2010
NeurIPS
NeurIPS 2010
Fast detection of multiple change-points shared by many signals using group LARS
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.
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Interdisciplinary Bridge
- Artificial Intelligence and Data Science & Analytics and Mathematics & Optimization
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Trend Setter
- Regression
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Hot Topic Early Bird
- optimization algorithm
Authors
Topics
Machine Learning > Core Methods > Clustering
Machine Learning > Core Methods > Regression
Machine Learning > Optimization & Theory > Optimization
Data Science & Analytics > Methods > Time Series Analysis
Mathematics & Optimization > Optimization > Continuous Optimization
Machine Learning > Core Methods > Dimensionality Reduction
Mathematics & Optimization > Statistics
Mathematics & Optimization > Optimization > Sparse Optimization
Machine Learning > Learning Types > Sparse Learning
Deep Learning > Learning Types > Regression
Machine Learning > Learning Types > Time Series Analysis