Constraints on the Neighborhood Size in LLE

LLE with low-dimensional neighborhood representation

The local linear embedding algorithm (LLE) is a non-linear dimension-reducing technique, widely used due to its computational simplicity and intuitive approach. LLE first linearly reconstructs each input point from its nearest neighbors and then preserves these neighborhood relations in the low-dimensional embedding. We show that the reconstruction weights computed by LLE capture the high-dimen...

An Adaptive Neighborhood Graph for LLE Algorithm without Free-Parameter

Locally Linear Embedding (LLE) algorithm is the first classic nonlinear manifold learning algorithm based on the local structure information about the data set, which aims at finding the low-dimension intrinsic structure lie in high dimensional data space for the purpose of dimensionality reduction. One deficiency appeared in this algorithm is that it requires users to give a free parameter k w...

Reconstruction of binary matrices under fixed size neighborhood constraints

Using a dynamic programming approach, we prove that a large variety of matrix reconstruction problems from two projections can be solved in polynomial timewhenever the number of rows (or columns) is fixed. We also prove some complexity results for several problems concerning the reconstruction of a binary matrix when a neighborhood constraint occurs. © 2008 Elsevier B.V. All rights reserved.

the impact of e-readiness on ec success in public sector in iran the impact of e-readiness on ec success in public sector in iran

acknowledge the importance of e-commerce to their countries and to survival of their businesses and in creating and encouraging an atmosphere for the wide adoption and success of e-commerce in the long term. the investment for implementing e-commerce in the public sector is one of the areas which is focused in government‘s action plan for cross-disciplinary it development and e-readiness in go...

LLE Review . , LLE Quarterly Report