@inproceedings{d09adc5cb5c94c50b60099104e9e8111,
title = "QUIC-SVD: Fast SVD using cosine trees",
abstract = "The Singular Value Decomposition is a key operation in many machine learning methods. Its computational cost, however, makes it unscalable and impractical for applications involving large datasets or real-time responsiveness, which are becoming increasingly common. We present a new method, QUIC-SVD, for fast approximation of the whole-matrix SVD based on a new sampling mechanism called the cosine tree. Our empirical tests show speedups of several orders of magnitude over exact SVD. Such scalability should enable QUIC-SVD to accelerate and enable a wide array of SVD-based methods and applications.",
author = "Holmes, \{Michael P.\} and Gray, \{Alexander G.\} and \{Lee Isbell\}, Charles",
year = "2009",
language = "English (US)",
isbn = "9781605609492",
series = "Advances in Neural Information Processing Systems 21 - Proceedings of the 2008 Conference",
publisher = "Neural Information Processing Systems",
pages = "673--680",
booktitle = "Advances in Neural Information Processing Systems 21 - Proceedings of the 2008 Conference",
note = "22nd Annual Conference on Neural Information Processing Systems, NIPS 2008 ; Conference date: 08-12-2008 Through 11-12-2008",
}