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Number of items: 66.

Article

Berg, TL; Berg, AC; Edwards, J; Maire, M; White, R; Teh, YW; Learned-Miller, E; Names and Faces. International Journal of Computer Vision

Gorur, D; Teh, YW; (2011) Concave-Convex Adaptive Rejection Sampling. J COMPUT GRAPH STAT , 20 (3) 670 - 691. 10.1198/jcgs.2011.09058.

Hinton, G; Osindero, S; Welling, M; Teh, YW; (2006) Unsupervised discovery of nonlinear structure using contrastive backpropagation. COGNITIVE SCI , 30 (4) 725 - 731.

Hinton, GE; Osindero, S; Teh, YW; (2006) A fast learning algorithm for deep belief nets. NEURAL COMPUT , 18 (7) 1527 - 1554.

Teh, YW; Jordan, MI; Beal, MJ; Blei, DM; (2006) Hierarchical Dirichlet processes. J AM STAT ASSOC , 101 (476) 1566 - 1581. 10.1198/016214506000000302.

Teh, YW; Welling, M; Osindero, S; Hinton, GE; (2004) Energy-based models for sparse overcomplete representations. J MACH LEARN RES , 4 (7-8) 1235 - 1260. Gold open access

Welling, M; Teh, YW; (2004) Linear response algorithms for approximate inference in graphical models. NEURAL COMPUT , 16 (1) 197 - 221.

Welling, M; Teh, YW; (2003) Approximate inference in Boltzmann machines. ARTIFICIAL INTELLIGENCE , 143 (1) 19 - 50.

Wood, F; Gasthaus, J; Archambeau, C; James, L; Teh, YW; (2011) The Sequence Memoizer. COMMUN ACM , 54 (2) 91 - 98. 10.1145/1897816.1897842.

Book chapter

Blundell, C; Teh, YW; Heller, KA; (2011) Discovering non-binary hierarchical structures with Bayesian rose trees. In: Mengersen, K and Robert, CP and Titterington, M, (eds.) Mixture: Estimation and Applications. (pp. 161-187). John Wiley & Sons: Chichester, UK.

Orbanz, P; Teh, YW; (2010) Bayesian Nonparametric Models. In: Sammut, C and Webb, GI, (eds.) Encyclopedia of Machine Learning. (pp. 81-89). Springer

Teh, YW; (2010) Dirichlet Process. In: Sammut, C and Webb, GI, (eds.) Encyclopedia of Machine Learning. (pp. 280-287). Springer

Teh, YW; Jordan, MI; (2010) Hierarchical Bayesian Nonparametric Models with Applications. In: Hjort, N and Holmes, C and Müller, P and Walker, S, (eds.) Bayesian Nonparametrics: Principles and Practice. Cambridge University Press

Proceedings paper

Asuncion, AU; Welling, M; Smyth, P; Teh, YW; (2012) On Smoothing and Inference for Topic Models. In:

Bacchus, F; Teh, YW; (1998) Making Forward Chaining Relevant. In: Simmons, RG and Veloso, MM and Smith, SF, (eds.) (pp. pp. 54-61). AAAI

Berg, TL; Berg, AC; Edwards, J; Maire, M; White, R; Teh, YW; Learned-Miller, E; (2004) Names and faces in the news. In: PROCEEDINGS OF THE 2004 IEEE COMPUTER SOCIETY CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, VOL 2. (pp. 848 - 854). IEEE COMPUTER SOC

Blundell, C; Teh, YW; Heller, KA; (2012) Bayesian Rose Trees. In:

Cai, JF; Lee, WS; Teh, YW; (2007) Improving Word Sense Disambiguation Using Topic Features. In: (pp. 1015–1023-1015–1023).

Cai, JF; Lee, WS; Teh, YW; (2007) NUS-ML: Improving Word Sense Disambiguation Using Topic Features. In: (Proceedings) Proceedings of the International Workshop on Semantic Evaluations.

Chieu, HL; Lee, WS; Teh, YW; (2007) Cooled and Relaxed Survey Propagation for MRFs. In: Platt, JC and Koller, D and Singer, Y and Roweis, ST, (eds.) (pp. pp. 297-304). Curran Associates, Inc.

Doshi, F; Miller, K; Gael, JV; Teh, YW; (2009) Variational Inference for the Indian Buffet Process. In: Dyk, DAV and Welling, M, (eds.) (pp. pp. 137-144). JMLR.org

Edwards, J; Teh, YW; Forsyth, DA; Bock, R; Maire, M; Vesom, G; (2004) Making Latin Manuscripts Searchable using gHMMs. In: (pp. pp. 385-392).

