Wray L. Buntine

Orcid: 0000-0001-9292-1015

Affiliations:
  • Monash University, Melbourne, Australia


According to our database1, Wray L. Buntine authored at least 168 papers between 1976 and 2024.

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Bibliography

2024
Bayesian Estimate of Mean Proper Scores for Diversity-Enhanced Active Learning.
IEEE Trans. Pattern Anal. Mach. Intell., May, 2024

Enhancing Educational Dialogue Act Classification With Discourse Context and Sample Informativeness.
IEEE Trans. Learn. Technol., 2024

Improving Vietnamese-English Medical Machine Translation.
CoRR, 2024

OntoMedRec: Logically-Pretrained Model-Agnostic Ontology Encoders for Medication Recommendation.
CoRR, 2024

Towards Uncertainty-Aware Language Agent.
CoRR, 2024

Reward Engineering for Generating Semi-structured Explanation.
Proceedings of the Findings of the Association for Computational Linguistics: EACL 2024, 2024

Harnessing the Power of Beta Scoring in Deep Active Learning for Multi-Label Text Classification.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
A systematic review of the use of topic models for short text social media analysis.
Artif. Intell. Rev., December, 2023

HOMOE: A Memory-Based and Composition-Aware Framework for Zero-Shot Learning with Hopfield Network and Soft Mixture of Experts.
CoRR, 2023

Open-Set Graph Anomaly Detection via Normal Structure Regularisation.
CoRR, 2023

PiVe: Prompting with Iterative Verification Improving Graph-based Generative Capability of LLMs.
CoRR, 2023

A Survey on Out-of-Distribution Evaluation of Neural NLP Models.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

MEG: Masked Ensemble Tabular Data Generator.
Proceedings of the IEEE International Conference on Data Mining, 2023

Low-Resource Named Entity Recognition: Can One-vs-All AUC Maximization Help?
Proceedings of the IEEE International Conference on Data Mining, 2023

Does Informativeness Matter? Active Learning for Educational Dialogue Act Classification.
Proceedings of the Artificial Intelligence in Education - 24th International Conference, 2023

Robust Educational Dialogue Act Classifiers with Low-Resource and Imbalanced Datasets.
Proceedings of the Artificial Intelligence in Education - 24th International Conference, 2023

Cross-Domain Graph Anomaly Detection via Anomaly-Aware Contrastive Alignment.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

AUC Maximization for Low-Resource Named Entity Recognition.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Understanding Hierarchical Processes.
Entropy, December, 2022

SQAPlanner: Generating Data-Informed Software Quality Improvement Plans.
IEEE Trans. Software Eng., 2022

Unsupervised Sentence Simplification via Dependency Parsing.
CoRR, 2022

Hands-On Bayesian Neural Networks - A Tutorial for Deep Learning Users.
IEEE Comput. Intell. Mag., 2022

Inductive Biases for Low Data VQA: A Data Augmentation Approach.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, 2022

ENDASh: Embedding Neighbourhood Dissimilarity with Attribute Shuffling for Graph Anomaly Detection.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2022

Hardness-guided domain adaptation to recognise biomedical named entities under low-resource scenarios.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

On the Effect of Isotropy on VAE Representations of Text.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2022

2021
Citation context-based topic models: discovering cited and citing topics from full text.
Libr. Hi Tech, 2021

Content-Aware Listwise Collaborative Filtering.
Neurocomputing, 2021

The Neglected Sibling: Isotropic Gaussian Posterior for VAE.
CoRR, 2021

Temporal Cascade and Structural Modelling of EHRs for Granular Readmission Prediction.
CoRR, 2021

Recommending content using side information.
Appl. Intell., 2021

Diversity Enhanced Active Learning with Strictly Proper Scoring Rules.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Topic Model or Topic Twaddle? Re-evaluating Semantic Interpretability Measures.
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Topic Modelling Meets Deep Neural Networks: A Survey.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Neural Topic Model via Optimal Transport.
Proceedings of the 9th International Conference on Learning Representations, 2021

Multilingual Neural Machine Translation: Can Linguistic Hierarchies Help?
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

Transformer over Pre-trained Transformer for Neural Text Segmentation with Enhanced Topic Coherence.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

Neural Attention-Aware Hierarchical Topic Model.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

All Labels Are Not Created Equal: Enhancing Semi-Supervision via Label Grouping and Co-Training.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020
Bayesian network classifiers using ensembles and smoothing.
Knowl. Inf. Syst., 2020

LoRMIkA: Local rule-based model interpretability with k-optimal associations.
Inf. Sci., 2020

