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Zoubin Ghahramani: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Zoubin Ghahramani
    Unsupervised Learning. [Citation Graph (0, 0)][DBLP]
    Advanced Lectures on Machine Learning, 2003, pp:72-112 [Conf]
  2. Arik Azran, Zoubin Ghahramani
    Spectral Methods for Automatic Multiscale Data Clustering. [Citation Graph (0, 0)][DBLP]
    CVPR (1), 2006, pp:190-197 [Conf]
  3. Katherine A. Heller, Zoubin Ghahramani
    A Simple Bayesian Framework for Content-Based Image Retrieval. [Citation Graph (0, 0)][DBLP]
    CVPR (2), 2006, pp:2110-2117 [Conf]
  4. JaeMo Sung, Sung Yang Bang, Seungjin Choi, Zoubin Ghahramani
    U-Likelihood and U-Updating Algorithms: Statistical Inference in Latent Variable Models. [Citation Graph (0, 0)][DBLP]
    ECML, 2005, pp:377-388 [Conf]
  5. Wei Chu, Zoubin Ghahramani, David L. Wild
    Protein secondary structure prediction using sigmoid belief networks to parameterize segmental semi-Markov models. [Citation Graph (0, 0)][DBLP]
    ESANN, 2004, pp:81-86 [Conf]
  6. Arik Azran, Zoubin Ghahramani
    A new approach to data driven clustering. [Citation Graph (0, 0)][DBLP]
    ICML, 2006, pp:57-64 [Conf]
  7. Wei Chu, Zoubin Ghahramani
    Preference learning with Gaussian processes. [Citation Graph (0, 0)][DBLP]
    ICML, 2005, pp:137-144 [Conf]
  8. Wei Chu, Zoubin Ghahramani, David L. Wild
    A graphical model for protein secondary structure prediction. [Citation Graph (0, 0)][DBLP]
    ICML, 2004, pp:- [Conf]
  9. Katherine A. Heller, Zoubin Ghahramani
    Bayesian hierarchical clustering. [Citation Graph (0, 0)][DBLP]
    ICML, 2005, pp:297-304 [Conf]
  10. Yuan (Alan) Qi, Thomas P. Minka, Rosalind W. Picard, Zoubin Ghahramani
    Predictive automatic relevance determination by expectation propagation. [Citation Graph (0, 0)][DBLP]
    ICML, 2004, pp:- [Conf]
  11. Ruslan Salakhutdinov, Sam T. Roweis, Zoubin Ghahramani
    Optimization with EM and Expectation-Conjugate-Gradient. [Citation Graph (0, 0)][DBLP]
    ICML, 2003, pp:672-679 [Conf]
  12. Edward Snelson, Zoubin Ghahramani
    Compact approximations to Bayesian predictive distributions. [Citation Graph (0, 0)][DBLP]
    ICML, 2005, pp:840-847 [Conf]
  13. Xiaojin Zhu, Zoubin Ghahramani, John D. Lafferty
    Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions. [Citation Graph (0, 0)][DBLP]
    ICML, 2003, pp:912-919 [Conf]
  14. Nicholas J. Adams, Amos J. Storkey, Christopher K. I. Williams, Zoubin Ghahramani
    MFDTs: Mean Field Dynamic Trees. [Citation Graph (0, 0)][DBLP]
    ICPR, 2000, pp:3151-3154 [Conf]
  15. Matthew J. Beal, Zoubin Ghahramani, Carl Edward Rasmussen
    The Infinite Hidden Markov Model. [Citation Graph (0, 0)][DBLP]
    NIPS, 2001, pp:577-584 [Conf]
  16. David A. Cohn, Zoubin Ghahramani, Michael I. Jordan
    Active Learning with Statistical Models. [Citation Graph (0, 0)][DBLP]
    NIPS, 1994, pp:705-712 [Conf]
  17. Zoubin Ghahramani
    Factorial Learning and the EM Algorithm. [Citation Graph (0, 0)][DBLP]
    NIPS, 1994, pp:617-624 [Conf]
  18. Zoubin Ghahramani, Matthew J. Beal
    Propagation Algorithms for Variational Bayesian Learning. [Citation Graph (0, 0)][DBLP]
    NIPS, 2000, pp:507-513 [Conf]
  19. Zoubin Ghahramani, Matthew J. Beal
    Variational Inference for Bayesian Mixtures of Factor Analysers. [Citation Graph (0, 0)][DBLP]
    NIPS, 1999, pp:449-455 [Conf]
  20. Zoubin Ghahramani, Katherine A. Heller
    Bayesian Sets. [Citation Graph (0, 0)][DBLP]
    NIPS, 2005, pp:- [Conf]
  21. Zoubin Ghahramani, Geoffrey E. Hinton
    Hierarchical Non-linear Factor Analysis and Topographic Maps. [Citation Graph (0, 0)][DBLP]
    NIPS, 1997, pp:- [Conf]
  22. Zoubin Ghahramani, Michael I. Jordan
    Supervised learning from incomplete data via an EM approach. [Citation Graph (0, 0)][DBLP]
    NIPS, 1993, pp:120-127 [Conf]
  23. Zoubin Ghahramani, Michael I. Jordan
    Factorial Hidden Markov Models. [Citation Graph (0, 0)][DBLP]
    NIPS, 1995, pp:472-478 [Conf]
  24. Zoubin Ghahramani, Sam T. Roweis
    Learning Nonlinear Dynamical Systems Using an EM Algorithm. [Citation Graph (0, 0)][DBLP]
    NIPS, 1998, pp:431-437 [Conf]
  25. Zoubin Ghahramani, Daniel M. Wolpert, Michael I. Jordan
    Computational Structure of coordinate transformations: A generalization study. [Citation Graph (0, 0)][DBLP]
    NIPS, 1994, pp:1125-1132 [Conf]
  26. Tom Griffiths, Zoubin Ghahramani