Gael, JV; Saatci, Y; Teh, YW; Ghahramani, Z; (2008) Beam sampling for the infinite hidden Markov model. In: Cohen, WW and McCallum, A and Roweis, ST, (eds.) (pp. pp. 1088-1095). ACM

Gael, JV; Teh, YW; Ghahramani, Z; (2008) The Infinite Factorial Hidden Markov Model. In: Koller, D and Schuurmans, D and Bengio, Y and Bottou, L, (eds.) (pp. pp. 1697-1704). Curran Associates, Inc.

Gasthaus, J; Teh, YW; (2010) Improvements to the Sequence Memoizer. In: Lafferty, JD and Williams, CKI and Shawe-Taylor, J and Zemel, RS and Culotta, A, (eds.) (pp. pp. 685-693). Curran Associates, Inc.

Gasthaus, J; Wood, FD; Görür, D; Teh, YW; (2008) Dependent Dirichlet Process Spike Sorting. In: Koller, D and Schuurmans, D and Bengio, Y and Bottou, L, (eds.) (pp. pp. 497-504). Curran Associates, Inc.

Gasthaus, J; Wood, FD; Teh, YW; (2010) Lossless Compression Based on the Sequence Memoizer. In: Storer, JA and Marcellin, MW, (eds.) (pp. pp. 337-345). IEEE Computer Society

Görür, D; Teh, YW; (2008) An Efficient Sequential Monte Carlo Algorithm for Coalescent Clustering. In: Koller, D and Schuurmans, D and Bengio, Y and Bottou, L, (eds.) (pp. pp. 521-528). Curran Associates, Inc.

Haffari, G; Teh, YW; (2009) Hierarchical Dirichlet Trees for Information Retrieval. In: (pp. pp. 173-181). The Association for Computational Linguistics

Heller, KA; Teh, YW; Görür, D; (2009) Infinite Hierarchical Hidden Markov Models. In: Dyk, DAV and Welling, M, (eds.) (pp. pp. 224-231). JMLR.org

Hinton, GE; Ghahramani, Z; Teh, YW; (2000) Learning to parse images. In: Solla, SA and Leen, TK and Muller, KR, (eds.) ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 12. (pp. 463 - 469). M I T PRESS

Hinton, GE; Teh, YW; (2001) Discovering Multiple Constraints that are Frequently Approximately Satisfied. In: Breese, JS and Koller, D, (eds.) (pp. pp. 227-234). Morgan Kaufmann

Hinton, GE; Welling, M; Teh, YW; Osindero, S; (2001) A New View of ICA. In:

Kakade, S; Teh, YW; Roweis, ST; (2002) An Alternate Objective Function for Markovian Fields. In: Sammut, C and Hoffmann, AG, (eds.) (pp. pp. 275-282). Morgan Kaufmann

Kurihara, K; Welling, M; Teh, YW; (2007) Collapsed Variational Dirichlet Process Mixture Models. In: Veloso, MM, (ed.) 20TH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE (IJCAI-07), PROCEEDINGS. (pp. 2796 - 2801). IJCAI-INT JOINT CONF ARTIF INTELL

Lim, YJ; Teh, YW; (2007) Variational Bayesian Approach to Movie Rating Prediction. In: (Proceedings) KDD Cup and Workshop.

Quon, G; Teh, YW; Chan, ET; Hughes, TR; Brudno, M; Morris, Q; (2008) A mixture model for the evolution of gene expression in non-homogeneous datasets. In: Koller, D and Schuurmans, D and Bengio, Y and Bottou, L, (eds.) (pp. pp. 1297-1304). Curran Associates, Inc.

Rao, V; Teh, YW; (2009) Spatial Normalized Gamma Processes. In: Bengio, Y and Schuurmans, D and Lafferty, JD and Williams, CKI and Culotta, A, (eds.) (pp. pp. 1554-1562). Curran Associates, Inc.

Roy, DM; Teh, YW; (2008) The Mondrian Process. In: Koller, D and Schuurmans, D and Bengio, Y and Bottou, L, (eds.) (pp. pp. 1377-1384). Curran Associates, Inc.

Teh, Y.W.; (2006) A hierarchical Bayesian language model based on Pitman-Yor processes. In: Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the ACL. (pp. pp. 993-1000). Association for Computational Linguistics: Morristown, US.

Teh, YW; (2006) A Hierarchical Bayesian Language Model based on Pitman-Yor Processes. In: COLING/ACL 2006, VOLS 1 AND 2, PROCEEDINGS OF THE CONFERENCE. (pp. 985 - 992). ASSOC COMPUTATIONAL LINGUISTICS-ACL

Teh, YW; Görür, D; (2009) Indian Buffet Processes with Power-law Behavior. In: Bengio, Y and Schuurmans, D and Lafferty, JD and Williams, CKI and Culotta, A, (eds.) (pp. pp. 1838-1846). Curran Associates, Inc.

Teh, YW; Görür, D; Ghahramani, Z; (2007) Stick-breaking Construction for the Indian Buffet Process. In: (Proceedings) Proceedings of the International Conference on Artificial Intelligence and Statistics.

