b'Wray Buntine'

research

∙ 09/15/2023

Reward Engineering for Generating Semi-structured Explanation

Semi-structured explanation depicts the implicit process of a reasoner w...

0 Jiuzhou Han, et al. ∙

research

∙ 06/27/2023

A Survey on Out-of-Distribution Evaluation of Neural NLP Models

Adversarial robustness, domain generalization and dataset biases are thr...

0 Xinzhe Li, et al. ∙

research

∙ 05/21/2023

PiVe: Prompting with Iterative Verification Improving Graph-based Generative Capability of LLMs

Large language models (LLMs) have shown great abilities of solving vario...

0 Jiuzhou Han, et al. ∙

research

∙ 04/15/2023

Robust Educational Dialogue Act Classifiers with Low-Resource and Imbalanced Datasets

Dialogue acts (DAs) can represent conversational actions of tutors or st...

0 Jionghao Lin, et al. ∙

research

∙ 04/12/2023

Does Informativeness Matter? Active Learning for Educational Dialogue Act Classification

Dialogue Acts (DAs) can be used to explain what expert tutors do and wha...

0 Wei Tan, et al. ∙

research

∙ 12/09/2022

AUC Maximization for Low-Resource Named Entity Recognition

Current work in named entity recognition (NER) uses either cross entropy...

0 Ngoc Dang Nguyen, et al. ∙

research

∙ 11/11/2022

Hardness-guided domain adaptation to recognise biomedical named entities under low-resource scenarios

Domain adaptation is an effective solution to data scarcity in low-resou...

0 Ngoc Dang Nguyen, et al. ∙

research

∙ 06/10/2022

Unsupervised Sentence Simplification via Dependency Parsing

Text simplification is the task of rewriting a text so that it is readab...

0 Vy Vo, et al. ∙

research

∙ 10/27/2021

Diversity Enhanced Active Learning with Strictly Proper Scoring Rules

We study acquisition functions for active learning (AL) for text classif...

0 Wei Tan, et al. ∙

research

∙ 10/15/2021

Multilingual Neural Machine Translation:Can Linguistic Hierarchies Help?

Multilingual Neural Machine Translation (MNMT) trains a single NMT model...

13 Fahimeh Saleh, et al. ∙

research

∙ 10/14/2021

The Neglected Sibling: Isotropic Gaussian Posterior for VAE

Deep generative models have been widely used in several areas of NLP, an...

0 Lan Zhang, et al. ∙

research

∙ 10/14/2021

Neural Attention-Aware Hierarchical Topic Model

Neural topic models (NTMs) apply deep neural networks to topic modelling...

0 Yuan Jin, et al. ∙

research

∙ 10/14/2021

Transformer over Pre-trained Transformer for Neural Text Segmentation with Enhanced Topic Coherence

This paper proposes a transformer over transformer framework, called Tra...

0 Chun Wai Lo, Kelvin, et al. ∙

research

∙ 02/28/2021

Topic Modelling Meets Deep Neural Networks: A Survey

Topic modelling has been a successful technique for text analysis for al...

0 He Zhao, et al. ∙

research

∙ 02/19/2021

SQAPlanner: Generating Data-Informed Software Quality Improvement Plans

Software Quality Assurance (SQA) planning aims to define proactive plans...

0 Dilini Rajapaksha, et al. ∙

research

∙ 02/04/2021

Temporal Cascade and Structural Modelling of EHRs for Granular Readmission Prediction

Predicting (1) when the next hospital admission occurs and (2) what will...

0 Bhagya Hettige, et al. ∙

research

∙ 11/12/2020

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

Supervised learning, characterized by both discriminative and generative...

0 Yuan Jin, et al. ∙

research

∙ 10/12/2020

Collective Wisdom: Improving Low-resource Neural Machine Translation using Adaptive Knowledge Distillation

Scarcity of parallel sentence-pairs poses a significant hurdle for train...

9 Fahimeh Saleh, et al. ∙

research

∙ 08/12/2020

Neural Sinkhorn Topic Model

In this paper, we present a new topic modelling approach via the theory ...

0 He Zhao, et al. ∙

research

∙ 07/14/2020

Hands-on Bayesian Neural Networks – a Tutorial for Deep Learning Users

Modern deep learning methods have equipped researchers and engineers wit...

356 Laurent Valentin Jospin, et al. ∙

research

∙ 12/08/2019

MedGraph: Structural and Temporal Representation Learning of Electronic Medical Records

Electronic medical record (EMR) data contains historical sequences of vi...

0 Bhagya Hettige, et al. ∙

research

∙ 12/02/2019

Gaussian Embedding of Large-scale Attributed Graphs

Graph embedding methods transform high-dimensional and complex graph con...

0 Bhagya Hettige, et al. ∙

research

∙ 08/11/2019

LoRMIkA: Local Rule-based Model Interpretability with k-optimal Associations

As we rely more and more on machine learning models for real-life decisi...

7 Dilini Rajapaksha, et al. ∙

research

∙ 05/02/2019

Deep Generative Models for Sparse, High-dimensional, and Overdispersed Discrete Data

Many applications, such as text modelling, high-throughput sequencing, a...

0 He Zhao, et al. ∙

research

∙ 11/02/2018

Dirichlet belief networks for topic structure learning

Recently, considerable research effort has been devoted to developing de...

0 He Zhao, et al. ∙

research

∙ 02/12/2018

Distinguishing Question Subjectivity from Difficulty for Improved Crowdsourcing

The questions in a crowdsourcing task typically exhibit varying degrees ...

0 Yuan Jin, et al. ∙

research

∙ 09/19/2017

MetaLDA: a Topic Model that Efficiently Incorporates Meta information

Besides the text content, documents and their associated words usually c...

0 He Zhao, et al. ∙

research

∙ 08/25/2017

Accurate parameter estimation for Bayesian Network Classifiers using Hierarchical Dirichlet Processes

This paper introduces a novel parameter estimation method for the probab...

0 Francois Petitjean, et al. ∙

research

∙ 06/14/2017

Leveraging Node Attributes for Incomplete Relational Data

Relational data are usually highly incomplete in practice, which inspire...

0 He Zhao, et al. ∙

research

∙ 09/22/2016

Bibliographic Analysis with the Citation Network Topic Model

Bibliographic analysis considers author's research areas, the citation n...

0 Kar Wai Lim, et al. ∙

research

∙ 09/22/2016

Nonparametric Bayesian Topic Modelling with the Hierarchical Pitman-Yor Processes

The Dirichlet process and its extension, the Pitman-Yor process, are sto...

0 Kar Wai Lim, et al. ∙

research

∙ 09/21/2016

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

Bibliographic analysis considers the author's research areas, the citati...

0 Kar Wai Lim, et al. ∙

research

∙ 06/18/2012

Dependent Hierarchical Normalized Random Measures for Dynamic Topic Modeling

We develop dependent hierarchical normalized random measures and apply t...

0 Changyou Chen, et al. ∙

research

∙ 05/18/2012

Theory of Dependent Hierarchical Normalized Random Measures

This paper presents theory for Normalized Random Measures (NRMs), Normal...

0 Changyou Chen, et al. ∙

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