Machine learning after the deep learning revolution.
Frontiers Comput. Sci., 2020

Discriminative, Generative and Self-Supervised Approaches for Target-Agnostic Learning.
CoRR, 2020

Neural Sinkhorn Topic Model.
CoRR, 2020

Hierarchical Gradient Smoothing for Probability Estimation Trees.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2020

Robust Attribute and Structure Preserving Graph Embedding.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2020

MedGraph: Structural and Temporal Representation Learning of Electronic Medical Records.
Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

Collective Wisdom: Improving Low-resource Neural Machine Translation using Adaptive Knowledge Distillation.
Proceedings of the 28th International Conference on Computational Linguistics, 2020

Variational Autoencoders for Sparse and Overdispersed Discrete Data.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Gaussian Embedding of Large-Scale Attributed Graphs.
Proceedings of the Databases Theory and Applications, 2020

2019
Leveraging external information in topic modelling.
Knowl. Inf. Syst., 2019

Variational Autoencoders for Sparse and Overdispersed Discrete Data.
CoRR, 2019

Leveraging Meta Information in Short Text Aggregation.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018
Accurate parameter estimation for Bayesian network classifiers using hierarchical Dirichlet processes.
Mach. Learn., 2018

A Left-to-Right Algorithm for Likelihood Estimation in Gamma-Poisson Factor Analysis.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

Dirichlet belief networks for topic structure learning.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Inter and Intra Topic Structure Learning with Word Embeddings.
Proceedings of the 35th International Conference on Machine Learning, 2018

Learning to Actively Learn Neural Machine Translation.
Proceedings of the 22nd Conference on Computational Natural Language Learning, 2018

Bayesian Multi-label Learning with Sparse Features and Labels, and Label Co-occurrences.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Distinguishing Question Subjectivity from Difficulty for Improved Crowdsourcing.
Proceedings of The 10th Asian Conference on Machine Learning, 2018

Adaptive Knowledge Sharing in Multi-Task Learning: Improving Low-Resource Neural Machine Translation.
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

Learning How to Actively Learn: A Deep Imitation Learning Approach.
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

2017
Regression.
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Linear Regression.
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Linear Discriminant.
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Graphical Models.
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Bayesian Methods.
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Efficient parameter learning of Bayesian network classifiers.
Mach. Learn., 2017

Leveraging Node Attributes for Incomplete Relational Data.
Proceedings of the 34th International Conference on Machine Learning, 2017

MetaLDA: A Topic Model that Efficiently Incorporates Meta Information.
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

Backoff methods for estimating parameters of a Bayesian network.
Proceedings of the 3rd Workshop on Advanced Methodologies for Bayesian Networks, 2017

A Word Embeddings Informed Focused Topic Model.
Proceedings of The 9th Asian Conference on Machine Learning, 2017

Leveraging Linguistic Resources for Improving Neural Text Classification.
Proceedings of the Australasian Language Technology Association Workshop, 2017

2016
Bibliographic analysis on research publications using authors, categorical labels and the citation network.
Mach. Learn., 2016

Towards a Methodology for Nursing-Specific Clinical Decision Support Systems (CDSS).
J. Decis. Syst., 2016

Nonparametric Bayesian topic modelling with the hierarchical Pitman-Yor processes.
Int. J. Approx. Reason., 2016

Twitter-Network Topic Model: A Full Bayesian Treatment for Social Network and Text Modeling.
CoRR, 2016

PULP: A System for Exploratory Search of Scientific Literature.
Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval, 2016

Learning cascaded latent variable models for biomedical text classification.
Proceedings of the Australasian Language Technology Association Workshop 2016, Melbourne, Australia, December 5, 2016

2015
Differential Topic Models.
IEEE Trans. Pattern Anal. Mach. Intell., 2015

Introduction: special issue of selected papers of ACML 2013.
Mach. Learn., 2015

Special session on trends & controversies in data science (TCDS).
Proceedings of the 2015 IEEE International Conference on Data Science and Advanced Analytics, 2015

Making Topic Models more Usable.
Proceedings of the 2015 Workshop on Topic Models: Post-Processing and Applications, 2015

2014
Experiments with non-parametric topic models.
Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

Twitter Opinion Topic Model: Extracting Product Opinions from Tweets by Leveraging Hashtags and Sentiment Lexicon.
Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, 2014

Bibliographic Analysis with the Citation Network Topic Model.
Proceedings of the Sixth Asian Conference on Machine Learning, 2014

