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Zoubin Ghahramani
2010 – today
- 2013
[j60]Frederik Eaton, Zoubin Ghahramani: Model Reductions for Inference: Generality of Pairwise, Binary, and Planar Factor Graphs. Neural Computation 25(5): 1213-1260 (2013)- [c91]Tomoharu Iwata, Amar Shah, Zoubin Ghahramani: Discovering latent influence in online social activities via shared cascade poisson processes. KDD 2013: 266-274
- [c90]Simon Lacoste-Julien, Konstantina Palla, Alex Davies, Gjergji Kasneci, Thore Graepel, Zoubin Ghahramani: SIGMa: simple greedy matching for aligning large knowledge bases. KDD 2013: 572-580
- [c89]Konstantinos Bousmalis, Stefanos Zafeiriou, Louis-Philippe Morency, Maja Pantic, Zoubin Ghahramani: Variational Hidden Conditional Random Fields with Coupled Dirichlet Process Mixtures. ECML/PKDD (2) 2013: 531-547
- [i16]David K. Duvenaud, James Robert Lloyd, Roger Grosse, Joshua B. Tenenbaum, Zoubin Ghahramani: Structure Discovery in Nonparametric Regression through Compositional Kernel Search. CoRR abs/1302.4922 (2013)
- [i15]Colorado Reed, Zoubin Ghahramani: Scaling the Indian Buffet Process via Submodular Maximization. CoRR abs/1304.3285 (2013)
- [i14]Sebastien Bratieres, Novi Quadrianto, Zoubin Ghahramani: Bayesian Structured Prediction Using Gaussian Processes. CoRR abs/1307.3846 (2013)
- [i13]Novi Quadrianto, Viktoriia Sharmanska, David A. Knowles, Zoubin Ghahramani: The Supervised IBP: Neighbourhood Preserving Infinite Latent Feature Models. CoRR abs/1309.6858 (2013)
- [i12]Amar Shah, Zoubin Ghahramani: Determinantal Clustering Processes - A Nonparametric Bayesian Approach to Kernel Based Semi-Supervised Clustering. CoRR abs/1309.6862 (2013)
- 2012
- [j59]Paul D. W. Kirk, Jim E. Griffin, Richard S. Savage, Zoubin Ghahramani, David L. Wild: Bayesian correlated clustering to integrate multiple datasets. Bioinformatics 28(24): 3290-3297 (2012)
- [j58]John Cunningham, Zoubin Ghahramani, Carl Edward Rasmussen: Gaussian Processes for time-marked time-series data. Journal of Machine Learning Research - Proceedings Track 22: 255-263 (2012)
- [j57]Hyun-Chul Kim, Zoubin Ghahramani: Bayesian Classifier Combination. Journal of Machine Learning Research - Proceedings Track 22: 619-627 (2012)
- [j56]Donglin Niu, Jennifer G. Dy, Zoubin Ghahramani: A Nonparametric Bayesian Model for Multiple Clustering with Overlapping Feature Views. Journal of Machine Learning Research - Proceedings Track 22: 814-822 (2012)
- [j55]Jacob Steinhardt, Zoubin Ghahramani: Flexible Martingale Priors for Deep Hierarchies. Journal of Machine Learning Research - Proceedings Track 22: 1108-1116 (2012)
- [c88]Shakir Mohamed, Katherine A. Heller, Zoubin Ghahramani: Evaluating Bayesian and L1 Approaches for Sparse Unsupervised Learning . ICML 2012
- [c87]Konstantina Palla, David A. Knowles, Zoubin Ghahramani: An Infinite Latent Attribute Model for Network Data. ICML 2012
- [c86]Barnabás Póczos, Zoubin Ghahramani, Jeff G. Schneider: Copula-based Kernel Dependency Measures. ICML 2012
- [c85]Andrew Gordon Wilson, David A. Knowles, Zoubin Ghahramani: Gaussian Process Regression Networks. ICML 2012
