7/13
For linear systems that contain unspecified parameters that lie in given intervals, we present a branch and bound algorithm for computing the maximum H_infinity-norm over the set of uncertain paramete...
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...
Stable Estimation of a Covariance Matrix Guided by Nuclear Norm Penalties
Covariance estimation Regularization Condition number Canonical correlation analysis Discriminant analysis Clustering
2013/6/14
Estimation of covariance matrices or their inverses plays a central role in many statistical methods. For these methods to work reliably, estimated matrices must not only be invertible but also well-c...
Convex Tensor Decomposition via Structured Schatten Norm Regularization
Convex Tensor Decomposition Structured Schatten Norm Regularization
2013/4/28
We discuss structured Schatten norms for tensor decomposition that includes two recently proposed norms ("overlapped" and "latent") for convex-optimization-based tensor decomposition, and connect tens...
$l_{2,p}$ Matrix Norm and Its Application in Feature Selection
$l_{2,p}$ Matrix Norm Its Application Feature Selection
2013/5/2
Recently, $l_{2,1}$ matrix norm has been widely applied to many areas such as computer vision, pattern recognition, biological study and etc. As an extension of $l_1$ vector norm, the mixed $l_{2,1}$ ...
Max-stable processes and the functional D-norm revisited
Max-stable process D-norm functional max-domain of attraction copula process generalized Pareto process δ-neighborhood of generalized Pareto process t-test for max-stable and for generalized Pareto process
2013/5/2
Aulbach et al. (2012) introduced some mathematical framework for extreme value theory in the space of continuous functions on compact intervals. Continuous max-stable processes on [0,1] were character...
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...
Breaking the Rules: Low Trait or State Self-Control Increases Social Norm Violations
Ego Depletion Social Norms Self-Control Self-Regulation Ethical Behavior Risk Taking Reciprocity
2013/2/21
Two pilot and six studies indicated that poor self-control causes people to violate social norms and rules that are effortful to follow. Lower trait self-control was associated with a greater willingn...
Fast and Accurate Algorithms for Re-Weighted L1-Norm Minimization
Fast and Accurate Algorithms Re-Weighted L1-Norm Minimization
2012/9/17
To recover a sparse signal from an underdetermined system, we often solve a constrained`1-norm minimization problem. In many cases, the signal sparsity and the recovery performance can be further impr...
Atomic norm denoising with applications to line spectral estimation
Atomic norm line spectral estimation Information Theory
2012/4/18
The sub-Nyquist estimation of line spectra is a classical problem in signal processing, but currently popular subspace-based techniques have few guarantees in the presence of noise and rely on a prior...
The Impact of ‘Violating the Heterosexual Norm’ on Reading Speed and Accuracy
Schema Reading Accuracy
2013/2/22
This study explores the impact of “schema non-congruent” content on reading speed that has been found in relation to non-stereotypical gender roles. The goal of the present study is to assess if this ...
Learning Image Vicept Description via Mixed-Norm Regularization for Large Scale Semantic Image Search
Vicept Description via Mixed-Norm Regularization Large Scale
2013/7/24
The paradox of visual polysemia and concept polymorphism has been a great challenge in the large scale semanticimage search. To address this problem, our paper proposesa new method to generate image V...
Learning with the Weighted Trace-norm under Arbitrary Sampling Distributions
Learning Weighted Trace-norm Arbitrary Sampling Distributions
2011/7/7
We provide rigorous guarantees on learning with the weighted trace-norm under arbitrary sampling distributions.
Efficient lp-Norm Multiple Feature Metric Learning for Image Categorization
Algorithms Performance Experimentation
2013/7/24
Previous metric learning approaches are only able to learn the metric based on single concatenated multivariate feature representation. However, for many real world problems with multiple feature repr...