    Infinite latent feature models and the Indian buffet process. [Citation Graph (0, 0)][DBLP]
    NIPS, 2005, pp:- [Conf]
  27. Geoffrey E. Hinton, Zoubin Ghahramani, Yee Whye Teh
    Learning to Parse Images. [Citation Graph (0, 0)][DBLP]
    NIPS, 1999, pp:463-469 [Conf]
  28. Rong Jin, Zoubin Ghahramani
    Learning with Multiple Labels. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:897-904 [Conf]
  29. Michael I. Jordan, Zoubin Ghahramani, Lawrence K. Saul
    Hidden Markov Decision Trees. [Citation Graph (0, 0)][DBLP]
    NIPS, 1996, pp:501-507 [Conf]
  30. Iain Murray, David MacKay, Zoubin Ghahramani, John Skilling
    Nested sampling for Potts models. [Citation Graph (0, 0)][DBLP]
    NIPS, 2005, pp:- [Conf]
  31. Carl Edward Rasmussen, Zoubin Ghahramani
    Occam's Razor. [Citation Graph (0, 0)][DBLP]
    NIPS, 2000, pp:294-300 [Conf]
  32. Carl Edward Rasmussen, Zoubin Ghahramani
    Infinite Mixtures of Gaussian Process Experts. [Citation Graph (0, 0)][DBLP]
    NIPS, 2001, pp:881-888 [Conf]
  33. Carl Edward Rasmussen, Zoubin Ghahramani
    Bayesian Monte Carlo. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:489-496 [Conf]
  34. Edward Snelson, Zoubin Ghahramani
    Sparse Gaussian Processes using Pseudo-inputs. [Citation Graph (0, 0)][DBLP]
    NIPS, 2005, pp:- [Conf]
  35. Edward Snelson, Carl Edward Rasmussen, Zoubin Ghahramani
    Warped Gaussian Processes. [Citation Graph (0, 0)][DBLP]
    NIPS, 2003, pp:- [Conf]
  36. Naonori Ueda, Ryohei Nakano, Zoubin Ghahramani, Geoffrey E. Hinton
    SMEM Algorithm for Mixture Models. [Citation Graph (0, 0)][DBLP]
    NIPS, 1998, pp:599-605 [Conf]
  37. Daniel M. Wolpert, Zoubin Ghahramani, Michael I. Jordan
    Forward dynamic models in human motor control: Psychophysical evidence. [Citation Graph (0, 0)][DBLP]
    NIPS, 1994, pp:43-50 [Conf]
  38. Jian Zhang, Zoubin Ghahramani, Yiming Yang
    A Probabilistic Model for Online Document Clustering with Application to Novelty Detection. [Citation Graph (0, 0)][DBLP]
    NIPS, 2004, pp:- [Conf]
  39. Jian Zhang, Zoubin Ghahramani, Yiming Yang
    Learning Multiple Related Tasks using Latent Independent Component Analysis. [Citation Graph (0, 0)][DBLP]
    NIPS, 2005, pp:- [Conf]
  40. Xiaojin Zhu, Jaz S. Kandola, Zoubin Ghahramani, John D. Lafferty
    Nonparametric Transforms of Graph Kernels for Semi-Supervised Learning. [Citation Graph (0, 0)][DBLP]
    NIPS, 2004, pp:- [Conf]
  41. Zoubin Ghahramani
    Learning Dynamic Bayesian Networks. [Citation Graph (0, 0)][DBLP]
    Summer School on Neural Networks, 1997, pp:168-197 [Conf]
  42. Ananya Dubey, Seungwoo Hwang, Claudia Rangel, Carl Edward Rasmussen, Zoubin Ghahramani, David L. Wild
    Clustering Protein Sequence and Structure Space with Infinite Gaussian Mixture Models. [Citation Graph (0, 0)][DBLP]
    Pacific Symposium on Biocomputing, 2004, pp:399-410 [Conf]
  43. Philip E. Bourne, C. K. J. Allerston, Werner G. Krebs, Wilfred W. Li, Ilya N. Shindyalov, Adam Godzik, Iddo Friedberg, Tong Liu, David L. Wild, Seungwoo Hwang, Zoubin Ghahramani, Li Chen, John D. Westbrook
    The Status of Structural Genomics Defined Through the Analysis of Current Targets and Structures. [Citation Graph (0, 0)][DBLP]
    Pacific Symposium on Biocomputing, 2004, pp:375-386 [Conf]
  44. Wei Chu, Zoubin Ghahramani, Roland Krause, David L. Wild
    Identifying Protein Complexes in High-Throughput Protein Interaction Screens Using an Infinite Latent Feature Model. [Citation Graph (0, 0)][DBLP]
    Pacific Symposium on Biocomputing, 2006, pp:231-242 [Conf]
  45. Ruslan Salakhutdinov, Sam T. Roweis, Zoubin Ghahramani
    On the Convergence of Bound Optimization Algorithms. [Citation Graph (0, 0)][DBLP]
    UAI, 2003, pp:509-516 [Conf]
  46. Matthew J. Beal, Francesco Falciani, Zoubin Ghahramani, Claudia Rangel, David L. Wild
    A Bayesian approach to reconstructing genetic regulatory networks with hidden factors. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2005, v:21, n:3, pp:349-356 [Journal]
  47. Wei Chu, Zoubin Ghahramani, Francesco Falciani, David L. Wild
    Biomarker discovery in microarray gene expression data with Gaussian processes. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2005, v:21, n:16, pp:3385-3393 [Journal]
  48. Claudia Rangel, John Angus, Zoubin Ghahramani, Maria Lioumi, Elizabeth Sotheran, Alessia Gaiba, David L. Wild, Francesco Falciani
    Modeling T-cell activation using gene expression profiling and state-space models. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2004, v:20, n:9, pp:1361-1372 [Journal]
