Dimensionality reduction via discretization

Improving Efficiency of Density-Based Shape Descriptors for 3D Object Retrieval

We consider 3D shape description as a probability modeling problem. The local surface properties are first measured via various features, and then the probability density function (pdf) of the multidimensional feature vector becomes the shape descriptor. Our prior work has shown that, for 3D object retrieval, pdf-based schemes can provide descriptors that are computationally efficient and perfo...

Dimension Reduction , Discretization and Diffusion on Compact Sets

Dimensionality reduction in the Geostatistical approach for Hydraulic Tomography

The implementation of geostatistical approach to solve inverse problems [8], such as estimating hydraulic conductivity from measurements of head, is expensive for problems discretized on fine grids. Dimensionality reduction techniques such as representing the random field via Karhunen-Loève expansion, are frequently used in such a context. We show how to combine an efficient method to compute t...

A sparse grid based method for generative dimensionality reduction of high-dimensional data

Generative dimensionality reduction methods play an important role in machine learning applications because they construct an explicit mapping from a lowdimensional space to the high-dimensional data space. We discuss a general framework to describe generative dimensionality reduction methods, where the main focus lies on a regularized principal manifold learning variant. Since most generative ...

Diagnosis of Diabetes Using an Intelligent Approach Based on Bi-Level Dimensionality Reduction and Classification Algorithms

Objective: Diabetes is one of the most common metabolic diseases. Earlier diagnosis of diabetes and treatment of hyperglycemia and related metabolic abnormalities is of vital importance. Diagnosis of diabetes via proper interpretation of the diabetes data is an important classification problem. Classification systems help the clinicians to predict the risk factors that cause the diabetes or pre...