Publications [#338762] of Lawrence Carin

Papers Published

1. Campbell, T; Liu, M; Kulis, B; How, JP; Carin, L, Dynamic clustering via asymptotics of the dependent Dirichlet process mixture, Advances in Neural Information Processing Systems (January, 2013)
   (last updated on 2024/12/31)

   Abstract:
   This paper presents a novel algorithm, based upon the dependent Dirichlet process mixture model (DDPMM), for clustering batch-sequential data containing an unknown number of evolving clusters. The algorithm is derived via a lowvariance asymptotic analysis of the Gibbs sampling algorithm for the DDPMM, and provides a hard clustering with convergence guarantees similar to those of the k-means algorithm. Empirical results from a synthetic test with moving Gaussian clusters and a test with real ADS-B aircraft trajectory data demonstrate that the algorithm requires orders of magnitude less computational time than contemporary probabilistic and hard clustering algorithms, while providing higher accuracy on the examined datasets.