Suhas Gundimeda

2 accepted papers

2024

Unsupervised Change Point Detection in Multivariate Time Series

Daoping Wu, Suhas Gundimeda, Shaoshuai Mou, Christopher Quinn

AISTATS 2024poster

We consider the challenging problem of unsupervised change point detection in multivariate time series when the number of change points is unknown. Our method eliminates the user’s need for careful parameter tuning, enhancing its practicality and usability. Our approach identifies time series segmen…

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2020

Modeling Piece-Wise Stationary Time Series

Daoping Wu, Suhas Gundimeda, Shaoshuai Mou, Christopher J. Quinn

ICASSP 2020accepted

We consider the problem of modeling piece-wise stationary time series. We propose a new, data-driven technique to automatically identify change-points and learn piece-wise stationary models. We do not assume prior knowledge of the stationary models or the number of change points. Our method can auto…

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