Teh, YW; Hinton, GE; (2001) Rate-coded restricted Boltzmann machines for face recognition. In: Leen, TK and Dietterich, TG and Tresp, V, (eds.) ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 13. (pp. 908 - 914). M I T PRESS

Teh, YW; III, HD; Roy, DM; (2007) Bayesian Agglomerative Clustering with Coalescents. In: Platt, JC and Koller, D and Singer, Y and Roweis, ST, (eds.) (pp. pp. 1473-1480). Curran Associates, Inc.

Teh, YW; Jordan, MI; Beal, MJ; Blei, DM; (2004) Sharing Clusters among Related Groups: Hierarchical Dirichlet Processes. In: (pp. pp. 1385-1392).

Teh, YW; Kurihara, K; Welling, M; (2007) Collapsed Variational Inference for HDP. In: Platt, JC and Koller, D and Singer, Y and Roweis, ST, (eds.) (pp. pp. 1481-1488). Curran Associates, Inc.

Teh, YW; Newman, D; Welling, M; (2006) A Collapsed Variational Bayesian Inference Algorithm for Latent Dirichlet Allocation. In: Schölkopf, B and Platt, JC and Hofmann, T, (eds.) (pp. pp. 1353-1360). MIT Press

Teh, YW; Roweis, ST; (2002) Automatic Alignment of Local Representations. In: Becker, S and Thrun, S and Obermayer, K, (eds.) (pp. pp. 841-848). MIT Press

Teh, YW; Seeger, MW; Jordan, MI; (2005) Semiparametric latent factor models. In: Cowell, RG and Ghahramani, Z, (eds.) Society for Artificial Intelligence and Statistics

Teh, YW; Welling, M; (2003) On Improving the Efficiency of the Iterative Proportional Fitting Procedure. In: Bishop, CM and Frey, BJ, (eds.) Society for Artificial Intelligence and Statistics

Teh, YW; Welling, M; (2002) The unified propagation and scaling algorithm. In: Dietterich, TG and Becker, S and Ghahramani, Z, (eds.) ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 14, VOLS 1 AND 2. (pp. 953 - 960). M I T PRESS

Welling, M; Minka, TP; Teh, YW; (2005) Structured Region Graphs: Morphing EP into GBP. In: (pp. pp. 609-614). AUAI Press

Welling, M; Rosen-Zvi, M; Teh, YW; (2004) Approximate inference by Markov chains on union spaces. In: Brodley, CE, (ed.) ACM

Welling, M; Teh, YW; (2004) Linear response for approximate inference. In: Thrun, S and Saul, K and Scholkopf, B, (eds.) ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 16. (pp. 361 - 368). M I T PRESS

Welling, M; Teh, YW; (2001) Belief Optimization for Binary Networks: A Stable Alternative to Loopy Belief Propagation. In: Breese, JS and Koller, D, (eds.) (pp. pp. 554-561). Morgan Kaufmann

Welling, M; Teh, YW; Kappen, B; (2008) Hybrid Variational/Gibbs Collapsed Inference in Topic Models. In: McAllester, DA and Myllymäki, P, (eds.) (pp. pp. 587-594). AUAI Press

Wood, FD; Archambeau, C; Gasthaus, J; James, L; Teh, YW; (2009) A stochastic memoizer for sequence data. In: Danyluk, AP and Bottou, L and Littman, ML, (eds.) (pp. pp. 1129-1136). ACM

Wood, FD; Teh, YW; (2009) A Hierarchical Nonparametric Bayesian Approach to Statistical Language Model Domain Adaptation. In: Dyk, DAV and Welling, M, (eds.) (pp. pp. 607-614). JMLR.org

Xing, EP; Sohn, K-A; Jordan, MI; Teh, YW; (2006) Bayesian multi-population haplotype inference via a hierarchical dirichlet process mixture. In: Cohen, WW and Moore, A, (eds.) (pp. pp. 1049-1056). ACM

Report

Lee, WS; Zhang, X; Teh, YW; (2006) Semi-supervised Learning in Reproducing Kernel Hilbert Spaces Using Local Invariances.

Seeger, M; Teh, YW; Jordan, MI; (2005) Semiparametric Latent Factor Models.

Silva, RBDAE; Blundell, C; Teh, YW; (2010) Mixed Cumulative Distribution Networks.

Teh, YW; (2006) A Bayesian Interpretation of Interpolated Kneser-Ney. : School of Computing, National University of Singapore.

Teh, YW; Welling, M; (2001) Passing and Bouncing Messages for Generalised Inference. Gatsby Computational Neuroscience Unit: London, UK.

Other

Teh, YW; (2003) Bethe Free Energy and Contrastive Divergence Approximations for Undirected Graphical Models. UNSPECIFIED

This list was generated on Sun Apr 21 14:52:17 2019 BST.