- [c84]Michael A. Osborne, David K. Duvenaud, Roman Garnett, Carl E. Rasmussen, Stephen J. Roberts, Zoubin Ghahramani: Active Learning of Model Evidence Using Bayesian Quadrature. NIPS 2012: 46-54
- [c83]James Robert Lloyd, Peter Orbanz, Zoubin Ghahramani, Daniel M. Roy: Random function priors for exchangeable arrays with applications to graphs and relational data. NIPS 2012: 1007-1015
- [c82]Neil Houlsby, José Miguel Hernández-Lobato, Ferenc Huszar, Zoubin Ghahramani: Collaborative Gaussian Processes for Preference Learning. NIPS 2012: 2105-2113
- [c81]David A. Knowles, Konstantina Palla, Zoubin Ghahramani: A nonparametric variable clustering model. NIPS 2012: 2996-3004
- [c80]Yichuan Zhang, Charles A. Sutton, Amos J. Storkey, Zoubin Ghahramani: Continuous Relaxations for Discrete Hamiltonian Monte Carlo. NIPS 2012: 3203-3211
- [c79]Andrew Gordon Wilson, Zoubin Ghahramani: Modelling Input Varying Correlations between Multiple Responses. ECML/PKDD (2) 2012: 858-861
- [i11]Finale Doshi-Velez, Zoubin Ghahramani: Correlated Non-Parametric Latent Feature Models. CoRR abs/1205.2650 (2012)
- [i10]Barnabás Póczos, Zoubin Ghahramani, Jeff G. Schneider: Copula-based Kernel Dependency Measures. CoRR abs/1206.4682 (2012)
- [i9]Iain Murray, Zoubin Ghahramani: Bayesian Learning in Undirected Graphical Models: Approximate MCMC algorithms. CoRR abs/1207.4134 (2012)
- [i8]Simon Lacoste-Julien, Konstantina Palla, Alex Davies, Gjergji Kasneci, Thore Graepel, Zoubin Ghahramani: SiGMa: Simple Greedy Matching for Aligning Large Knowledge Bases. CoRR abs/1207.4525 (2012)
- [i7]Ruslan Salakhutdinov, Sam T. Roweis, Zoubin Ghahramani: On the Convergence of Bound Optimization Algorithms. CoRR abs/1212.2490 (2012)
- 2011
- [j54]Thomas L. Griffiths, Zoubin Ghahramani: The Indian Buffet Process: An Introduction and Review. Journal of Machine Learning Research 12: 1185-1224 (2011)
- [j53]Simon Lacoste-Julien, Ferenc Huszar, Zoubin Ghahramani: Approximate inference for the loss-calibrated Bayesian. Journal of Machine Learning Research - Proceedings Track 15: 416-424 (2011)
- [j52]Ramin Zabih, Jiri Matas, Zoubin Ghahramani: State of the Journal. IEEE Trans. Pattern Anal. Mach. Intell. 33(1): 1-2 (2011)
- [j51]Ramin Zabih, Zoubin Ghahramani, Sing Bing Kang, Jiri Matas: Editor's Note. IEEE Trans. Pattern Anal. Mach. Intell. 33(5): 865-866 (2011)
- [j50]Ramin Zabih, Zoubin Ghahramani, Sing Bing Kang, Jiri Matas: Editorial. IEEE Trans. Pattern Anal. Mach. Intell. 33(9): 1697-1698 (2011)
- [c78]David A. Knowles, Jurgen Van Gael, Zoubin Ghahramani: Message Passing Algorithms for the Dirichlet Diffusion Tree. ICML 2011: 721-728
- [c77]Ali Bahramisharif, Marcel A. J. van Gerven, Jan-Mathijs Schoffelen, Zoubin Ghahramani, Tom Heskes: The Dynamic Beamformer. MLINI 2011: 148-155
- [c76]Joshua T. Abbott, Katherine A. Heller, Zoubin Ghahramani, Thomas L. Griffiths: Testing a Bayesian Measure of Representativeness Using a Large Image Database. NIPS 2011: 2321-2329
- [c75]
- [c74]
- [i6]Shakir Mohamed, Katherine A. Heller, Zoubin Ghahramani: Bayesian and L1 Approaches to Sparse Unsupervised Learning. CoRR abs/1106.1157 (2011)
- [i5]Neil Houlsby, Ferenc Huszar, Zoubin Ghahramani, Máté Lengyel: Bayesian Active Learning for Classification and Preference Learning. CoRR abs/1112.5745 (2011)
