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Research Output 1987 2019

Article

Accurate parameter estimation for Bayesian network classifiers using hierarchical Dirichlet processes

Petitjean, F., Buntine, W., Webb, G. I. & Zaidi, N., Sep 2018, In : Machine Learning. 107, 8-10, p. 1303-1331 29 p.

Research output: Contribution to journalArticleResearchpeer-review

A Further Comparison of Splitting Rules for Decision-Tree Induction

Buntine, W. & Niblett, T., 1 Jan 1992, In : Machine Learning. 8, 1, p. 75-85 11 p.

Research output: Contribution to journalArticleResearchpeer-review

Analyzing the U.S. Senate in 2003: similarities, clusters, and blocs

Jakulin, A., Buntine, W. L., LaPira, T. M. & Brasher, H., 2009, In : Political Analysis. 17, p. 291 - 310 20 p.

Research output: Contribution to journalArticleResearchpeer-review

A segmented topic model based on the two-parameter Poisson-Dirichlet process

Du, L., Buntine, W. L. & Jin, H., 2010, In : Machine Learning. 81, 1, p. 5 - 19 15 p.

Research output: Contribution to journalArticleResearchpeer-review

Bibliographic analysis on research publications using authors, categorical labels and the citation network

Lim, K. W. & Buntine, W., 1 May 2016, In : Machine Learning. 103, 2, p. 185-213 29 p.

Research output: Contribution to journalArticleResearchpeer-review

Computing Second Derivatives in Feedforward Networks: A Review

Buntine, W. L. & Weigend, A. S., 1 Jan 1994, In : IEEE Transactions on Neural Networks. 5, 3, p. 480-488 9 p.

Research output: Contribution to journalArticleResearchpeer-review

Differential topic models

Chen, C., Buntine, W., Ding, N., Xie, L. & Du, L., Feb 2015, In : IEEE Transactions on Pattern Analysis and Machine Intelligence. 37, 2, p. 230 - 242 13 p.

Research output: Contribution to journalArticleResearchpeer-review

Efficient parameter learning of Bayesian network classifiers

Zaidi, N. A., Webb, G. I., Carman, M., Petitjean, F., Buntine, W., Hynes, M. & De Sterck, H., 2017, In : Machine Learning. 106, 9-10, p. 1289-1329 41 p.

Research output: Contribution to journalArticleResearchpeer-review

Experiments with learning graphical models on text

Capdevila, J., Zhao, E., Petitjean, F. & Buntine, W. L., Oct 2018, In : Behaviormetrika. 45, 2, p. 363-387 25 p.

Research output: Contribution to journalArticleResearchpeer-review

Generalized subsumption and its applications to induction and redundancy

Buntine, W., 1 Jan 1988, In : Artificial Intelligence. 36, 2, p. 149-176 28 p.

Research output: Contribution to journalArticleResearchpeer-review

Induction of Horn clauses: methods and the plausible generalization algorithm

Buntine, W., Apr 1987, In : International Journal of Man-Machine Studies. 26, 4, p. 499-519 21 p.

Research output: Contribution to journalArticleResearchpeer-review

Inductive knowledge acquisition and induction methodologies

Buntine, W., 1 Jan 1989, In : Knowledge-Based Systems. 2, 1, p. 52-61 10 p.

Research output: Contribution to journalArticleResearchpeer-review

Learning as applied to stochastic optimization for standard-cell placement

Su, L., Buntine, W., Newton, A. R. & Peters, B. S., 1 Apr 2001, In : IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 20, 4, p. 516-527 12 p.

Research output: Contribution to journalArticleResearchpeer-review

Learning classification trees

Buntine, W., 1 Jun 1992, In : Statistics and Computing. 2, 2, p. 63-73 11 p.

Research output: Contribution to journalArticleResearchpeer-review

Leveraging external information in topic modelling

Zhao, H., Du, L., Buntine, W. & Liu, G., 2019, (Accepted/In press) In : Knowledge and Information Systems. p. 1-33 33 p.

Research output: Contribution to journalArticleResearchpeer-review

Modelling default and likelihood reasoning as probabilistic reasoning

Buntine, W., 1 Mar 1991, In : Annals of Mathematics and Artificial Intelligence. 4, 1-2, p. 25-68 44 p.

