Loading patent…
AssigneeJohnson & Johnson Pharmaceutical Reseach & Develpment, L.L.C.
InventorsDimitris K. Agrafiotis, Victor S. Lobanov, Francis R. Salemme
Estimating the term…
A method, system and computer program product are provided for scaling, or dimensionally reducing, multi-dimensional data sets that scale well for large data sets. The invention scales multi-dimensional data sets by determining one or more non-linear functions between a sample of points from the multi-dimensional data set and a corresponding set of dimensionally reduced points. Thereafter, these one or more non-linear functions are used to non-linearly map additional points. The additional points may be members of the original multi-dimensional data set or may be new, previously unseen points. In an embodiment, the determination of the non-linear relationship between the sample of points from the multi-dimensional data set and the corresponding set of dimensionally reduced points is performed by a self-learning system such as a neural network. The additional points are mapped using the self-learning system in a feed-forward/predictive manner.
A method for mapping large multi-dimensional data sets from an N-dimensional space to an M-dimensional space, wherein N is greater than M, comprising:
A method for representing relationships between objects as distances from one another on a display map, comprising:
A system for representing relationships between objects in a set of objects as distances from one another on a display map, comprising:
Dependencies are inferred from the claim text.
Drawings are temporarily unavailable. Open the PDF at USPTO
From the US filing history. Foreign family members aren’t listed.
Backward citations are indexed for grants only.
Function evaluation by approximation methods, e.g. inter- or extrapolation, smoothing, least mean square method: of multidimensional data
Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods: based on criteria of topology…
Computing and data processing
Term end not estimated
1. Field of the Invention
The present invention relates to scaling of multi-dimensional data sets and, more particularly, to non-linear mapping of a sample of points from a multi-dimensional data set, determining one or more non-linear functions for the mapped sample of points, and mapping additional points using the one or more non-linear functions, including mapping members of the original multi-dimensional data set and mapping new and previously unseen points.
2. Related Art
The present invention will be described with reference to the accompanying drawings, wherein:
FIG. 1A illustrates a lateral view of a face data set;
FIG. 1B illustrates a frontal view of the face data set;
In the drawings, like reference numbers indicate identical or functionally similar elements. Also, the leftmost digit(s) of the reference numbers identify the drawings in which the associated elements are first introduced.
I. Non-Linear Mapping Networks
A. Introduction