- 2010
- [j49]Christoph Lippert, Zoubin Ghahramani, Karsten M. Borgwardt: Gene function prediction from synthetic lethality networks via ranking on demand. Bioinformatics 26(7): 912-918 (2010)
- [j48]Richard S. Savage, Zoubin Ghahramani, Jim E. Griffin, Bernard J. de la Cruz, David L. Wild: Discovering transcriptional modules by Bayesian data integration. Bioinformatics [ISMB] 26(12): 158-167 (2010)
- [j47]Oliver Stegle, Katherine J. Denby, Emma J. Cooke, David L. Wild, Zoubin Ghahramani, Karsten M. Borgwardt: A Robust Bayesian Two-Sample Test for Detecting Intervals of Differential Gene Expression in Microarray Time Series. Journal of Computational Biology 17(3): 355-367 (2010)
- [j46]Ryan Prescott Adams, Hanna M. Wallach, Zoubin Ghahramani: Learning the Structure of Deep Sparse Graphical Models. Journal of Machine Learning Research - Proceedings Track 9: 1-8 (2010)
- [j45]Sinead Williamson, Peter Orbanz, Zoubin Ghahramani: Dependent Indian Buffet Processes. Journal of Machine Learning Research - Proceedings Track 9: 924-931 (2010)
- [j44]Jure Leskovec, Deepayan Chakrabarti, Jon M. Kleinberg, Christos Faloutsos, Zoubin Ghahramani: Kronecker Graphs: An Approach to Modeling Networks. Journal of Machine Learning Research 11: 985-1042 (2010)
- [j43]Ramin Zabih, Jiri Matas, Zoubin Ghahramani: Editor's Note. IEEE Trans. Pattern Anal. Mach. Intell. 32(5): 769 (2010)
- [j42]Ramin Zabih, Jiri Matas, Zoubin Ghahramani: Editor's Note. IEEE Trans. Pattern Anal. Mach. Intell. 32(8): 1345-1346 (2010)
- [j41]Ramin Zabih, Jiri Matas, Zoubin Ghahramani: Editor's Note. IEEE Trans. Pattern Anal. Mach. Intell. 32(10): 1729 (2010)
- [c73]Sebastien Bratieres, Jurgen Van Gael, Andreas Vlachos, Zoubin Ghahramani: Scaling the iHMM: Parallelization versus Hadoop. CIT 2010: 1235-1240
- [c72]Charalampos Rotsos, Jurgen Van Gael, Andrew W. Moore, Zoubin Ghahramani: Probabilistic graphical models for semi-supervised traffic classification. IWCMC 2010: 752-757
- [c71]Ryan Prescott Adams, Zoubin Ghahramani, Michael I. Jordan: Tree-Structured Stick Breaking for Hierarchical Data. NIPS 2010: 19-27
- [c70]
- [i4]David A. Knowles, Zoubin Ghahramani: Nonparametric Bayesian Sparse Factor Models with application to Gene Expression modelling. CoRR abs/1011.6293 (2010)
2000 – 2009
- 2009
- [j40]Richard S. Savage, Katherine A. Heller, Yang Xu, Zoubin Ghahramani, William M. Truman, Murray Grant, Katherine J. Denby, David L. Wild: R/BHC: fast Bayesian hierarchical clustering for microarray data. BMC Bioinformatics 10 (2009)
- [j39]Wei Chu, Zoubin Ghahramani: Probabilistic Models for Incomplete Multi-dimensional Arrays. Journal of Machine Learning Research - Proceedings Track 5: 89-96 (2009)
- [j38]Frederik Eaton, Zoubin Ghahramani: Choosing a Variable to Clamp. Journal of Machine Learning Research - Proceedings Track 5: 145-152 (2009)
- [j37]Christoph Lippert, Oliver Stegle, Zoubin Ghahramani, Karsten M. Borgwardt: A kernel method for unsupervised structured network inference. Journal of Machine Learning Research - Proceedings Track 5: 368-375 (2009)
- [j36]Ricardo Silva, Zoubin Ghahramani: Factorial Mixture of Gaussians and the Marginal Independence Model. Journal of Machine Learning Research - Proceedings Track 5: 520-527 (2009)
