Search Results for author: Wray Buntine

Found 44 papers, 17 papers with code

On the Effect of Isotropy on VAE Representations of Text

1 code implementation ACL 2022 Lan Zhang, Wray Buntine, Ehsan Shareghi

Injecting desired geometric properties into text representations has attracted a lot of attention.

Multilingual Neural Machine Translation: Can Linguistic Hierarchies Help?

no code implementations Findings (EMNLP) 2021 Fahimeh Saleh, Wray Buntine, Gholamreza Haffari, Lan Du

Multilingual Neural Machine Translation (MNMT) trains a single NMT model that supports translation between multiple languages, rather than training separate models for different languages.

Knowledge Distillation Machine Translation +1

Unsupervised Sentence Simplification via Dependency Parsing

1 code implementation10 Jun 2022 Vy Vo, Weiqing Wang, Wray Buntine

Text simplification is the task of rewriting a text so that it is readable and easily understood.

Dependency Parsing Sentence Embeddings +1

Diversity Enhanced Active Learning with Strictly Proper Scoring Rules

1 code implementation NeurIPS 2021 Wei Tan, Lan Du, Wray Buntine

We convert the ELR framework to estimate the increase in (strictly proper) scores like log probability or negative mean square error, which we call Bayesian Estimate of Mean Proper Scores (BEMPS).

Active Learning Pretrained Language Models +2

Multilingual Neural Machine Translation:Can Linguistic Hierarchies Help?

no code implementations15 Oct 2021 Fahimeh Saleh, Wray Buntine, Gholamreza Haffari, Lan Du

Multilingual Neural Machine Translation (MNMT) trains a single NMT model that supports translation between multiple languages, rather than training separate models for different languages.

Knowledge Distillation Machine Translation +1

The Neglected Sibling: Isotropic Gaussian Posterior for VAE

1 code implementation14 Oct 2021 Lan Zhang, Wray Buntine, Ehsan Shareghi

Deep generative models have been widely used in several areas of NLP, and various techniques have been proposed to augment them or address their training challenges.

Topic Model or Topic Twaddle? Re-evaluating Semantic Interpretability Measures

no code implementations NAACL 2021 Caitlin Doogan, Wray Buntine

In this paper, we probe the issue of validity in topic model evaluation and assess how informative coherence measures are for specialized collections used in an applied setting.

Topic Models

All Labels Are Not Created Equal: Enhancing Semi-supervision via Label Grouping and Co-training

1 code implementation CVPR 2021 Islam Nassar, Samitha Herath, Ehsan Abbasnejad, Wray Buntine, Gholamreza Haffari

We train two classifiers with two different views of the class labels: one classifier uses the one-hot view of the labels and disregards any potential similarity among the classes, while the other uses a distributed view of the labels and groups potentially similar classes together.

Semi-Supervised Image Classification

Topic Modelling Meets Deep Neural Networks: A Survey

no code implementations28 Feb 2021 He Zhao, Dinh Phung, Viet Huynh, Yuan Jin, Lan Du, Wray Buntine

Topic modelling has been a successful technique for text analysis for almost twenty years.

Navigate Text Generation +1

SQAPlanner: Generating Data-Informed Software Quality Improvement Plans

1 code implementation19 Feb 2021 Dilini Rajapaksha, Chakkrit Tantithamthavorn, Jirayus Jiarpakdee, Christoph Bergmeir, John Grundy, Wray Buntine

Thus, our SQAPlanner paves a way for novel research in actionable software analytics-i. e., generating actionable guidance on what should practitioners do and not do to decrease the risk of having defects to support SQA planning.

Temporal Cascade and Structural Modelling of EHRs for Granular Readmission Prediction

no code implementations4 Feb 2021 Bhagya Hettige, Weiqing Wang, Yuan-Fang Li, Suong Le, Wray Buntine

Although a point process (e. g., Hawkes process) is able to model a cascade temporal relationship, it strongly relies on a prior generative process assumption.

Decision Making Point Processes +1

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

no code implementations12 Nov 2020 Yuan Jin, Wray Buntine, Francois Petitjean, Geoffrey I. Webb

For this task, we survey a wide range of techniques available for handling missing values, self-supervised training and pseudo-likelihood training, and adapt them to a suite of algorithms that are suitable for the task.

Self-Supervised Learning

Neural Topic Model via Optimal Transport

1 code implementation ICLR 2021 He Zhao, Dinh Phung, Viet Huynh, Trung Le, Wray Buntine

Recently, Neural Topic Models (NTMs) inspired by variational autoencoders have obtained increasingly research interest due to their promising results on text analysis.

Topic Models

$\mathtt{MedGraph:}$ Structural and Temporal Representation Learning of Electronic Medical Records

1 code implementation8 Dec 2019 Bhagya Hettige, Yuan-Fang Li, Weiqing Wang, Suong Le, Wray Buntine

To address these limitations, we present $\mathtt{MedGraph}$, a supervised EMR embedding method that captures two types of information: (1) the visit-code associations in an attributed bipartite graph, and (2) the temporal sequencing of visits through a point process.

Point Processes Representation Learning

Gaussian Embedding of Large-scale Attributed Graphs

1 code implementation2 Dec 2019 Bhagya Hettige, Yuan-Fang Li, Weiqing Wang, Wray Buntine

Graph embedding methods transform high-dimensional and complex graph contents into low-dimensional representations.

