PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

EPrints submitted by Wray Buntine

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Number of EPrints submitted by this user: 75

Estimating Likelihoods for Topic Models
Wray Buntine
In: ACML 2009, 3-5 Nov 2009, Nanjing, China.

Analyzing the U.S. Senate in 2003: Similarities, Clusters, and Blocs
Aleks Jakulin, Wray Buntine, Timothy La Pira and Holly Brasher
Political Analysis Volume 17, Number 3, pp. 291-310, 2009. ISSN 1047-1987

A Bayesian Review of the Poisson-Dirichlet Process
Wray Buntine and Marcus Hutter
(2010) Technical Report. Cornell UNiversity Library, USA.

Real-time Multiattribute Bayesian Preference Elicitation with Pairwise Comparison Queries
Shengbo Guo and Scott Sanner
In: NIPS 2009, 7-12 Dec 2009, Vancouver, Canada.

Real-time Multiattribute Bayesian Preference Elicitation with Pairwise Comparison Queries
Shengbo Guo and Scott Sanner
In: AISTATS 2010, 13-15 May 2010, Sardinia, Italy.

Ranking in the algebra of the symmetric group
Risi Kondor and Marconi Barbosa
In: NIPS 2009, 7-12 Dec 2009, Vancouver, Canada.

Online Learning for Multi-label and Multi-variate Performance Measures
X Zhang, T Graepel and R Herbrich
In: 13th International Conference on Artificial Intelligence and Statistics (AISTATS)(2010).

Model Selection with the Loss Rank Principle
Marcus Hutter and M Tran
Computational Statistics and Data Analysis Volume 54, pp. 1288-1306, 2010.

Rapid Face Recognition Using Hashing
Q Shi, Hanxi Li and Chunhua Shen
In: Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR), San Francisco, USA(2010).

Ranking with kernels in Fourier space
Risi Kondor and M Barbosa
In: Computational Learning Theory (COLT), Haifa, Israel(2010).

Reverse Multi-Label Learning
James Petterson and Tiberio Caetano
In: Advances in Neural Information Processing Systems (NIPS)(2011).

Word Features for Latent Dirichlet Allocation
James Petterson, A.J. Smola, Tiberio Caetano, Wray Buntine and S Narayanamurthy
In: Advances in Neural Information Processing Systems (NIPS)(2011).

Multitask Learning without Label Correspondences
Novi Quadrianto, A.J. Smola, Tiberio Caetano, S.V.N. Vishwanathan and James Petterson
In: Advances in Neural Information Processing Systems (NIPS)(2011).

Graphical Models
Julian McAuley, Tiberio Caetano and Wray Buntine
In: Encyclopedia of Machine Learning (2010) Springer .

Bayesian networks on Dirichlet distributed vectors
Wray Buntine, Lan Du and Petteri Nurmi
In: Proceedings of the 5th European Workshop on Probabilistic Graphical Models (PGM-10), Helsinki, Finland(2010).

A segmented topic model based on the two-parameter Poisson-Dirichlet process
Lan Du, Wray Buntine and H Jin
Machine Learning Journal Volume 81, Number 1, pp. 5-19, 2010.

A Segmented Topic Model based on the Two-parameter Poisson-Dirichlet Process
Lan Du, Wray Buntine and H Jin
In: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2010, Barcelona, Spain.

Wearable-sensor activity analysis using semi-Markov models with a grammar
O Thomas, Peter Sunehag, G Dror, S Yun, S Kim, M Robards, A.J. Smola, D Green and P Saunders
Pervasive and Mobile Computing 2010.

Symbolic Dynamic Programming for First-order POMDPs
Scott Sanner and Kristian Kersting
In: Proceedings of the 24th AAAI Conference on Artificial Intelligence (AAAI-10)(2010).

Temporal Difference Bayesian Model Averaging: A Bayesian Perspective on Adapting Lambda
C Downey and Scott Sanner
In: Proceedings of the 27th International Conference on Machine Learning (ICML-10)(2010).

Approximate Dynamic Programming with Affine ADDs
Scott Sanner, W Uther and KV Delgado
In: Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS-10), Toronto, Canada(2010).

