| 2008 |
|---|
| 86 | EE | Zoubin Ghahramani:
Bayesian Methods for Artificial Intelligence and Machine Learning.
ECAI 2008: 8 |
| 85 | EE | Christian Hübler,
Hans-Peter Kriegel,
Karsten M. Borgwardt,
Zoubin Ghahramani:
Metropolis Algorithms for Representative Subgraph Sampling.
ICDM 2008: 283-292 |
| 84 | EE | Jurgen Van Gael,
Yunus Saatci,
Yee Whye Teh,
Zoubin Ghahramani:
Beam sampling for the infinite hidden Markov model.
ICML 2008: 1088-1095 |
| 83 | EE | Katherine A. Heller,
Sinead Williamson,
Zoubin Ghahramani:
Statistical models for partial membership.
ICML 2008: 392-399 |
| 82 | EE | Shakir Mohamed,
Katherine A. Heller,
Zoubin Ghahramani:
Bayesian Exponential Family PCA.
NIPS 2008: 1089-1096 |
| 81 | EE | Jurgen Van Gael,
Yee Whye Teh,
Zoubin Ghahramani:
The Infinite Factorial Hidden Markov Model.
NIPS 2008: 1697-1704 |
| 80 | EE | Hyun-Chul Kim,
Zoubin Ghahramani:
Outlier Robust Gaussian Process Classification.
SSPR/SPR 2008: 896-905 |
| 79 | EE | David J. Kriegman,
David J. Fleet,
Zoubin Ghahramani:
Editorial-State of the Transactions.
IEEE Trans. Pattern Anal. Mach. Intell. 30(2): 193-194 (2008) |
| 78 | EE | David J. Kriegman,
David J. Fleet,
Zoubin Ghahramani:
Introduction of New Associate Editors.
IEEE Trans. Pattern Anal. Mach. Intell. 30(4): 561 (2008) |
| 77 | EE | Jian Zhang,
Zoubin Ghahramani,
Yiming Yang:
Flexible latent variable models for multi-task learning.
Machine Learning 73(3): 221-242 (2008) |
| 2007 |
|---|
| 76 | | Zoubin Ghahramani:
Machine Learning, Proceedings of the Twenty-Fourth International Conference (ICML 2007), Corvalis, Oregon, USA, June 20-24, 2007
ACM 2007 |
| 75 | EE | David Knowles,
Zoubin Ghahramani:
Infinite Sparse Factor Analysis and Infinite Independent Components Analysis.
ICA 2007: 381-388 |
| 74 | EE | Ricardo Silva,
Wei Chu,
Zoubin Ghahramani:
Hidden Common Cause Relations in Relational Learning.
NIPS 2007 |
| 2006 |
|---|
| 73 | EE | Arik Azran,
Zoubin Ghahramani:
Spectral Methods for Automatic Multiscale Data Clustering.
CVPR (1) 2006: 190-197 |
| 72 | EE | Katherine A. Heller,
Zoubin Ghahramani:
A Simple Bayesian Framework for Content-Based Image Retrieval.
CVPR (2) 2006: 2110-2117 |
| 71 | EE | Arik Azran,
Zoubin Ghahramani:
A new approach to data driven clustering.
ICML 2006: 57-64 |
| 70 | EE | Hyun-Chul Kim,
Daijin Kim,
Zoubin Ghahramani,
Sung Yang Bang:
Gender Classification with Bayesian Kernel Methods.
IJCNN 2006: 3371-3376 |
| 69 | EE | Wei Chu,
Vikas Sindhwani,
Zoubin Ghahramani,
S. Sathiya Keerthi:
Relational Learning with Gaussian Processes.
NIPS 2006: 289-296 |
| 68 | EE | Edward Meeds,
Zoubin Ghahramani,
Radford M. Neal,
Sam T. Roweis:
Modeling Dyadic Data with Binary Latent Factors.
NIPS 2006: 977-984 |
| 67 | EE | Wei Chu,
Zoubin Ghahramani,
Roland Krause,
David L. Wild:
Identifying Protein Complexes in High-Throughput Protein Interaction Screens Using an Infinite Latent Feature Model.
Pacific Symposium on Biocomputing 2006: 231-242 |
| 66 | EE | Frank Wood,
Thomas L. Griffiths,
Zoubin Ghahramani:
A Non-Parametric Bayesian Method for Inferring Hidden Causes.
