Fast detection of multiple change-points shared by many signals using group LARS
Part of: Advances in Neural Information Processing Systems 23 (NIPS 2010)
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Abstract
We present a fast algorithm for the detection of multiple change-points when each is frequently shared by members of a set of co-occurring one-dimensional signals. We give conditions on consistency of the method when the number of signals increases, and provide empirical evidence to support the consistency results.