Gaussian Process Preference Elicitation
Edwin Bonilla, Shengbo Guo and Scott Sanner
In: Proceedings of the 24th Annual Conference on Neural Information Processing Systems (NIPS-10), Vancouver, Canada(2010).

Composite Binary Losses
Mark Reid and Bob Williamson
Journal of Machine Learning Research Volume 11, 2010.

Generalization Bounds 
Mark Reid
(2010) Springer .

Squinting at a Sea of Dots: Visualising Australian Readerships using Statistical Machine Learning
JV Lamond and Mark Reid
In: Resourceful Reading: The New Empiricism (2010) Sydney University Press , Sydney, Australia , pp. 223-240.

Convexity of Proper Composite Binary Losses
Mark Reid and Bob Williamson
In: Proceedings of the 13th International Conference on Artificial Intelligence and Statistics (AISTATS), Sardinia, Italy(2010).

Optimal Web-scale Tiering as a Flow Problem
G Leung, Novi Quadrianto, AJ Smola and K Tsioutsiouliklis
In: Advances in Neural Information Processing Systems (NIPS)(2011).

Beyond 2D-grids: a dependence maximization view on image browsing
Novi Quadrianto, Kristian Kersting, Tinne Tuytelaars and Wray Buntine
In: Proceedings of the international conference on Multimedia information retrieval, ACM, New York, NY(2010).

State Estimation Schemes for Independent Component Coupled Hidden Markov Models
WP Malcolm, Novi Quadrianto and Aggoun L
Stochastic Analysis and Applications Volume 28, Number 3, pp. 430-446, 2010.

Bayesian Online Learning for Multi-label and Multi-variate Performance Measures
X Zhang, T Graepel and R Herbrich
In: Proceedings of the 13th International Conference on Artificial Intelligence and Statistics (AISTATS)(2010).

Information, Divergence and Risk for Binary Experiments
Mark Reid and Bob Williamson
Journal of Machine Learning Research Volume 12, pp. 731-817, 2009.

Attribute-based Vehicle Search in Crowded Surveillance Videos
F Rogerio, S Behjat, Z Yun, James Petterson, B Lisa and P Sharath
In: ACM International Conference on Multimedia Retrieval (ICMR), 1-8 April 2011, Trento, Italy.

Using Mathematical Programming to Solve Factored Markov Decision Processes with Imprecise Probabilities
K Delgado Valdivia, L de Barros, F Cozman and Scott Sanner
International Journal of Approximate Reasoning Volume 1, Number 1, pp. 1-30, 2011.

Supporting Communication and Decision Making in Finnish Intensive Care with Language Technology
Hanna Suominen and T Salakoski
In: Journal of Healthcare Engineering (2010) Multi-Science Publishing Co. Ltd , Essex, UK , pp. 595-614.

Mixability is Bayes Risk Curvature Relative to Log Loss
T van Erven, Mark Reid and Bob Williamson
In: 24th Annual Conference on Learning Theory, July 2011, Budapest.

Characteristics of Finnish and Swedish intensive care nursing narratives: a comparative analysis to support the development of clinical language technologies
H Allvin, E Carlsson, H Dalianis, R Danielsson-Ojala, V Daudaravičius, M Hassel, D Kokkinakis, H Lundgrén-Laine, G Nilsson, A Nytra, S Salanterä, M Skeppstedt, Hanna Suominen and S Velupillai
Journal of Biomedical Semantics Volume Suppl 3, Number 2, 2011.

Machine Intelligence for Health Information: Capturing Concepts & Trends in Social Media via Query Expansion
X Su, Hanna Suominen and Leif Hanlen
In: Health Informatics Conference 2011 (HIC 2011),, August 2011, Brisbane Australia.

Sampling Table Configurations for the Hierarchical Poisson-Dirichlet Process
Changyou Chen, L Du and Wray Buntine
In: Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2011, Athens Greece(2011).

Sparse Kernel-SARSA(lambda) with an Eligibility Trace
M Robards, Peter Sunehag, Scott Sanner and B Marthi
In: European Conference on Machine Learning (ECML), 1-8 September 2011, Athens Greece.

Composite Binary Losses
Mark Reid and Bob Williamson
Journal of Machine Learning Research Number 11, pp. 2387-2422, 2010.