UAI 2006 |
| 65 | EE | Ricardo Silva,
Zoubin Ghahramani:
Bayesian Inference for Gaussian Mixed Graph Models.
UAI 2006 |
| 64 | EE | Iain Murray,
Zoubin Ghahramani,
David MacKay:
MCMC for Doubly-intractable Distributions.
UAI 2006 |
| 63 | EE | Edward Snelson,
Zoubin Ghahramani:
Variable Noise and Dimensionality Reduction for Sparse Gaussian processes.
UAI 2006 |
| 62 | EE | Hyun-Chul Kim,
Zoubin Ghahramani:
Bayesian Gaussian Process Classification with the EM-EP Algorithm.
IEEE Trans. Pattern Anal. Mach. Intell. 28(12): 1948-1959 (2006) |
| 61 | EE | 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.
IEEE/ACM Trans. Comput. Biology Bioinform. 3(2): 98-113 (2006) |
| 60 | EE | Hyun-Chul Kim,
Daijin Kim,
Zoubin Ghahramani,
Sung Yang Bang:
Appearance-based gender classification with Gaussian processes.
Pattern Recognition Letters 27(6): 618-626 (2006) |
| 2005 |
|---|
| 59 | EE | JaeMo Sung,
Sung Yang Bang,
Seungjin Choi,
Zoubin Ghahramani:
U-Likelihood and U-Updating Algorithms: Statistical Inference in Latent Variable Models.
ECML 2005: 377-388 |
| 58 | EE | Wei Chu,
Zoubin Ghahramani:
Preference learning with Gaussian processes.
ICML 2005: 137-144 |
| 57 | EE | Katherine A. Heller,
Zoubin Ghahramani:
Bayesian hierarchical clustering.
ICML 2005: 297-304 |
| 56 | EE | Edward Snelson,
Zoubin Ghahramani:
Compact approximations to Bayesian predictive distributions.
ICML 2005: 840-847 |
| 55 | EE | Zoubin Ghahramani,
Katherine A. Heller:
Bayesian Sets.
NIPS 2005 |
| 54 | EE | Tom Griffiths,
Zoubin Ghahramani:
Infinite latent feature models and the Indian buffet process.
NIPS 2005 |
| 53 | EE | Jian Zhang,
Zoubin Ghahramani,
Yiming Yang:
Learning Multiple Related Tasks using Latent Independent Component Analysis.
NIPS 2005 |
| 52 | EE | Iain Murray,
David MacKay,
Zoubin Ghahramani,
John Skilling:
Nested sampling for Potts models.
NIPS 2005 |
| 51 | EE | Edward Snelson,
Zoubin Ghahramani:
Sparse Gaussian Processes using Pseudo-inputs.
NIPS 2005 |
| 50 | EE | Wei Chu,
Zoubin Ghahramani,
Francesco Falciani,
David L. Wild:
Biomarker discovery in microarray gene expression data with Gaussian processes.
Bioinformatics 21(16): 3385-3393 (2005) |
| 49 | EE | Matthew J. Beal,
Francesco Falciani,
Zoubin Ghahramani,
Claudia Rangel,
David L. Wild:
A Bayesian approach to reconstructing genetic regulatory networks with hidden factors.
Bioinformatics 21(3): 349-356 (2005) |
| 48 | EE | Wei Chu,
Zoubin Ghahramani:
Gaussian Processes for Ordinal Regression.
Journal of Machine Learning Research 6: 1019-1041 (2005) |
| 2004 |
|---|
| 47 | EE | Wei Chu,
Zoubin Ghahramani,
David L. Wild:
Protein secondary structure prediction using sigmoid belief networks to parameterize segmental semi-Markov models.
ESANN 2004: 81-86 |
| 46 | EE | Wei Chu,
Zoubin Ghahramani,
David L. Wild:
A graphical model for protein secondary structure prediction.
ICML 2004 |
| 45 | EE | Yuan (Alan) Qi,
Thomas P. Minka,
Rosalind W. Picard,
Zoubin Ghahramani:
Predictive automatic relevance determination by expectation propagation.
