Skip to search formSkip to main content
You are currently offline. Some features of the site may not work correctly.

Gramian matrix

Known as: Grammian, Gram determinant, Gramian 
In linear algebra, the Gram matrix (Gramian matrix or Gramian) of a set of vectors in an inner product space is the Hermitian matrix of inner… Expand
Wikipedia

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2019
Highly Cited
2019
Gradient descent finds a global minimum in training deep neural networks despite the objective function being non-convex. The… Expand
Highly Cited
2014
Highly Cited
2014
Modeling the target appearance is critical in many modern visual tracking algorithms. Many tracking-by-detection algorithms… Expand
  • figure 1
  • figure 2
  • figure 3
  • table 1
  • table 2
Highly Cited
2007
Highly Cited
2007
This paper presents a semi-supervised graph-based method for the classification of hyperspectral images. The method is designed… Expand
  • figure 1
  • figure 2
  • table I
  • figure 3
  • table II
Highly Cited
2005
Highly Cited
2005
A problem for many kernel-based methods is that the amount of computation required to find the solution scales as O(n 3 ), where… Expand
Highly Cited
2005
Highly Cited
2005
  • C. Rowley
  • Int. J. Bifurc. Chaos
  • 2005
  • Corpus ID: 9272678
Many of the tools of dynamical systems and control theory have gone largely unused for fluids, because the governing equations… Expand
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • figure 5
Highly Cited
2004
Highly Cited
2004
Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among… Expand
  • table 1
  • table 2
  • table 3
  • table 4
Highly Cited
2002
Highly Cited
2002
In this paper, we introduce a new method of model reduction for nonlinear control systems. Our approach is to construct an… Expand
  • figure 1
  • figure 2
  • figure 3
  • figure 4
Highly Cited
2001
Highly Cited
2001
The popular K-means clustering partitions a data set by minimizing a sum-of-squares cost function. A coordinate descend method is… Expand
  • figure 1
  • table 1
  • table 2
Highly Cited
1984
Highly Cited
1984
  • D. Enns
  • The 23rd IEEE Conference on Decision and Control
  • 1984
  • Corpus ID: 38786395
An error bound for reduced order models obtained from internally balanced realizations is derived. The bound is that the infinity… Expand
  • figure 1
  • figure 3
  • figure 4
  • figure 5
  • figure 6
Highly Cited
1960
Highly Cited
1960
THIS is one of the two ground-breaking papers by Kalman that appeared in 1960—with the other one (discussed next) being the… Expand