Graph Embedding Link Prediction +1

LoRMIkA: Local rule-based model interpretability with k-optimal associations

no code implementations11 Aug 2019 Dilini Rajapaksha, Christoph Bergmeir, Wray Buntine

In this paper, we propose Local Rule-based Model Interpretability with k-optimal Associations (LoRMIkA), a novel model-agnostic approach that obtains k-optimal association rules from a neighbourhood of the instance to be explained.

BIG-bench Machine Learning Decision Making

Leveraging Meta Information in Short Text Aggregation

no code implementations ACL 2019 He Zhao, Lan Du, Guanfeng Liu, Wray Buntine

Short texts such as tweets often contain insufficient word co-occurrence information for training conventional topic models.

Topic Models

Variational Autoencoders for Sparse and Overdispersed Discrete Data

1 code implementation2 May 2019 He Zhao, Piyush Rai, Lan Du, Wray Buntine, Mingyuan Zhou

Many applications, such as text modelling, high-throughput sequencing, and recommender systems, require analysing sparse, high-dimensional, and overdispersed discrete (count-valued or binary) data.

Collaborative Filtering Multi-Label Learning +1

Dirichlet belief networks for topic structure learning

2 code implementations NeurIPS 2018 He Zhao, Lan Du, Wray Buntine, Mingyuan Zhou

Recently, considerable research effort has been devoted to developing deep architectures for topic models to learn topic structures.

Topic Models

Learning How to Actively Learn: A Deep Imitation Learning Approach

1 code implementation ACL 2018 Ming Liu, Wray Buntine, Gholamreza Haffari

Heuristic-based active learning (AL) methods are limited when the data distribution of the underlying learning problems vary.

Active Learning General Classification +6

Distinguishing Question Subjectivity from Difficulty for Improved Crowdsourcing

no code implementations12 Feb 2018 Yuan Jin, Mark Carman, Ye Zhu, Wray Buntine

Experiments show that our model(1) improves the performance of both quality control for crowd-sourced answers and next answer prediction for crowd-workers, and (2) can potentially provide coherent rankings of questions in terms of their difficulty and subjectivity, so that task providers can refine their designs of the crowdsourcing tasks, e. g. by removing highly subjective questions or inappropriately difficult questions.

MetaLDA: a Topic Model that Efficiently Incorporates Meta information

1 code implementation19 Sep 2017 He Zhao, Lan Du, Wray Buntine, Gang Liu

Besides the text content, documents and their associated words usually come with rich sets of meta informa- tion, such as categories of documents and semantic/syntactic features of words, like those encoded in word embeddings.

Topic Models Word Embeddings

Accurate parameter estimation for Bayesian Network Classifiers using Hierarchical Dirichlet Processes

4 code implementations25 Aug 2017 Francois Petitjean, Wray Buntine, Geoffrey I. Webb, Nayyar Zaidi

The main result of this paper is to show that improved parameter estimation allows BNCs to outperform leading learning methods such as Random Forest for both 0-1 loss and RMSE, albeit just on categorical datasets.

General Classification

Leveraging Node Attributes for Incomplete Relational Data

1 code implementation ICML 2017 He Zhao, Lan Du, Wray Buntine

Relational data are usually highly incomplete in practice, which inspires us to leverage side information to improve the performance of community detection and link prediction.

Community Detection Link Prediction

Nonparametric Bayesian Topic Modelling with the Hierarchical Pitman-Yor Processes

no code implementations22 Sep 2016 Kar Wai Lim, Wray Buntine, Changyou Chen, Lan Du

In this article, we present efficient methods for the use of these processes in this hierarchical context, and apply them to latent variable models for text analytics.

Topic Models

Twitter-Network Topic Model: A Full Bayesian Treatment for Social Network and Text Modeling

no code implementations22 Sep 2016 Kar Wai Lim, Changyou Chen, Wray Buntine

Exploiting this additional information, we propose the Twitter-Network (TN) topic model to jointly model the text and the social network in a full Bayesian nonparametric way.

Topic Models

Bibliographic Analysis with the Citation Network Topic Model

no code implementations22 Sep 2016 Kar Wai Lim, Wray Buntine

Bibliographic analysis considers author's research areas, the citation network and paper content among other things.

Bibliographic Analysis on Research Publications using Authors, Categorical Labels and the Citation Network

no code implementations21 Sep 2016 Kar Wai Lim, Wray Buntine

In this paper, we combine these three in a topic model that produces a bibliographic model of authors, topics and documents, using a nonparametric extension of a combination of the Poisson mixed-topic link model and the author-topic model.

Twitter Opinion Topic Model: Extracting Product Opinions from Tweets by Leveraging Hashtags and Sentiment Lexicon

no code implementations21 Sep 2016 Kar Wai Lim, Wray Buntine

Although social media data like tweets are laden with opinions, their "dirty" nature (as natural language) has discouraged researchers from applying LDA-based opinion model for product review mining.

Opinion Mining Sentiment Analysis

Word Features for Latent Dirichlet Allocation

no code implementations NeurIPS 2010 James Petterson, Wray Buntine, Shravan M. Narayanamurthy, Tibério S. Caetano, Alex J. Smola

We extend Latent Dirichlet Allocation (LDA) by explicitly allowing for the encoding of side information in the distribution over words.

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