Research output: Contribution to journalArticleResearchpeer-review

Nonparametric Bayesian topic modelling with the hierarchical Pitman–Yor processes

Lim, K. W., Buntine, W., Chen, C. & Du, L., 1 Nov 2016, In : International Journal of Approximate Reasoning. 78, p. 172-191 20 p.

Research output: Contribution to journalArticleResearchpeer-review

On Solving Equations and Disequations

Buntine, W. L. & Bürckert, H. J., 7 Jan 1994, In : Journal of the ACM (JACM). 41, 4, p. 591-629 39 p.

Research output: Contribution to journalArticleResearchpeer-review

Sequential latent Dirichlet allocation

Du, L., Buntine, W. L., Jin, H. & Chen, C., 2012, In : Knowledge and Information Systems. 31, 3, p. 475 - 503 29 p.

Research output: Contribution to journalArticleResearchpeer-review

Towards a methodology for nursing-specific clinical decision support systems (CDSS)

Ahamed, T., Lederman, R., Bosua, R., Verspoor, K., Buntine, W. & Hart, G., 10 Jun 2016, In : Journal of Decision Systems. 25, S1, p. 23-34 12 p.

Research output: Contribution to journalArticleResearchpeer-review

Unsupervised object discovery: a comparison

Tuytelaars, T., Lampert, C. H., Blaschko, M. B. & Buntine, W. L., 2010, In : International Journal of Computer Vision. 88, 2, p. 284 - 302 19 p.

Research output: Contribution to journalArticleResearchpeer-review

Chapter (Book)

Dirichlet belief networks for topic structure learning

Zhao, H., Du, L., Buntine, W. & Zhou, M., 2018, NIPS Proceedings: Advances in Neural Information Processing Systems 31 (NIPS 2018). Bengio, S., Wallach, H., Larochelle, H., Grauman, K., Cesa-Bianchi, N. & Garnett, R. (eds.). San Diego CA USA: Neural Information Processing Systems (NIPS), p. 7966-7977 12 p.

Research output: Chapter in Book/Report/Conference proceedingChapter (Book)Researchpeer-review

Open Access
File
Conference article

Adaptive methods for netlist partitioning

Buntine, W. L., Su, L., Newton, A. R. & Mayer, A., 1 Dec 1997, In : IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers. p. 356-363 8 p.

Research output: Contribution to journalConference articleResearchpeer-review

Conference Paper

Adaptive knowledge sharing in multi-task learning: improving low-resource neural machine translation

Zaremoodi, P., Buntine, W. & Haffari, G., 2018, ACL 2018 - The 56th Annual Meeting of the Association for Computational Linguistics: Proceedings of the Conference, Vol. 2 (Short Papers). Gurevych, I. & Miyao, Y. (eds.). Stroudsburg PA USA: Association for Computational Linguistics (ACL), p. 656-661 6 p.

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Open Access
File

A fusion of predicate logic and document semantic distance method orientated on data and context mapping

Liu, G., Sun, S., Buntine, W. & Yang, X., 2015, Proceedings of 2015 4th International Conference on Computer Science and Network Technology, ICCSNT 2015: December 19-20, 2015 Harbin, China. Guo, L. (ed.). Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, p. 645-651 7 p. 2541

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearch

A left-to-right algorithm for likelihood estimation in gamma-poisson factor analysis

Capdevila, J., Cerquides, J., Torres, J., Petitjean, F. & Buntine, W., 2019, Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2018 Dublin, Ireland, September 10–14, 2018 Proceedings, Part II. Berlingerio, M., Bonchi, F., Gärtner, T., Hurley, N. & Ifrim, G. (eds.). Cham Switzerland: Springer, p. 638-654 17 p. (Lecture Notes in Computer Science ; vol. 11052 ).

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

ALVIS - Superpeer semantic search engine - ECDL 2006 demo submission

Pedersen, G. S., Ardö, A., Cromme, M., Taylor, M. & Buntine, W., 1 Jan 2006, 2nd International Workshop on Parameterized and Exact Computation, IWPEC 2006. Springer-Verlag London Ltd., p. 461-462 2 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 4172 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

A scalable topic-based open source search engine

Buntine, W., Löfström, J., Perkiö, J., Perttu, S., Poroshin, V., Silander, T., Tirri, H., Tuominen, A. & Tuulos, V., 1 Dec 2004, Proceedings - IEEE/WIC/ACM International Conference on Web Intelligence, WI 2004. Zhong, N., Tirri, H., Yao, Y. & Zhou, L. (eds.). p. 228-234 7 p.

