Research Projects

Streaming, Distributed, Asynchronous Inference

Merging Bayesian nonparametric posteriors with bipartite matching

[Paper] [Slides] [Poster]

Merging symmetric posteriors with combinatorial optimization

[Paper] [Slides] [Poster] [MIT News Feature] [Popular Science]

Low-Variance Dynamic Bayesian Nonparametrics

Tractable Markov dependent Dirichlet process MAP approximation

[Paper] [Slides] [Poster] [Code]

Dynamic von-Mises-Fisher mixtures for robotic perception

[Paper] [Slides] [Poster] [Code] [Video]

Bayesian Nonparametric Theory

Sequential representations, error bounds and sampling algorithms for truncated random measures

[Paper]

Optimization with Bayesian Nonparametrics

Efficient globally optimal point cloud alignment

[Paper]

Tractable nonconvex uncertainty sets via the Dirichlet process mixture

[Paper] [Slides]

Publications

Published

  • 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.
    [NIPS] [Supplement] [arXiv] [BibTeX]
    @inproceedings{Campbell15_NIPS,
    	author={Trevor Campbell and Julian Straub and John W.~Fisher III, and Jonathan P.~How},
    	title={Streaming, Distributed Variational Inference for Bayesian Nonparametrics},
    	year={2015},
    	booktitle={Advances in Neural Information Processing Systems}
    }
    
  • 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.
    [CVPR] [Supplement] [BibTeX]
    @inproceedings{Straub15_CVPR,
    	author = {Julian Straub and Trevor Campbell and Jonathan P.~How, and John W.~Fisher III},
    	title = {Small-Variance Nonparametric Clustering on the Hypersphere},
    	year = {2015},
    	booktitle = {IEEE Conference on Computer Vision and Pattern Recognition}
    }
    
  • Bayesian Nonparametric Set Construction for Robust Optimization.
    T. Campbell and J. P. How.
    American Control Conference, 2015.
    [IEEE Explore] [BibTeX]
    @inproceedings{Campbell15_ACC,
    	author = {Trevor Campbell and Jonathan P.~How},
    	title = {Bayesian Nonparametric Set Construction for Robust Optimization},
    	year = {2015},
    	booktitle = {American Controls Conference}
    }
    
  • Approximate Decentralized Bayesian Inference.
    T. Campbell and J. P. How.
    Uncertainty in Artificial Intelligence, 2014.
    [UAI] [arXiv] [BibTeX]
    @inproceedings{Campbell14_UAI,
    	author = {Trevor Campbell and Jonathan P.~How},
    	title = {Approximate Decentralized Bayesian Inference},
    	year = {2014},
    	booktitle = {Uncertainty in Artificial Intelligence}
    }
    
  • Dynamic Clustering via Asymptotics of the Dependent Dirichlet Process Mixture.
    T. Campbell, M. Liu, B. Kulis, L. Carin, and J. P. How.
    Advances in Neural Information Processing Systems, 2013.
    [NIPS] [arXiv] [BibTeX]
    @inproceedings{Campbell13_NIPS,
    	author = {Trevor Campbell and Miao Liu and Brian Kulis and Jonathan P.~How and Lawrence Carin},
    	title = {Dynamic Clustering via Asymptotics of the Dependent Dirichlet Process Mixture},
    	year = {2013},
    	booktitle = {Advances in Neural Information Processing Systems}
    }
    
  • Multiagent Allocation of Markov Decision Process Tasks.
    T. Campbell, L. Johnson, and J. P. How.
    American Control Conference, 2013.
    [IEEE Explore] [BibTeX]
    @inproceedings{Campbell13_ACC,
    	author = {Trevor Campbell and Luke Johnson and Jonathan P.~How},
    	title = {Multiagent Allocation of Markov Decision Process Tasks},
    	year = {2013},
    	booktitle = {American Controls Conference}
    }
    
  • 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.
    [PDF] [RLDM] [BibTeX]
    @inproceedings{Campbell13_RLDM,
    	author = {Trevor Campbell and Robert Klein and Alborz Geramifard and Jonathan P.~How},
    	title = {Simultaneous Clustering on Representation Expansion for Learning Multimodel MDPs},
    	year = {2013},
    	booktitle = {Reinforcement Learning and Decision Making}
    }
    

Preprints

  • Truncated Random Measures.
    T. Campbell*, J. Huggins*, J. P. How, and T. Broderick.
    [arXiv]
  • Efficient Globally Optimal Point Cloud Alignment using Bayesian Nonparametric Mixtures.
    J. Straub*, T. Campbell*, J. P. How, and J. W. Fisher III.
    [arXiv]
  • Dynamic Clustering Algorithms via Small-Variance Analysis of the Markov Dependent Dirichlet Process.
    T. Campbell, B. Kulis, and J. P. How.