Dimensionality reduction plays an important role in many machine learning and pattern recognition tasks. In this paper, we present a novel dimensionality reduction algorithm called multilinear maximum distance embedding (MDE), which includes three key components. To preserve the local geometry and discriminant information in the embedded space, MDE utilizes a new objective function, which aims ...

Linearization of graph embedding has been emerged as an effective dimensionality reduction technique in pattern recognition. However, it may not be optimal for nonlinearly distributed real world data, such as face, due to its linear nature. So, a kernelization of graph embedding is proposed as a dimensionality reduction technique in face recognition. In order to further boost the recognition ca...

The double-rooted complete binary tree is a complete binary tree where the path (of length ) between the children of the root is replaced by a path of length . It is folklore that the double-rooted complete binary tree is a spanning tree of the hypercube of the same size. Unfortunately, the usual construction of an embedding of a double-rooted complete binary tree into the hypercube does not pr...

The task of dimensionality reduction for regression (DRR) is to find a low dimensional representation z ∈ R of the input covariates x ∈ R, with q p, for regressing the output y ∈ R. DRR can be beneficial for visualization of high dimensional data, efficient regressor design with a reduced input dimension, but also when eliminating noise in data x through uncovering the essential information z f...

It is folklore that the double-rooted complete binary tree is a spanning tree of the hypercube of the same size. Unfortunately, the usual construction of an embedding of a double-rooted complete binary tree into a hypercube does not provide any hint on how this embedding can be extended if each leaf spawns two new leaves. In this paper, we present simple dynamic embeddings of double-rooted comp...

Double-tree-scan (DTS) is a new scan-path architecture that is deemed to be suitable for low-power testing of VLSI circuits. A full DTS resembles two complete k-level (k > 0) binary trees whose leaf nodes are merged pair-wise, and thus consists of exactly Nk = 3× 2 − 2 nodes. In this paper, the problem of planar straight-line embedding of a “double-tree graph” on a rectangular grid is investiga...

Over the past few years, some embedding methods have been proposed for feature extraction and dimensionality reduction in various machine learning and pattern classification tasks. Among the methods proposed are Neighborhood Preserving Embedding (NPE), Locality Preserving Projection (LPP) and Local Discriminant Embedding (LDE) which have been used in such applications as face recognition and im...

Objectives: To perform aspect extraction for opinion mining of learner comments in the online teaching-learning scenario. Methods : A machine learning model is developed extraction. The authors collected dataset consisting around 5000 from Coursera and performed analysis on dataset. validate results, standard SemEval2014 used. Findings: For both contextualised non word embeddings, compiled resu...

A new algorithm is proposed for the construction of BrezingWeng-like elliptic curves such that polynomials defining the CM discriminant are linear. Using this construction, new families of curves with variable discriminants and embedding degrees of k ∈ {8, 16, 20, 24}, which were not covered by Freeman, Scott, and Teske [9], are presented. Our result is useful for constructing elliptic curves w...