  49. A. Raval, Zoubin Ghahramani, David L. Wild
    A Bayesian network model for protein fold and remote homologue recognition. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2002, v:18, n:6, pp:788-801 [Journal]
  50. David A. Cohn, Zoubin Ghahramani, Michael I. Jordan
    Active Learning with Statistical Models [Citation Graph (0, 0)][DBLP]
    CoRR, 1996, v:0, n:, pp:- [Journal]
  51. Zoubin Ghahramani
    An Introduction to Hidden Markov Models and Bayesian Networks. [Citation Graph (0, 0)][DBLP]
    IJPRAI, 2001, v:15, n:1, pp:9-42 [Journal]
  52. Sebastian Thrun, Yufeng Liu, Daphne Koller, Andrew Y. Ng, Zoubin Ghahramani, Hugh F. Durrant-Whyte
    Simultaneous Localization and Mapping with Sparse Extended Information Filters. [Citation Graph (0, 0)][DBLP]
    I. J. Robotic Res., 2004, v:23, n:7-8, pp:693-716 [Journal]
  53. David A. Cohn, Zoubin Ghahramani, Michael I. Jordan
    Active Learning with Statistical Models. [Citation Graph (0, 0)][DBLP]
    J. Artif. Intell. Res. (JAIR), 1996, v:4, n:, pp:129-145 [Journal]
  54. Wei Chu, Zoubin Ghahramani
    Gaussian Processes for Ordinal Regression. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2005, v:6, n:, pp:1019-1041 [Journal]
  55. Zoubin Ghahramani, Michael I. Jordan
    Factorial Hidden Markov Models. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1997, v:29, n:2-3, pp:245-273 [Journal]
  56. Michael I. Jordan, Zoubin Ghahramani, Tommi Jaakkola, Lawrence K. Saul
    An Introduction to Variational Methods for Graphical Models. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1999, v:37, n:2, pp:183-233 [Journal]
  57. Zoubin Ghahramani, Geoffrey E. Hinton
    Variational Learning for Switching State-Space Models. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2000, v:12, n:4, pp:831-864 [Journal]
  58. Sam T. Roweis, Zoubin Ghahramani
    A Unifying Review of Linear Gaussian Models. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 1999, v:11, n:2, pp:305-345 [Journal]
  59. Naonori Ueda, Ryohei Nakano, Zoubin Ghahramani, Geoffrey E. Hinton
    SMEM Algorithm for Mixture Models. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2000, v:12, n:9, pp:2109-2128 [Journal]
  60. Naonori Ueda, Zoubin Ghahramani
    Bayesian model search for mixture models based on optimizing variational bounds. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2002, v:15, n:10, pp:1223-1241 [Journal]
  61. Hyun-Chul Kim, Zoubin Ghahramani
    Bayesian Gaussian Process Classification with the EM-EP Algorithm. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Pattern Anal. Mach. Intell., 2006, v:28, n:12, pp:1948-1959 [Journal]
  62. Hyun-Chul Kim, Daijin Kim, Zoubin Ghahramani, Sung Yang Bang
    Appearance-based gender classification with Gaussian processes. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition Letters, 2006, v:27, n:6, pp:618-626 [Journal]
  63. Wei Chu, Zoubin Ghahramani, Alexei Podtelezhnikov, David L. Wild
    Bayesian Segmental Models with Multiple Sequence Alignment Profiles for Protein Secondary Structure and Contact Map Prediction. [Citation Graph (0, 0)][DBLP]
    IEEE/ACM Trans. Comput. Biology Bioinform., 2006, v:3, n:2, pp:98-113 [Journal]
  64. Wei Chu, Vikas Sindhwani, Zoubin Ghahramani, S. Sathiya Keerthi
    Relational Learning with Gaussian Processes. [Citation Graph (0, 0)][DBLP]
    NIPS, 2006, pp:289-296 [Conf]
  65. Edward Meeds, Zoubin Ghahramani, Radford M. Neal, Sam T. Roweis
    Modeling Dyadic Data with Binary Latent Factors. [Citation Graph (0, 0)][DBLP]
    NIPS, 2006, pp:977-984 [Conf]
  66. Ricardo Silva, Zoubin Ghahramani
    Bayesian Inference for Gaussian Mixed Graph Models. [Citation Graph (0, 0)][DBLP]
    UAI, 2006, pp:- [Conf]
  67. Iain Murray, Zoubin Ghahramani
    Bayesian Learning in Undirected Graphical Models: Approximate MCMC Algorithms. [Citation Graph (0, 0)][DBLP]
    UAI, 2004, pp:392-399 [Conf]
  68. Frank Wood, Thomas L. Griffiths, Zoubin Ghahramani
    A Non-Parametric Bayesian Method for Inferring Hidden Causes. [Citation Graph (0, 0)][DBLP]
    UAI, 2006, pp:- [Conf]
  69. Edward Snelson, Zoubin Ghahramani
    Variable Noise and Dimensionality Reduction for Sparse Gaussian processes. [Citation Graph (0, 0)][DBLP]
    UAI, 2006, pp:- [Conf]
  70. Iain Murray, Zoubin Ghahramani, David MacKay
    MCMC for Doubly-intractable Distributions. [Citation Graph (0, 0)][DBLP]
    UAI, 2006, pp:- [Conf]

