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Tests for High Dimensional Generalized Linear Models
Generalized Linear Model Gene-Sets High Dimensional Covariate Nuisance Parameter U-statistics
2016/1/26
We consider testing regression coefficients in high dimensional generalized linear mod-els. By modifying a test statistic proposed by Goeman et al. (2011) for large but fixed dimensional settings, we ...
Tests for High Dimensional Generalized Linear Models
Generalized Linear Model Gene-Sets High Dimensional Covariate Nuisance Parameter U-statistics
2016/1/20
We consider testing regression coefficients in high dimensional generalized linear mod-els. By modifying a test statistic proposed by Goeman et al. (2011) for large but fixed dimensional settings, we ...
Profiled Forward Regression for Ultrahigh Dimensional Variable Screening in Semiparametric Partially Linear Models
Forward Regression Partially Linear Model Profiled Forward Regres- 9 sion Screening Consistency
2016/1/19
Profiled Forward Regression for Ultrahigh Dimensional Variable Screening in Semiparametric Partially Linear Models.
Integer Parameter Estimation in Linear Models with Applications to GPS
GPS integer least-squares integer parameter estimation linear model
2015/7/10
We consider parameter estimation in linear models when some of the parameters are known to be integers. Such problems arise, for example, in positioning using phase measurements in the global position...
Robust Linear Programming and Optimal Control
Linear programming Convex optimization Model-predictive control
2015/7/10
We describe an efficient method for solving an optimal control problem that arises in robust model-predictive control. The problem is to design the input sequence that minimizes the peak tracking erro...
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 ...
Convex Piecewise-Linear Fitting
Convex optimization Piecewise-linear approximation Data fi tting
2015/7/9
We consider the problem of fitting a convex piecewise-linear function, with some specified form, to given multi-dimensional data. Except for a few special cases, this problem is hard to solve exactly,...
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 ...
Linear Models Based on Noisy Data and the Frisch Scheme
linear models factor analysis identifi cation
2015/7/8
We address the problem of identifying linear relations among variables based on noisy measurements. This is a central question in the search for structure in large data sets. Often a key assumption is...
Standard nearest-neighbour discretizations of Klein–Gordon models cannot preserve both energy and linear momentum
Discrete nonlinear klein GeDengBo equation the standard discrete linear momentum
2014/12/25
We consider nonlinear Klein–Gordon wave equations and illustrate that standard discretizations thereof (involving nearest neighbours) may preserve either standardly defined linear momentum or standard...
Solitary waves under the competition of linear and nonlinear periodic potentials
The linear and nonlinear lattice bright solitons dynamics
2014/12/25
In this paper, we study the competition of the linear and nonlinear lattices and its effects on the stability and dynamics of bright solitary waves. We consider both lattices in a perturbative framewo...
Asymptotic calculation of discrete non-linear wave interactions
Discrete the dispersion equation klein Gordon
2014/12/25
We illustrate how to compute asymptotic interactions between discrete solitary waves of dispersive equations, using the approach proposed by Manton [N.S. Manton, Nucl. Phys. B 150 (1979) 397]. We also...
n this paper we prove that the linear Koszul duality equivalence constructed in a previous paper provides a geometric realization of the Iwahori-Matsumoto involution of affine Hecke algebras.
Linear Koszul duality
Plexus vector duality Hecke algebra
2014/12/24
In this paper we construct, for F1 and F2 subbundles of a vector bundle E, a ‘Koszul duality’ equivalence between derived categories of m-equivariant coherent(dg-)sheaves on the derived intersection ,...
Non-linear dimensionality reduction: Riemannian metric estimation and the problem of geometric discovery
Non-linear dimensionality reduction Riemannian metric estimation the problem geometric discovery
2013/5/30
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...