搜索结果: 1-15 共查到“统计学 Manifolds”相关记录18条 . 查询时间(0.887 秒)
Some Real and Unreal Enumerative Geometry for Flag Manifolds
Build geometric shape numerical homotopy continuation algorithm
2014/12/29
We present a general method for constructing real solutions to some problems in enumerative geometry which gives lower bounds on the maximum number of real solutions. We apply this method to show that...
Smooth s-cobordisms of elliptic 3-manifolds
The oval 3-manifolds tectonic structure smooth
2014/12/25
The main result of this paper states that a symplectic s-cobordism of elliptic 3-manifolds is diffeomorphic to a product (assuming a canonical contact structure on the boundary). Based on this theorem...
A study of symplectic actions of a finite group G on smooth 4-manifolds is initiated. The central new idea is the use of G-equivariant Seiberg–Witten–Taubes theory in studying the structure of the fix...
Group actions on 4-manifolds: some recent results and open questions
Dynamic 4 - manifolds smooth symplectic classification group action
2014/12/24
A survey of finite group actions on symplectic 4-manifolds is given with a special emphasis on results and questions concerning smooth or symplectic classification of group actions, group actions and ...
On the orders of periodic diffeomorphisms of 4-manifolds
Smooth smooth and round action constant
2014/12/24
This paper initiated an investigation on the following question: Suppose that a smooth 4 -manifold does not admit any smooth circle actions. Does there exist a constant C>0 such that the manifold supp...
Embedding Riemannian Manifolds by the Heat Kernel of the Connection Laplacian
Embedding Riemannian Manifolds Heat Kernel Connection Laplacian
2013/6/17
Given a class of closed Riemannian manifolds with prescribed geometric conditions, we introduce an embedding of the manifolds into $\ell^2$ based on the heat kernel of the Connection Laplacian associa...
Sparse Projections of Medical Images onto Manifolds
Sparse Projections Medical Images Manifolds
2013/5/2
Manifold learning has been successfully applied to a variety of medical imaging problems. Its use in real-time applications requires fast projection onto the low-dimensional space. To this end, out-of...
A parameter estimation method based on random slow manifolds
Parameter estimation Slow-fast system Random slow manifold Quantifying uncer-tainty Numerical optimization
2013/5/2
A parameter estimation method is devised for a slow-fast stochastic dynamical system, where often only the slow component is observable. By using the observations only on the slow component, the syste...
Tangent space estimation for smooth embeddings of Riemannian manifolds
Riemannian manifolds tangent space estimation manifold sampling manifold learning Chernoff bounds for sums of random matrices singular value perturbation.
2012/9/17
Numerous dimensionality reduction problems in data analysis involve the recovery of low-dimensional models or the learning of manifolds underlying sets of data. Many manifold learning methods require ...
k-Nearest neighbor density estimation on Riemannian Manifolds
Asymptotic results Density estimation Meteorological applications
2011/7/6
In this paper, we consider a k-nearest neighbor kernel type estimator when the random variables belong in a Riemannian manifolds.
Behavior of Graph Laplacians on Manifolds with Boundary
Graph Laplacians Behavior Manifolds Boundary
2011/6/21
In manifold learning, algorithms based on graph Laplacians constructed from data have received
considerable attention both in practical applications and theoretical analysis. In particular, the
conv...
Concentration Inequalities and Confidence Bands for Needlet Density Estimators on Compact Homogeneous Manifolds
Concentration Inequalities Confidence Bands Density Estimators
2011/3/21
Let $X_1,...,X_n$ be a random sample from some unknown probability density $f$ defined on a compact homogeneous manifold $\mathbf M$ of dimension $d \ge 1$. Consider a 'needlet frame' $\{\phi_{j \eta}...
Partially linear models on Riemannian manifolds
Nonparametric estimation Partly linear models Riemannian manifolds
2010/3/11
In partially linear models the dependence of the response y on (xt, t) is modeled through the relationship
y = xt +g(t)+" where " is independent of (xt, t). In this paper, estimators of g are constr...
Learning gradients on manifolds
classification feature selection manifold learning regression shrinkage estimator Tikhonov regularization
2010/3/10
A common belief in high-dimensional data analysis is that data are concentrated on a lowdimensional
manifold. This motivates simultaneous dimension reduction and regression on manifolds.
We provide ...
Time dependent Malliavin calculus on manifolds and application to nonlinear filtering
Time dependent Malliavin calculus application to nonlinear filtering
2009/9/22
In this paper, we prove, using Malliavin calculus, that
under a global Hormander condition the law of a Riemannian manifold
valued stochastic process, a solution of a stochastic differential
equati...