Diverse Retrieval via Greedy Optimization of Expected 1-call@k in a Latent Subtopic Relevance Model
Scott Sanner, S Guo, T Graepel, S Kharazmi and S Karimi
In: 20th ACM Conference on Information and Knowledge Management, October 2011, Glasgow UK.

Composite Multiclass Losses
E Vermet, Bob Williamson and Mark Reid
In: NIPS 2011, December 2011, Grenada Spain.

Submodular Multi-Label Learning
James Petterson and Tiberio Caetano
In: NIPS 2011, December 2011, Granada Spain.

Improving Topic Coherence with Regularized Topic Models
D Newman, Edwin Bonilla and Wray Buntine
In: Neural Information Processing Systems (NIPS), December 2011, Granada Spain.

Sparse Gaussian Processes for Learning Preferences
Ehsan Abbasnejad, Edwin Bonilla and Scott Sanner
In: NIPS, Choice Models and Preference Learning Workshop, December 2011, Granada Spain.

Exact Bayesian Pairwise Preference Learning and Inference on the Uniform Convex Polytope
Scott Sanner and Ehsan Abbasnejad
In: NIPS Workshop on Choice Models and Preference Learning, December 2011, Granada Spain.

Fast On-line Statistical Learning on a GPGPU
F Xiao, E McCreath and Christfried Webers
In: 9th Australasian Symposium on Parallel and Distributed Computing,, January 2011, Perth Australia.

Large-Scale Vehicle Detection in Challenging Urban Surveillance Environments
R Feris, James Petterson, B Siddiquie, L Brown and S Pankanti
In: IEEE Workshop on Applications of Computer Vision (WACV), January 2011, Kona Hawaii.

A Monte-Carlo AIXI Approximation
J Veness, K Ng, Marcus Hutter, William Uther and D Silva
Journal of Artificial Intelligence Research Volume 40, pp. 95-142, 2011.

On the Mathematical Relationship between Expected n-call@k and the Relevance vs. Diversity Trade-off
Kar Wai Lim, Scott Sanner and Shengbo Guo
35th ACM SIGIR conference on Research and development in information retrieval pp. 1117-1118, 2012. ISSN 978-1-4503-1472-5

Modelling Sequential Text with an Adaptive Topic Model
Lan Du, Wray Buntine and Huidong Jin
In: Empirical Methods in Natural Language Processing (EMNLP), 12-14 July 2012, Jeju, Korea.

Predicting Best Design Trade-offs: A Case Study in Processor Customization
Marcela Zuluaga, Edwin Bonilla and Nigel Topham
In: Design, Automation and Test in Europe, Mar 2012, Germany.

New Objective Functions for Social Collaborative Filtering
Joseph Noel, Scott Sanner, Khoi-Nguyen Tran, Peter Christen, Lexing Xie, Edwin Bonilla, Ehsan Abbasnejad and Nic Della Penna
In: International World Wide Web Conference, 16 Apr - 20 Apr 2012, Lyon, France.

Mixability is Bayes Risk Curvature Relative to Log Loss
Tim van Erven, Mark Reid and Bob Williamson
Journal of Machine Learning Research Volume 13, Number May, pp. 1639-1663, 2012.

A Survey of the Seventh International Planning Competition
Amanda Coles, Andrew Coles, Angel Garcia Olaya, Sergio Jimenez, Carlos Linares Lopez, Scott Sanner and Sungwook Yoon
AI Magazine Volume 33, Number 1, pp. 1-8, 2012.

Recent Advances in Reinforcement Learning - 9th European Workshop, EWRL 2011
Scott Sanner and Marcus Hutter
(2012) Lecture Notes in Computer Science . Springer . ISBN 978-3-642-29945-2

Tighter Variational Representations of f-Divergences via Restriction to Probability Measures
Avraham Ruderman, Dario Garcia, James Petterson and Mark Reid
In: International Conference on Machine Learning 2012, June 26–July 1, 2012, Edinburgh, Scotland.

Divergences and Risks for Multiclass Experiments
Dario Garcia and Bob Williamson
In: Conference on Learning Theory, June 25–June 27, 2012, Edinburgh, Scotland.