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

A temporally adaptive content-based relevance ranking algorithm

Perkiö, J., Buntine, W. & Tirri, H., 1 Dec 2005, SIGIR 2005 - Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. Association for Computing Machinery (ACM), p. 647-648 2 p. (SIGIR 2005 - Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval).

Research output: Chapter in Book/Report/Conference proceedingConference PaperOtherpeer-review

Automated synthesis of data analysis programs: learning in logic

Buntine, W., 2004, 14th International Conference ILP 2004: Inductive Logic Programming; : Porto; Portugal; 6 September 2004 through 8 September 2004. Springer, 1 p. (Lecture Notes in Computer Science; vol. 3194).

Research output: Chapter in Book/Report/Conference proceedingConference PaperOtherpeer-review

Automatic derivation of statistical algorithms: The EM family and beyond

Gray, A. G., Fischer, B., Schumann, J. & Buntine, W., 1 Jan 2003, Advances in Neural Information Processing Systems 15 - Proceedings of the 2002 Conference, NIPS 2002. Neural information processing systems foundation

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

A Word Embeddings Informed Focused Topic Model

Zhao, H., Du, L. & Buntine, W., 2017, 2017 Ninth Asian Conference on Machine Learning, ACML 2017: 15-17 November 2017, Seoul, Korea, Proceedings. Zhang, M-L. & Noh, Y-K. (eds.). USA: Proceedings of Machine Learning Research (PMLR), p. 423-438 16 p. (Proceedings of Machine Learning Research; vol. 77).

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearch

Open Access

Bayesian Multi-label Learning with Sparse Features and Labels, and Label Co-occurrences

Zhao, H., Rai, P., Du, L. & Buntine, W., 2018, 2018 Twenty-First International Conference on Artificial Intelligence and Statistics, AISTATS 2018 : 9-11 April 2018, Lanzarote, Canary Islands, Proceedings . Storkey, A. & Perez-Cruz, F. (eds.). USA: Proceedings of Machine Learning Research (PMLR), p. 1943-1951 9 p. (Proceedings of Machine Learning Research; vol. 84).

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Open Access

Bayesian networks on dirichlet distributed vectors

Buntine, W. L., Du, L. & Nurmi, P., 2010, Proceedings of the Fifth European Workshop on Probabilistic Graphical Models. Myllymaki, P., Roos, T. & Jaakkola, T. (eds.). Helsinki Finland: Helsinki Institute for Information Technology, p. 33 - 40 8 p.

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Bibliographic analysis with the citation network topic model

Lim, K. W. & Buntine, W. L., 2014, Proceedings of the Sixth Asian Conference on Machine Learning (ACML 2014). Li, H. & Phung, D. (eds.). Journal of Machine Learning Research (Online) USA: JMLR Workshop and Conference Proceedings, p. 142 - 158 17 p.

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Dependent hierarchical normalized random measures for dynamic topic modeling

Chen, C., Ding, N. & Buntine, W. L., 2012, Proceedings of the 29th International Conference on Machine Learning (ICML 2012). Langford, J. & Pineau, J. (eds.). Edinburgh Scotland UK: Journal of Machine Learning Research (JMLR), p. 895 - 902 8 p.

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Dependent normalized random measures

Chen, C., Rao, V., Buntine, W. & Teh, Y. W., 2013, Proceedings of the 30th International Conference on Machine Learning (ICML 2013): June 16 – June 21, 2013, Atlanta, Georgia, USA. Dasgupta, S. & McAllester, D. (eds.). International Machine Learning Society (IMLS), p. 2006-2014 9 p.

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Discrete component analysis

Buntine, W. & Jakulin, A., 1 Jan 2006, Subspace, Latent Structure and Feature Selection - Statistical and Optimization Perspectives Workshop, SLSFS 2005, Revised Selected Papers. Springer-Verlag London Ltd., p. 1-33 33 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 3940 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Estimating likelihoods for topic models

Buntine, W. L., 2009, Advances in Machine Learning: First Asian Conference on Machine Learning, ACML 2009, Proceedings. Zhou, Z-H. & Washio, T. (eds.). Berlin Germany: Springer-Verlag London Ltd., p. 51 - 64 14 p.

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Experiments with non-parametric topic models

Buntine, W. L. & Mishra, S., 2014, KDD'14: Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Leskovec, J. & Wang, W. (eds.). New York NY USA: Association for Computing Machinery (ACM), p. 881 - 890 10 p.

