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Published in:
2010 | OriginalPaper | Chapter
Novel Alternating Least Squares Algorithm for Nonnegative Matrix and Tensor Factorizations
Authors : Anh Huy Phan, Andrzej Cichocki, Rafal Zdunek, Thanh Vu Dinh
Published in: Neural Information Processing. Theory and Algorithms
Publisher: Springer Berlin Heidelberg
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Alternative least squares (ALS) algorithm is considered as a “work-horse” algorithm for general tensor factorizations. For nonnegative tensor factorizations (NTF), we usually use a nonlinear projection (rectifier) to remove negative entries during the iteration process. However, this kind of ALS algorithm often fails and cannot converge to the desired solution. In this paper, we proposed a novel algorithm for NTF by recursively solving nonnegative quadratic programming problems. The validity and high performance of the proposed algorithm has been confirmed for difficult benchmarks, and also in an application of object classification.