Discriminative Probabilistic Prototype Learning
Edwin Bonilla and Antonio Robles-Kelly
In: International Conference on Machine Learning, une 26–July 1, 2012, Edinburgh, Scotland.

Dependent Hierarchical Normalized Random Measures for Dynamic Topic Modeling
Changyou Chen, Nan Ding and Wray Buntine
In: International Conference on Machine Learning, June 26–July 1, 2012, Edinburgh, Scotland.

The Convexity and Design of Composite Multiclass Losses
Mark Reid, Bob Williamson and Peng Sun
In: International Conference on Machine Learning 2012, June 26–July 1, 2012, Edinburgh, Scotland.

AOSO-LogitBoost: Adaptive One-Vs-One LogitBoost for Multiclass Problem
Peng Sun, Mark Reid and Jie Zhou
In: International Conference on Machine Learning 2012, June 26–July 1, 2012, Edinburgh, Scotland.

Item Fields -- A Probabilistic Neighbourhood Approach to Collaborative Filtering with Undirected Graphical Models
Aaron Defazio and Tiberio Caetano
In: International Conference on Machine Learning 2012, June 26–July 1, 2012, Edinburgh, Scotland.

Efficient Cross-validation for Kernelized Least-Squares Regression with Sparse Basis Expansions
Tapio Pahikkala, Hanna Suominen and Jorma Boberg
Machine Learning Volume 87, Number 3, pp. 786-787, 2012.

Symbolic Dynamic Programming for Continuous State and Action MDPs
Zahra Zamani and Scott Sanner
In: Conference on Artificial Intelligence (AAAI) 2012, July 22–26, 2012, Toronto, Canada.

Symbolic Variable Elimination for Discrete and Continuous Graphical Models
Scott Sanner and Ehsan Abbasnejad
In: Conference on Artificial Intelligence (AAAI) 2012, July 22–26, 2012, Toronto, Canada.

On the Mathematical Relationship between Expected n-call@k and the Relevance vs. Diversity Trade-off
Kar Wai Lim, Scott Sanner and Shengbo Guo
In: SIGIR 2012, August 12-16, 2012, Portland, Oregon.

Reassignment-Based Strategy-Proof Mechanisms for Interdependent Task Allocation
Ayman Ghoneim
In: The 15th International Conference on Principles and Practice of Multi-Agent Systems (PRIMA-2012), September 3 - 7, 2012, Kuching, Sarawak, Malaysia.

CLEFeHealth2012: The CLEF 2012 Workshop on Cross-Language Evaluation of Methods, Applications, and Resources for eHealth Document Analysis
Hanna Suominen
In: CLEF 2012, 17-20 September 2012, Rome, Italy.

Score-based Bayesian Skill Learning
Shengbo Guo, Scott Sanner, Thore Graepel and Wray Buntine
In: European Conference on Machine Learning, 24-28 September 2012, Bristol, UK.

Analyzing Social Media via Event Facets
Zhiyu Wang, Peng Cui, Lexing Xie, Hao Chen, Wenwu Zhu and Shiqiang Yang
In: ACM Multimedia 2012, 29 Oct - 2 Nov 2012, Nara, Japan.

Bayesian data fusion for geothermal exploration
Fabio Ramos, Edwin Bonilla, Simon O'Callaghan, Alistair Reid, William Uther, Malcolm Sambridge and Tim Rawling
In: Australian Geothermal Energy Conference 2012, 14 Nov - 16 Nov 2012, NSW, Australia.

A Convex Formulation for Learning Scale-Free Networks via Submodular Relaxation
Aaron Defazio and Tiberio Caetano
In: Neural Information Processing Systems 2012, 3 Dec - 8 Dec 2012, Nevada, United States.

Symbolic Dynamic Programming for Continuous State and Observation POMDPs
Zahra Zamani and Scott Sanner
In: Neural Information Processing Systems 2012, 3 Dec - 8 Dec 2012, Nevada, United States.

Interpreting Prediction Markets: A Stochastic Approach
Rafael Frongillo, Nicolás Della Penna and Mark Reid
In: Neural Information Processing Systems 2012, 3 Dec - 8 Dec 2012, Nevada, United States.