Trevor Campbell
Postdoctoral Associate
CSAIL MIT

Research Areas


Preprints

  • Automated scalable Bayesian inference via Hilbert coresets
    T. Campbell and T. Broderick
  • Exchangeable trait allocations
    T. Campbell, D. Cai, and T. Broderick
  • Truncated random measures
    T. Campbell, J. Huggins, J. P. How, and T. Broderick
  • Dynamic clustering algorithms via small-variance analysis of Markov chain mixture models
    T. Campbell, B. Kulis, and J. P. How

Publications

  • Efficient global point cloud alignment using Bayesian nonparametric mixtures
    J. Straub, T. Campbell, J. P. How, and J. W. Fisher III
    IEEE Conference on Computer Vision and Pattern Recognition, 2017
  • Coresets for scalable Bayesian logistic regression
    J. Huggins, T. Campbell, and T. Broderick
    Advances in Neural Information Processing Systems, 2016
  • Edge-exchangeable graphs and sparsity
    D. Cai, T. Campbell, and T. Broderick
    Advances in Neural Information Processing Systems, 2016
  • Streaming, distributed variational inference for Bayesian nonparametrics
    T. Campbell, J. Straub, J. W. Fisher III, and J. P. How
    Advances in Neural Information Processing Systems, 2015
  • Small-variance nonparametric clustering on the hypersphere
    J. Straub, T. Campbell, J. P. How, and J. W. Fisher III
    IEEE Conference on Computer Vision and Pattern Recognition, 2015
  • Bayesian nonparametric set construction for robust optimization
    T. Campbell and J. P. How
    American Control Conference, 2015
  • Approximate decentralized Bayesian inference
    T. Campbell and J. P. How
    Uncertainty in Artificial Intelligence, 2014
  • Dynamic clustering via asymptotics of the dependent Dirichlet process mixture
    T. Campbell, M. Liu, B. Kulis, J. P. How, and L. Carin
    Advances in Neural Information Processing Systems, 2013
  • Multiagent allocation of Markov decision process tasks
    T. Campbell, L. Johnson, and J. P. How
    American Control Conference, 2013
  • Simultaneous clustering on representation expansion for learning multimodel MDPs
    T. Campbell, R. H. Klein, A. Geramifard, and J. P. How
    Reinforcement Learning and Decision Making, 2013
  • Truncated Bayesian nonparametrics
    Ph.D. thesis
    Massachusetts Institute of Technology, 2016
  • Multiagent planning with Bayesian nonparametric asymptotics
    Master's thesis
    Massachusetts Institute of Technology, 2013