  71. Scaling the iHMM: Parallelization versus Hadoop. [Citation Graph (, )][DBLP]


  72. Bayesian Methods for Artificial Intelligence and Machine Learning. [Citation Graph (, )][DBLP]


  73. Discovering Temporal Patterns of Differential Gene Expression in Microarray Time Series. [Citation Graph (, )][DBLP]


  74. Infinite Sparse Factor Analysis and Infinite Independent Components Analysis. [Citation Graph (, )][DBLP]


  75. Metropolis Algorithms for Representative Subgraph Sampling. [Citation Graph (, )][DBLP]


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


  77. Statistical models for partial membership. [Citation Graph (, )][DBLP]


  78. Archipelago: nonparametric Bayesian semi-supervised learning. [Citation Graph (, )][DBLP]


  79. Accelerated sampling for the Indian Buffet Process. [Citation Graph (, )][DBLP]


  80. Gender Classification with Bayesian Kernel Methods. [Citation Graph (, )][DBLP]


  81. Hidden Common Cause Relations in Relational Learning. [Citation Graph (, )][DBLP]


  82. Bayesian Exponential Family PCA. [Citation Graph (, )][DBLP]


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


  84. A Robust Bayesian Two-Sample Test for Detecting Intervals of Differential Gene Expression in Microarray Time Series. [Citation Graph (, )][DBLP]


  85. Outlier Robust Gaussian Process Classification. [Citation Graph (, )][DBLP]


  86. Probabilistic graphical models for semi-supervised traffic classification. [Citation Graph (, )][DBLP]


  87. The infinite HMM for unsupervised PoS tagging. [Citation Graph (, )][DBLP]


  88. Gene function prediction from synthetic lethality networks via ranking on demand. [Citation Graph (, )][DBLP]


  89. Discovering transcriptional modules by Bayesian data integration. [Citation Graph (, )][DBLP]


  90. R/BHC: fast Bayesian hierarchical clustering for microarray data. [Citation Graph (, )][DBLP]


  91. Bayesian two-sample tests [Citation Graph (, )][DBLP]


  92. Ranking Relations using Analogies in Biological and Information Networks [Citation Graph (, )][DBLP]


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