- [j35]Thomas S. Stepleton, Zoubin Ghahramani, Geoffrey J. Gordon, Tai Sing Lee: The Block Diagonal Infinite Hidden Markov Model. Journal of Machine Learning Research - Proceedings Track 5: 552-559 (2009)
- [j34]Yang Xu, Katherine A. Heller, Zoubin Ghahramani: Tree-Based Inference for Dirichlet Process Mixtures. Journal of Machine Learning Research - Proceedings Track 5: 623-630 (2009)
- [j33]Ricardo Silva, Zoubin Ghahramani: The Hidden Life of Latent Variables: Bayesian Learning with Mixed Graph Models. Journal of Machine Learning Research 10: 1187-1238 (2009)
- [j32]Ramin Zabih, Zoubin Ghahramani, Jiri Matas: Introduction of New Associate Editors. IEEE Trans. Pattern Anal. Mach. Intell. 31(6): 961-963 (2009)
- [j31]Ramin Zabih, Jiri Matas, Zoubin Ghahramani: Introduction of New Associate Editors. IEEE Trans. Pattern Anal. Mach. Intell. 31(8): 1345-1346 (2009)
- [j30]Carl Edward Rasmussen, Bernard J. de la Cruz, Zoubin Ghahramani, David L. Wild: Modeling and Visualizing Uncertainty in Gene Expression Clusters Using Dirichlet Process Mixtures. IEEE/ACM Trans. Comput. Biology Bioinform. 6(4): 615-628 (2009)
- [c69]Jurgen Van Gael, Andreas Vlachos, Zoubin Ghahramani: The infinite HMM for unsupervised PoS tagging. EMNLP 2009: 678-687
- [c68]Oliver Stegle, Katherine J. Denby, David L. Wild, Stuart McHattie, Andrew Meade, Zoubin Ghahramani, Karsten M. Borgwardt: Discovering Temporal Patterns of Differential Gene Expression in Microarray Time Series. GCB 2009: 133-142
- [c67]Ryan Prescott Adams, Zoubin Ghahramani: Archipelago: nonparametric Bayesian semi-supervised learning. ICML 2009: 1
- [c66]Finale Doshi-Velez, Zoubin Ghahramani: Accelerated sampling for the Indian Buffet Process. ICML 2009: 35
- [c65]Finale Doshi-Velez, David A. Knowles, Shakir Mohamed, Zoubin Ghahramani: Large Scale Nonparametric Bayesian Inference: Data Parallelisation in the Indian Buffet Process. NIPS 2009: 1294-1302
- [c64]Oliver Stegle, Katherine J. Denby, David L. Wild, Zoubin Ghahramani, Karsten M. Borgwardt: A Robust Bayesian Two-Sample Test for Detecting Intervals of Differential Gene Expression in Microarray Time Series. RECOMB 2009: 201-216
- [c63]Finale Doshi-Velez, Zoubin Ghahramani: Correlated Non-Parametric Latent Feature Models. UAI 2009: 143-150
- [i3]
- [i2]Ricardo Silva, Katherine A. Heller, Zoubin Ghahramani, Edoardo M. Airoldi: Ranking Relations using Analogies in Biological and Information Networks. CoRR abs/0912.5193 (2009)
- 2008
- [j29]Jian Zhang, Zoubin Ghahramani, Yiming Yang: Flexible latent variable models for multi-task learning. Machine Learning 73(3): 221-242 (2008)
- [j28]David J. Kriegman, David J. Fleet, Zoubin Ghahramani: Editorial-State of the Transactions. IEEE Trans. Pattern Anal. Mach. Intell. 30(2): 193-194 (2008)
- [j27]David J. Kriegman, David J. Fleet, Zoubin Ghahramani: Introduction of New Associate Editors. IEEE Trans. Pattern Anal. Mach. Intell. 30(4): 561 (2008)
- [j26]David J. Kriegman, David J. Fleet, Zoubin Ghahramani: Introduction of New Associate Editors. IEEE Trans. Pattern Anal. Mach. Intell. 30(9): 1505-1506 (2008)
- [j25]David J. Kriegman, David J. Fleet, Zoubin Ghahramani: Introduction of New Associate Editors. IEEE Trans. Pattern Anal. Mach. Intell. 30(12): 2065-2066 (2008)