ICML 2004 |
| 44 | EE | Jian Zhang,
Zoubin Ghahramani,
Yiming Yang:
A Probabilistic Model for Online Document Clustering with Application to Novelty Detection.
NIPS 2004 |
| 43 | EE | Xiaojin Zhu,
Jaz S. Kandola,
Zoubin Ghahramani,
John D. Lafferty:
Nonparametric Transforms of Graph Kernels for Semi-Supervised Learning.
NIPS 2004 |
| 42 | EE | 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.
Pacific Symposium on Biocomputing 2004: 375-386 |
| 41 | EE | 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.
Pacific Symposium on Biocomputing 2004: 399-410 |
| 40 | EE | Iain Murray,
Zoubin Ghahramani:
Bayesian Learning in Undirected Graphical Models: Approximate MCMC Algorithms.
UAI 2004: 392-399 |
| 39 | EE | 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.
Bioinformatics 20(9): 1361-1372 (2004) |
| 38 | EE | Sebastian Thrun,
Yufeng Liu,
Daphne Koller,
Andrew Y. Ng,
Zoubin Ghahramani,
Hugh F. Durrant-Whyte:
Simultaneous Localization and Mapping with Sparse Extended Information Filters.
I. J. Robotic Res. 23(7-8): 693-716 (2004) |
| 2003 |
|---|
| 37 | EE | Zoubin Ghahramani:
Unsupervised Learning.
Advanced Lectures on Machine Learning 2003: 72-112 |
| 36 | | Ruslan Salakhutdinov,
Sam T. Roweis,
Zoubin Ghahramani:
Optimization with EM and Expectation-Conjugate-Gradient.
ICML 2003: 672-679 |
| 35 | | Xiaojin Zhu,
Zoubin Ghahramani,
John D. Lafferty:
Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions.
ICML 2003: 912-919 |
| 34 | EE | Edward Snelson,
Carl Edward Rasmussen,
Zoubin Ghahramani:
Warped Gaussian Processes.
NIPS 2003 |
| 33 | | Ruslan Salakhutdinov,
Sam T. Roweis,
Zoubin Ghahramani:
On the Convergence of Bound Optimization Algorithms.
UAI 2003: 509-516 |
| 2002 |
|---|
| 32 | EE | Carl Edward Rasmussen,
Zoubin Ghahramani:
Bayesian Monte Carlo.
NIPS 2002: 489-496 |
| 31 | EE | Rong Jin,
Zoubin Ghahramani:
Learning with Multiple Labels.
NIPS 2002: 897-904 |
| 30 | | A. Raval,
Zoubin Ghahramani,
David L. Wild:
A Bayesian network model for protein fold and remote homologue recognition.
Bioinformatics 18(6): 788-801 (2002) |
| 29 | EE | Naonori Ueda,
Zoubin Ghahramani:
Bayesian model search for mixture models based on optimizing variational bounds.
Neural Networks 15(10): 1223-1241 (2002) |
| 2001 |
|---|
| 28 | | Thomas G. Dietterich,
Suzanna Becker,
Zoubin Ghahramani:
Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, NIPS 2001, December 3-8, 2001, Vancouver, British Columbia, Canada]
MIT Press 2001 |
| 27 | EE | Matthew J. Beal,
Zoubin Ghahramani,
Carl Edward Rasmussen:
The Infinite Hidden Markov Model.
NIPS 2001: 577-584 |
| 26 | EE | Carl Edward Rasmussen,
Zoubin Ghahramani:
Infinite Mixtures of Gaussian Process Experts.
NIPS 2001: 881-888 |
| 25 | | Zoubin Ghahramani:
An Introduction to Hidden Markov Models and Bayesian Networks.
IJPRAI 15(1): 9-42 (2001) |
| 2000 |
|---|
| 24 | EE | Nicholas J. Adams,
Amos J. Storkey,
Christopher K. I. Williams,
Zoubin Ghahramani:
MFDTs: Mean Field Dynamic Trees.
ICPR 2000: 3151-3154 |
| 23 | | Carl Edward Rasmussen,
Zoubin Ghahramani:
Occam's Razor.
NIPS 2000: 294-300 |
| 22 | | Zoubin Ghahramani,
Matthew J. Beal:
Propagation Algorithms for Variational Bayesian Learning.