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Exploring independent trends in a topic-based search engine

Perkiö, J., Buntine, W. & Perttu, S., 2004, Proceedings - IEEE/WIC/ACM International Conference on Web Intelligence, WI 2004: Beijing; China; 20 September 2004 through 24 September 2004. Zhong, N., Tirri, H., Yao, Y. & Zhou, L. (eds.). IEEE, Institute of Electrical and Electronics Engineers, p. 664-668 5 p.

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Improving LDA topic models for microblogs via tweet pooling and automatic labeling

Mehrotra, R., Sanner, S. P., Buntine, W. L. & Xie, L., 2013, Proceedings of the 36th International ACM SIGIR Conference on Research & Development in Information Retrieval (SIGIR 2013). Kelly, D., de Rijke, M. & Sakai, T. (eds.). New York NY USA: Association for Computing Machinery (ACM), p. 889 - 892 4 p.

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Improving topic coherence with regularized topic models

Newman, D., Bonilla, E. V. & Buntine, W. L., 2011, Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011 (NIPS 2011): Volume 1 of 3. Shawe-Taylor, J., Zemel, R., Bartlett, P. & Pereira, F. (eds.). LaJolla CA USA: Neural Information Processing Systems (NIPS), p. 1 - 9 9 p.

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Inter and intra topic structure learning with word embeddings

Zhao, H., Du, L., Buntine, W. & Zhou, M., 2018, Proceedings of Machine Learning Research: International Conference on Machine Learning, 10-15 July 2018, Stockholmsmässan, Stockholm Sweden. Dy, J. & Krause, A. (eds.). Stockholmsmässan Stockholm Sweden: Proceedings of Machine Learning Research (PMLR), Vol. 80. 10 p. (Proceedings of Machine Learning Research).

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Open Access
File

Kernel conditional quantile estimation via reduction revisited

Quadrianto, N., Kersting, K., Reid, M. D., Caetano, T. S. & Buntine, W. L., 2009, Proceedings - IEEE International Conference on Data Mining, ICDM. Wang, W., Kargupta, H., Ranka, S., Yu, P. S. & Wu, X. (eds.). Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, p. 938 - 943 6 p.

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Learning how to actively learn: a deep imitation learning approach

Liu, M., Buntine, W. & Haffari, G., 2018, ACL 2018 - The 56th Annual Meeting of the Association for Computational Linguistics: Proceedings of the Conference, Vol. 1 (Long Papers). Gurevych, I. & Miyao, Y. (eds.). Stroudsburg PA USA: Association for Computational Linguistics (ACL), p. 1874-1883 10 p.

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Open Access
File

Learning to actively learn neural machine translation

Liu, M., Buntine, W. & Haffari, G., 2018, CoNLL 2018 - The 22nd Conference on Computational Natural Language Learning - Proceedings of the Conference: October 31 - November 1, 2018 Brussels, Belgium. Silfverberg, M. (ed.). Stroudsburg PA USA: The Association for Computational Linguistics, p. 334-344 11 p.

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Open Access
File

Leveraging linguistic resources for improving neural text classification

Liu, M., Haffari, G., Buntine, W. & Ananda-Rajah, M., 2017, Australasian Language Technology Association Workshop, ALTA 2017: 6–8 December 2017, Brisbane, Australia, Proceedings . Wong, J. S-M. & Haffari, G. (eds.). 2017 ed. Melbourne Victoria Australia: Australian Language Technology Association (ALTA), Vol. 15. p. 34-42 9 p.

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearch

Leveraging node attributes for incomplete relational data

Zhao, H., Du, L. & Buntine, W., 2017, International Conference on Machine Learning, 6-11 August 2017, International Convention Centre, Sydney, Australia. Precup, D. & Teh, Y. W. (eds.). USA: Proceedings of Machine Learning Research (PMLR), p. 4072-4081 10 p. (Proceedings of Machine Learning Research; vol. 70).

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Open Access
File

Leveraging node attributes for incomplete relational data

Zhao, H., Du, L. & Buntine, W., 6 Aug 2017, 34th International Conference on Machine Learning (ICML 2017): Sydney, Australia - 6-11 August 2017. Precup, D. & Teh, Y. W. (eds.). Stroudsburg PA USA: International Machine Learning Society (IMLS), Vol. 8. p. 6176-6185 10 p.

Research output: Chapter in Book/Report/Conference proceedingConference PaperOtherpeer-review