Exploring Temporal Patterns in Emergency Department Triage Notes with Topic Models.
Proceedings of the Australasian Language Technology Association Workshop, 2014

2013
Introduction to the special issue on social web mining.
ACM Trans. Intell. Syst. Technol., 2013

Introduction: special issue of selected papers of ACML 2012.
Mach. Learn., 2013

Improving LDA topic models for microblogs via tweet pooling and automatic labeling.
Proceedings of the 36th International ACM SIGIR conference on research and development in Information Retrieval, 2013

Topic Segmentation with a Structured Topic Model.
Proceedings of the Human Language Technologies: Conference of the North American Chapter of the Association of Computational Linguistics, 2013

Dependent Normalized Random Measures.
Proceedings of the 30th International Conference on Machine Learning, 2013

2012
Sequential latent Dirichlet allocation.
Knowl. Inf. Syst., 2012

Preface.
Proceedings of the 4th Asian Conference on Machine Learning, 2012

Theory of Dependent Hierarchical Normalized Random Measures
CoRR, 2012

Score-Based Bayesian Skill Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

Dependent Hierarchical Normalized Random Measures for Dynamic Topic Modeling.
Proceedings of the 29th International Conference on Machine Learning, 2012

Modelling Sequential Text with an Adaptive Topic Model.
Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, 2012

2011
Sampling Table Configurations for the Hierarchical Poisson-Dirichlet Process.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

Improving Topic Coherence with Regularized Topic Models.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Discovery in Text: Visualisation, Topics and Statistics.
Proceedings of the Australasian Language Technology Association Workshop 2011, 2011

2010
Regression.
Proceedings of the Encyclopedia of Machine Learning, 2010

Linear Regression.
Proceedings of the Encyclopedia of Machine Learning, 2010

Linear Discriminant.
Proceedings of the Encyclopedia of Machine Learning, 2010

Graphical Models.
Proceedings of the Encyclopedia of Machine Learning, 2010

Bayesian Methods.
Proceedings of the Encyclopedia of Machine Learning, 2010

A segmented topic model based on the two-parameter Poisson-Dirichlet process.
Mach. Learn., 2010

Unsupervised Object Discovery: A Comparison.
Int. J. Comput. Vis., 2010

A Bayesian Review of the Poisson-Dirichlet Process
CoRR, 2010

Word Features for Latent Dirichlet Allocation.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Beyond 2D-grids: a dependence maximization view on image browsing.
Proceedings of the 11th ACM SIGMM International Conference on Multimedia Information Retrieval, 2010

Sequential Latent Dirichlet Allocation: Discover Underlying Topic Structures within a Document.
Proceedings of the ICDM 2010, 2010

2009
Guest editors' introduction: Special Issue from ECML PKDD 2009.
Mach. Learn., 2009

Guest editors' introduction: special issue of selected papers from ECML PKDD 2009.
Data Min. Knowl. Discov., 2009

Exploring Scale-Induced Feature Hierarchies in Natural Images.
Proceedings of the International Conference on Machine Learning and Applications, 2009

Kernel Conditional Quantile Estimation via Reduction Revisited.
Proceedings of the ICDM 2009, 2009

Estimating Likelihoods for Topic Models.
Proceedings of the Advances in Machine Learning, 2009

2008
Product retrieval for grocery stores.
Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2008

Natural language retrieval of grocery products.
Proceedings of the 17th ACM Conference on Information and Knowledge Management, 2008

2006
SIGIR06 workshop report: Open Source Information Retrieval systems (OSIR06).
SIGIR Forum, 2006

Open source search and research.
Proceedings of the International Workshop on Research Issues in Digital Libraries, 2006

ALVIS - Superpeer Semantic Search Engine - ECDL 2006 Demo Submission.
Proceedings of the Research and Advanced Technology for Digital Libraries, 2006

2005
Open source search: a data mining platform.
SIGIR Forum, 2005

Multi-Faceted Information Retrieval System for Large Scale Email Archives.
Proceedings of the 2005 IEEE / WIC / ACM International Conference on Web Intelligence (WI 2005), 2005

Opportunities from Open Source Search.
Proceedings of the 2005 IEEE / WIC / ACM International Conference on Web Intelligence (WI 2005), 2005

Discrete Component Analysis.
Proceedings of the Subspace, 2005

A temporally adaptive content-based relevance ranking algorithm.
Proceedings of the SIGIR 2005: Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2005

2004
Exploring Independent Trends in a Topic-Based Search Engine.
Proceedings of the 2004 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2004), 2004

A Scalable Topic-Based Open Source Search Engine.
Proceedings of the 2004 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2004), 2004