- [j24]JaeMo Sung, Zoubin Ghahramani, Sung Yang Bang: Latent-Space Variational Bayes. IEEE Trans. Pattern Anal. Mach. Intell. 30(12): 2236-2242 (2008)
- [j23]JaeMo Sung, Zoubin Ghahramani, Sung Yang Bang: Second-Order Latent-Space Variational Bayes for Approximate Bayesian Inference. IEEE Signal Process. Lett. 15: 918-921 (2008)
- [c62]
- [c61]Christian Hübler, Hans-Peter Kriegel, Karsten M. Borgwardt, Zoubin Ghahramani: Metropolis Algorithms for Representative Subgraph Sampling. ICDM 2008: 283-292
- [c60]Katherine A. Heller, Sinead Williamson, Zoubin Ghahramani: Statistical models for partial membership. ICML 2008: 392-399
- [c59]Jurgen Van Gael, Yunus Saatci, Yee Whye Teh, Zoubin Ghahramani: Beam sampling for the infinite hidden Markov model. ICML 2008: 1088-1095
- [c58]Shakir Mohamed, Katherine A. Heller, Zoubin Ghahramani: Bayesian Exponential Family PCA. NIPS 2008: 1089-1096
- [c57]Jurgen Van Gael, Yee Whye Teh, Zoubin Ghahramani: The Infinite Factorial Hidden Markov Model. NIPS 2008: 1697-1704
- [c56]Hyun-Chul Kim, Zoubin Ghahramani: Outlier Robust Gaussian Process Classification. SSPR/SPR 2008: 896-905
- 2007
- [j22]Katherine A. Heller, Zoubin Ghahramani: A Nonparametric Bayesian Approach to Modeling Overlapping Clusters. Journal of Machine Learning Research - Proceedings Track 2: 187-194 (2007)
- [j21]Ricardo Silva, Katherine A. Heller, Zoubin Ghahramani: Analogical Reasoning with Relational Bayesian Sets. Journal of Machine Learning Research - Proceedings Track 2: 500-507 (2007)
- [j20]Edward Snelson, Zoubin Ghahramani: Local and global sparse Gaussian process approximations. Journal of Machine Learning Research - Proceedings Track 2: 524-531 (2007)
- [j19]Yee Whye Teh, Dilan Görür, Zoubin Ghahramani: Stick-breaking Construction for the Indian Buffet Process. Journal of Machine Learning Research - Proceedings Track 2: 556-563 (2007)
- [c55]David A. Knowles, Zoubin Ghahramani: Infinite Sparse Factor Analysis and Infinite Independent Components Analysis. ICA 2007: 381-388
- [c54]Ricardo Silva, Wei Chu, Zoubin Ghahramani: Hidden Common Cause Relations in Relational Learning. NIPS 2007
- [e2]Zoubin Ghahramani (Ed.): Machine Learning, Proceedings of the Twenty-Fourth International Conference (ICML 2007), Corvallis, Oregon, USA, June 20-24, 2007. ACM International Conference Proceeding Series 227, ACM 2007, ISBN 978-1-59593-793-3
- 2006
- [j18]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)
- [j17]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)
- [j16]Wei Chu, Zoubin Ghahramani, Alexei A. 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)
- [c53]Arik Azran, Zoubin Ghahramani: Spectral Methods for Automatic Multiscale Data Clustering. CVPR (1) 2006: 190-197
- [c52]Katherine A. Heller, Zoubin Ghahramani: A Simple Bayesian Framework for Content-Based Image Retrieval. CVPR (2) 2006: 2110-2117
- [c51]
- [c50]Hyun-Chul Kim, Daijin Kim, Zoubin Ghahramani, Sung Yang Bang: Gender Classification with Bayesian Kernel Methods. IJCNN 2006: 3371-3376
- [c49]Wei Chu, Vikas Sindhwani, Zoubin Ghahramani, S. Sathiya Keerthi: Relational Learning with Gaussian Processes. NIPS 2006: 289-296
