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Yee Whye Teh: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Yee Whye Teh
    A Hierarchical Bayesian Language Model Based On Pitman-Yor Processes. [Citation Graph (0, 0)][DBLP]
    ACL, 2006, pp:- [Conf]
  2. Fahiem Bacchus, Yee Whye Teh
    Making Forward Chaining Relevant. [Citation Graph (0, 0)][DBLP]
    AIPS, 1998, pp:54-61 [Conf]
  3. Tamara L. Berg, Alexander C. Berg, Jaety Edwards, Michael Maire, Ryan White, Yee Whye Teh, Erik G. Learned-Miller, David A. Forsyth
    Names and Faces in the News. [Citation Graph (0, 0)][DBLP]
    CVPR (2), 2004, pp:848-854 [Conf]
  4. Sham Kakade, Yee Whye Teh, Sam T. Roweis
    An Alternate Objective Function for Markovian Fields. [Citation Graph (0, 0)][DBLP]
    ICML, 2002, pp:275-282 [Conf]
  5. Max Welling, Michal Rosen-Zvi, Yee Whye Teh
    Approximate inference by Markov chains on union spaces. [Citation Graph (0, 0)][DBLP]
    ICML, 2004, pp:- [Conf]
  6. Eric P. Xing, Kyung-Ah Sohn, Michael I. Jordan, Yee Whye Teh
    Bayesian multi-population haplotype inference via a hierarchical dirichlet process mixture. [Citation Graph (0, 0)][DBLP]
    ICML, 2006, pp:1049-1056 [Conf]
  7. Kenichi Kurihara, Max Welling, Yee Whye Teh
    Collapsed Variational Dirichlet Process Mixture Models. [Citation Graph (0, 0)][DBLP]
    IJCAI, 2007, pp:2796-2801 [Conf]
  8. Jaety Edwards, Yee Whye Teh, David A. Forsyth, Roger Bock, Michael Maire, Grace Vesom
    Making Latin Manuscripts Searchable using gHMMs. [Citation Graph (0, 0)][DBLP]
    NIPS, 2004, pp:- [Conf]
  9. Geoffrey E. Hinton, Zoubin Ghahramani, Yee Whye Teh
    Learning to Parse Images. [Citation Graph (0, 0)][DBLP]
    NIPS, 1999, pp:463-469 [Conf]
  10. Yee Whye Teh, Geoffrey E. Hinton
    Rate-coded Restricted Boltzmann Machines for Face Recognition. [Citation Graph (0, 0)][DBLP]
    NIPS, 2000, pp:908-914 [Conf]
  11. Yee Whye Teh, Michael I. Jordan, Matthew J. Beal, David M. Blei
    Sharing Clusters among Related Groups: Hierarchical Dirichlet Processes. [Citation Graph (0, 0)][DBLP]
    NIPS, 2004, pp:- [Conf]
  12. Yee Whye Teh, Sam T. Roweis
    Automatic Alignment of Local Representations. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:841-848 [Conf]
  13. Yee Whye Teh, Max Welling
    The Unified Propagation and Scaling Algorithm. [Citation Graph (0, 0)][DBLP]
    NIPS, 2001, pp:953-960 [Conf]
  14. Max Welling, Yee Whye Teh
    Linear Response for Approximate Inference. [Citation Graph (0, 0)][DBLP]
    NIPS, 2003, pp:- [Conf]
  15. Geoffrey E. Hinton, Yee Whye Teh
    Discovering Multiple Constraints that are Frequently Approximately Satisfied. [Citation Graph (0, 0)][DBLP]
    UAI, 2001, pp:227-234 [Conf]
  16. Max Welling, Yee Whye Teh
    Belief Optimization for Binary Networks: A Stable Alternative to Loopy Belief Propagation. [Citation Graph (0, 0)][DBLP]
    UAI, 2001, pp:554-561 [Conf]
  17. Max Welling, Yee Whye Teh
    Approximate inference in Boltzmann machines. [Citation Graph (0, 0)][DBLP]
    Artif. Intell., 2003, v:143, n:1, pp:19-50 [Journal]
  18. Yee Whye Teh, Max Welling, Simon Osindero, Geoffrey E. Hinton
    Energy-Based Models for Sparse Overcomplete Representations. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2003, v:4, n:, pp:1235-1260 [Journal]
  19. Geoffrey E. Hinton, Simon Osindero, Yee Whye Teh
    A Fast Learning Algorithm for Deep Belief Nets. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2006, v:18, n:7, pp:1527-1554 [Journal]
  20. Max Welling, Yee Whye Teh
    Linear Response Algorithms for Approximate Inference in Graphical Models. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2004, v:16, n:1, pp:197-221 [Journal]
  21. Yee Whye Teh, David Newman, Max Welling
    A Collapsed Variational Bayesian Inference Algorithm for Latent Dirichlet Allocation. [Citation Graph (0, 0)][DBLP]
    NIPS, 2006, pp:1353-1360 [Conf]
  22. Max Welling, Thomas P. Minka, Yee Whye Teh
    Structured Region Graphs: Morphing EP into GBP. [Citation Graph (0, 0)][DBLP]
    UAI, 2005, pp:609-614 [Conf]

  23. Lossless Compression Based on the Sequence Memoizer. [Citation Graph (, )][DBLP]


  24. Beam sampling for the infinite hidden Markov model. [Citation Graph (, )][DBLP]


  25. A stochastic memoizer for sequence data. [Citation Graph (, )][DBLP]


  26. Hierarchical Dirichlet Trees for Information Retrieval. [Citation Graph (, )][DBLP]


  27. Collapsed Variational Inference for HDP. [Citation Graph (, )][DBLP]


  28. Cooled and Relaxed Survey Propagation for MRFs. [Citation Graph (, )][DBLP]


  29. Bayesian Agglomerative Clustering with Coalescents. [Citation Graph (, )][DBLP]


  30. Dependent Dirichlet Process Spike Sorting. [Citation Graph (, )][DBLP]


  31. The Infinite Factorial Hidden Markov Model. [Citation Graph (, )][DBLP]


  32. An Efficient Sequential Monte Carlo Algorithm for Coalescent Clustering. [Citation Graph (, )][DBLP]


  33. A mixture model for the evolution of gene expression in non-homogeneous datasets. [Citation Graph (, )][DBLP]


  34. The Mondrian Process. [Citation Graph (, )][DBLP]


  35. Hybrid Variational/Gibbs Collapsed Inference in Topic Models. [Citation Graph (, )][DBLP]


  36. Improving Word Sense Disambiguation Using Topic Features. [Citation Graph (, )][DBLP]


  37. Mixed Cumulative Distribution Networks [Citation Graph (, )][DBLP]


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