Applying Discrete PCA in Data Analysis.
Proceedings of the UAI '04, 2004

Automated Synthesis of Data Analysis Programs: Learning in Logic.
Proceedings of the Inductive Logic Programming, 14th International Conference, 2004

ALVIS: Superpeer Semantic Search Engine.
Proceedings of the Knowledge-Based Media Analysis for Self-Adaptive and Agile Multi-Media, 2004

2003
Efficient Computing of Stochastic Complexity.
Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, 2003

Is Multinomial PCA Multi-faceted Clustering or Dimensionality Reduction?
Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, 2003

2002
Automatic Derivation of Statistical Algorithms: The EM Family and Beyond.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Variational Extensions to EM and Multinomial PCA.
Proceedings of the Machine Learning: ECML 2002, 2002

2001
Learning as applied to stochastic optimization for standard-cellplacement.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2001

1999
Towards Automated Synthesis of Data Mining Programs.
Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 1999

1998
Trends & Controversies: Will Domain-Specific Code Synthesis Become a Silver Bullet?
IEEE Intell. Syst., 1998

Analysing Rock Samples for the Mars Lander.
Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining (KDD-98), 1998

Learning as applied to stochastic optimization for standard cell placement.
Proceedings of the International Conference on Computer Design: VLSI in Computers and Processors, 1998

1997
Adaptive methods for netlist partitioning.
Proceedings of the 1997 IEEE/ACM International Conference on Computer-Aided Design, 1997

1996
A Guide to the Literature on Learning Probabilistic Networks from Data.
IEEE Trans. Knowl. Data Eng., 1996

Graphical Models for Discivering Knowledge.
Proceedings of the Advances in Knowledge Discovery and Data Mining., 1996

1995
Book reviews.
Minds Mach., 1995

Chain graphs for learning.
Proceedings of the UAI '95: Proceedings of the Eleventh Annual Conference on Uncertainty in Artificial Intelligence, 1995

Intelligent Instruments: Discovering How to Turn Spectral Data into Information.
Proceedings of the First International Conference on Knowledge Discovery and Data Mining (KDD-95), 1995

1994
Computing second derivatives in feed-forward networks: a review.
IEEE Trans. Neural Networks, 1994

Guest Editorial.
Mach. Learn., 1994

Operations for Learning with Graphical Models.
J. Artif. Intell. Res., 1994

On Solving Equations and Disequations.
J. ACM, 1994

1992
A Further Comparison of Splitting Rules for Decision-Tree Induction.
Mach. Learn., 1992

1991
Bayesian Back-Propagation.
Complex Syst., 1991

Modelling default and likelihood reasoning as probabilistic reasoning.
Ann. Math. Artif. Intell., 1991

Theory Refinement on Bayesian Networks.
Proceedings of the UAI '91: Proceedings of the Seventh Annual Conference on Uncertainty in Artificial Intelligence, 1991

Some Properties of Plausible Reasoning.
Proceedings of the UAI '91: Proceedings of the Seventh Annual Conference on Uncertainty in Artificial Intelligence, 1991

Classifiers: A Theoretical and Empirical Study.
Proceedings of the 12th International Joint Conference on Artificial Intelligence. Sydney, 1991

1990
Myths and Legends in Learning Classification Rules.
Proceedings of the 8th National Conference on Artificial Intelligence. Boston, Massachusetts, USA, July 29, 1990

1989
Inductive knowledge acquisition and induction methodologies.
Knowl. Based Syst., 1989

A Critique of the Valiant Model.
Proceedings of the 11th International Joint Conference on Artificial Intelligence. Detroit, 1989

Learning Classification Rules Using Bayes.
Proceedings of the Sixth International Workshop on Machine Learning (ML 1989), 1989

1988
Decision tree induction systems: A Bayesian analysis.
Int. J. Approx. Reason., 1988

Generalized Subsumption and Its Applications to Induction and Redundancy.
Artif. Intell., 1988

Machine Invention of First Order Predicates by Inverting Resolution.
Proceedings of the Machine Learning, 1988

1987
Induction of Horn Clauses: Methods and the Plausible Generalization Algorithm.
Int. J. Man Mach. Stud., 1987

1986
Generalised Subsumption and its Applications to Induction and Redundancy.
Proceedings of the Advances in Artificial Intelligence II, 1986

1976
Automatic circuit analysis based on mask information.
Proceedings of the 13th Design Automation Conference, 1976

Design rule checking and analysis of IC mask designs.
Proceedings of the 13th Design Automation Conference, 1976


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