- [c48]Edward Meeds, Zoubin Ghahramani, Radford M. Neal, Sam T. Roweis: Modeling Dyadic Data with Binary Latent Factors. NIPS 2006: 977-984
- [c47]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
- [c46]Iain Murray, Zoubin Ghahramani, David J. C. MacKay: MCMC for Doubly-intractable Distributions. UAI 2006
- [c45]
- [c44]Edward Snelson, Zoubin Ghahramani: Variable Noise and Dimensionality Reduction for Sparse Gaussian processes. UAI 2006
- [c43]Frank Wood, Thomas L. Griffiths, Zoubin Ghahramani: A Non-Parametric Bayesian Method for Inferring Hidden Causes. UAI 2006
- 2005
- [j15]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)
- [j14]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)
- [j13]Wei Chu, Zoubin Ghahramani: Gaussian Processes for Ordinal Regression. Journal of Machine Learning Research 6: 1019-1041 (2005)
- [c42]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
- [c41]
- [c40]
- [c39]Edward Snelson, Zoubin Ghahramani: Compact approximations to Bayesian predictive distributions. ICML 2005: 840-847
- [c38]
- [c37]Thomas L. Griffiths, Zoubin Ghahramani: Infinite latent feature models and the Indian buffet process. NIPS 2005
- [c36]Iain Murray, David J. C. MacKay, Zoubin Ghahramani, John Skilling: Nested sampling for Potts models. NIPS 2005
- [c35]
- [c34]Jian Zhang, Zoubin Ghahramani, Yiming Yang: Learning Multiple Related Tasks using Latent Independent Component Analysis. NIPS 2005
- 2004
- [j12]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)
- [j11]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)
- [c33]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
- [c32]Wei Chu, Zoubin Ghahramani, David L. Wild: A graphical model for protein secondary structure prediction. ICML 2004
- [c31]Yuan (Alan) Qi, Thomas P. Minka, Rosalind W. Picard, Zoubin Ghahramani: Predictive automatic relevance determination by expectation propagation. ICML 2004
- [c30]Jian Zhang, Zoubin Ghahramani, Yiming Yang: A Probabilistic Model for Online Document Clustering with Application to Novelty Detection. NIPS 2004
- [c29]Xiaojin Zhu, Jaz S. Kandola, Zoubin Ghahramani, John D. Lafferty: Nonparametric Transforms of Graph Kernels for Semi-Supervised Learning. NIPS 2004
- [c28]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
- [c27]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
- [c26]Iain Murray, Zoubin Ghahramani: Bayesian Learning in Undirected Graphical Models: Approximate MCMC Algorithms. UAI 2004: 392-399
- 2003
- [c25]
- [c24]Ruslan Salakhutdinov, Sam T. Roweis, Zoubin Ghahramani: Optimization with EM and Expectation-Conjugate-Gradient. ICML 2003: 672-679
- [c23]Xiaojin Zhu, Zoubin Ghahramani, John D. Lafferty: Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions. ICML 2003: 912-919
- [c22]
- [c21]Ruslan Salakhutdinov, Sam T. Roweis, Zoubin Ghahramani: On the Convergence of Bound Optimization Algorithms. UAI 2003: 509-516
- 2002
- [j10]A. Raval, Zoubin Ghahramani, David L. Wild: A Bayesian network model for protein fold and remote homologue recognition. Bioinformatics 18(6): 788-801 (2002)
- [j9]Naonori Ueda, Zoubin Ghahramani: Bayesian model search for mixture models based on optimizing variational bounds. Neural Networks 15(10): 1223-1241 (2002)
