Tensor Embedding Methods

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 image/video retrieval. However, although the data in these applications are more naturally represented as higher-order tensors, the embedding methods can only work with vectorized data representations which may not capture well some useful information in the original data. Moreover, highdimensional vectorized representations also suffer from the curse of dimensionality and the high computational demand. In this paper, we propose some novel tensor embedding methods which, unlike previous methods, take data directly in the form of tensors of arbitrary order as input. These methods allow the relation...

• Type: Conference
• Year: 2006
• Where: AAAI
• Authors: Guang Dai, Dit-Yan Yeung
• Keywords: AAAI 2006, Embedding Methods, Intelligent Agents, Local Discriminant Embedding, Tensor Embedding Methods