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Creators/Authors contains: "Reddy, Aravind"

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  1. ; ; (, Advances in neural information processing systems)
    Accepted Manuscript Full Text Available
  2. ; ; (, Advances in neural information processing systems)
    In this paper, we study k-means++ and k-means++ parallel, the two most popular algorithms for the classic k-means clustering problem. We provide novel analyses and show improved approximation and bi-criteria approximation guarantees for k-means++ and k-means++ parallel. Our results give a better theoretical justification for why these algorithms perform extremely well in practice. We also propose a new variant of k-means++ parallel algorithm (Exponential Race k-means++) that has the same approximation guarantees as k-means++. 
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    Accepted Manuscript Full Text Available
  3. ; ; ; (, Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR)
    null (Ed.)
    Accepted Manuscript Full Text Available
  4. ; ; ; (, Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR)
    null (Ed.)
    Accepted Manuscript Full Text Available