- [c20]
- [c19]
- 2001
- [j8]Zoubin Ghahramani: An Introduction to Hidden Markov Models and Bayesian Networks. IJPRAI 15(1): 9-42 (2001)
- [c18]Matthew J. Beal, Zoubin Ghahramani, Carl Edward Rasmussen: The Infinite Hidden Markov Model. NIPS 2001: 577-584
- [c17]Carl Edward Rasmussen, Zoubin Ghahramani: Infinite Mixtures of Gaussian Process Experts. NIPS 2001: 881-888
- [e1]Thomas G. Dietterich, Suzanna Becker, Zoubin Ghahramani (Eds.): 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
- 2000
- [j7]Zoubin Ghahramani, Geoffrey E. Hinton: Variational Learning for Switching State-Space Models. Neural Computation 12(4): 831-864 (2000)
- [j6]Naonori Ueda, Ryohei Nakano, Zoubin Ghahramani, Geoffrey E. Hinton: SMEM Algorithm for Mixture Models. Neural Computation 12(9): 2109-2128 (2000)
- [j5]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)
- [c16]Nicholas J. Adams, Amos J. Storkey, Christopher K. I. Williams, Zoubin Ghahramani: MFDTs: Mean Field Dynamic Trees. ICPR 2000: 3151-3154
- [c15]
- [c14]Zoubin Ghahramani, Matthew J. Beal: Propagation Algorithms for Variational Bayesian Learning. NIPS 2000: 507-513
1990 – 1999
- 1999
- [j4]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)
- [j3]Sam T. Roweis, Zoubin Ghahramani: A Unifying Review of Linear Gaussian Models. Neural Computation 11(2): 305-345 (1999)
- [c13]Zoubin Ghahramani, Matthew J. Beal: Variational Inference for Bayesian Mixtures of Factor Analysers. NIPS 1999: 449-455
- [c12]
- 1998
- [c11]Zoubin Ghahramani, Sam T. Roweis: Learning Nonlinear Dynamical Systems Using an EM Algorithm. NIPS 1998: 431-437
- [c10]Naonori Ueda, Ryohei Nakano, Zoubin Ghahramani, Geoffrey E. Hinton: SMEM Algorithm for Mixture Models. NIPS 1998: 599-605
- 1997
- [j2]Zoubin Ghahramani, Michael I. Jordan: Factorial Hidden Markov Models. Machine Learning 29(2-3): 245-273 (1997)
- [c9]Zoubin Ghahramani, Geoffrey E. Hinton: Hierarchical Non-linear Factor Analysis and Topographic Maps. NIPS 1997
- [c8]Zoubin Ghahramani: Learning Dynamic Bayesian Networks. Summer School on Neural Networks 1997: 168-197
- 1996
- [j1]David A. Cohn, Zoubin Ghahramani, Michael I. Jordan: Active Learning with Statistical Models. J. Artif. Intell. Res. (JAIR) 4: 129-145 (1996)
- [c7]Michael I. Jordan, Zoubin Ghahramani, Lawrence K. Saul: Hidden Markov Decision Trees. NIPS 1996: 501-507
- [i1]David A. Cohn, Zoubin Ghahramani, Michael I. Jordan: Active Learning with Statistical Models. CoRR cs.AI/9603104 (1996)
- 1995
- [c6]
- 1994
- [c5]Daniel M. Wolpert, Zoubin Ghahramani, Michael I. Jordan: Forward dynamic models in human motor control: Psychophysical evidence. NIPS 1994: 43-50
- [c4]
- [c3]David A. Cohn, Zoubin Ghahramani, Michael I. Jordan: Active Learning with Statistical Models. NIPS 1994: 705-712
- [c2]Zoubin Ghahramani, Daniel M. Wolpert, Michael I. Jordan: Computational Structure of coordinate transformations: A generalization study. NIPS 1994: 1125-1132
- 1993
- [c1]Zoubin Ghahramani, Michael I. Jordan: Supervised learning from incomplete data via an EM approach. NIPS 1993: 120-127
Coauthor Index
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last updated on 2013-10-16 21:29 CEST by the dblp team