NIPS 2000: 507-513 |
| 21 | | Zoubin Ghahramani,
Geoffrey E. Hinton:
Variational Learning for Switching State-Space Models.
Neural Computation 12(4): 831-864 (2000) |
| 20 | | Naonori Ueda,
Ryohei Nakano,
Zoubin Ghahramani,
Geoffrey E. Hinton:
SMEM Algorithm for Mixture Models.
Neural Computation 12(9): 2109-2128 (2000) |
| 19 | EE | Naonori Ueda,
Ryohei Nakano,
Zoubin Ghahramani,
Geoffrey E. Hinton:
Split and Merge EM Algorithm for Improving Gaussian Mixture Density Estimates.
VLSI Signal Processing 26(1-2): 133-140 (2000) |
| 1999 |
|---|
| 18 | EE | Zoubin Ghahramani,
Matthew J. Beal:
Variational Inference for Bayesian Mixtures of Factor Analysers.
NIPS 1999: 449-455 |
| 17 | EE | Geoffrey E. Hinton,
Zoubin Ghahramani,
Yee Whye Teh:
Learning to Parse Images.
NIPS 1999: 463-469 |
| 16 | | Michael I. Jordan,
Zoubin Ghahramani,
Tommi Jaakkola,
Lawrence K. Saul:
An Introduction to Variational Methods for Graphical Models.
Machine Learning 37(2): 183-233 (1999) |
| 15 | | Sam T. Roweis,
Zoubin Ghahramani:
A Unifying Review of Linear Gaussian Models.
Neural Computation 11(2): 305-345 (1999) |
| 1998 |
|---|
| 14 | EE | Zoubin Ghahramani,
Sam T. Roweis:
Learning Nonlinear Dynamical Systems Using an EM Algorithm.
NIPS 1998: 431-437 |
| 13 | EE | Naonori Ueda,
Ryohei Nakano,
Zoubin Ghahramani,
Geoffrey E. Hinton:
SMEM Algorithm for Mixture Models.
NIPS 1998: 599-605 |
| 1997 |
|---|
| 12 | | Zoubin Ghahramani,
Geoffrey E. Hinton:
Hierarchical Non-linear Factor Analysis and Topographic Maps.
NIPS 1997 |
| 11 | EE | Zoubin Ghahramani:
Learning Dynamic Bayesian Networks.
Summer School on Neural Networks 1997: 168-197 |
| 10 | | Zoubin Ghahramani,
Michael I. Jordan:
Factorial Hidden Markov Models.
Machine Learning 29(2-3): 245-273 (1997) |
| 1996 |
|---|
| 9 | EE | Michael I. Jordan,
Zoubin Ghahramani,
Lawrence K. Saul:
Hidden Markov Decision Trees.
NIPS 1996: 501-507 |
| 8 | EE | David A. Cohn,
Zoubin Ghahramani,
Michael I. Jordan:
Active Learning with Statistical Models
CoRR cs.AI/9603104: (1996) |
| 7 | | David A. Cohn,
Zoubin Ghahramani,
Michael I. Jordan:
Active Learning with Statistical Models.
J. Artif. Intell. Res. (JAIR) 4: 129-145 (1996) |
| 1995 |
|---|
| 6 | EE | Zoubin Ghahramani,
Michael I. Jordan:
Factorial Hidden Markov Models.
NIPS 1995: 472-478 |
| 1994 |
|---|
| 5 | EE | Zoubin Ghahramani,
Daniel M. Wolpert,
Michael I. Jordan:
Computational Structure of coordinate transformations: A generalization study.
NIPS 1994: 1125-1132 |
| 4 | EE | Daniel M. Wolpert,
Zoubin Ghahramani,
Michael I. Jordan:
Forward dynamic models in human motor control: Psychophysical evidence.
NIPS 1994: 43-50 |
| 3 | EE | Zoubin Ghahramani:
Factorial Learning and the EM Algorithm.
NIPS 1994: 617-624 |
| 2 | EE | David A. Cohn,
Zoubin Ghahramani,
Michael I. Jordan:
Active Learning with Statistical Models.
NIPS 1994: 705-712 |
| 1993 |
|---|
| 1 | EE | Zoubin Ghahramani,
Michael I. Jordan:
Supervised learning from incomplete data via an EM approach.
NIPS 1993: 120-127 |
