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07/24/2023
Towards Generalising Neural Topical Representations
Topic models have evolved from conventional Bayesian probabilistic model...
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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...
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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...
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04/04/2023
Multimodal Neural Processes for Uncertainty Estimation
Neural processes (NPs) have brought the representation power of parametr...
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02/27/2023
DST: Deformable Speech Transformer for Emotion Recognition
Enabled by multi-head self-attention, Transformer has exhibited remarkab...
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02/27/2023
SpeechFormer++: A Hierarchical Efficient Framework for Paralinguistic Speech Processing
Paralinguistic speech processing is important in addressing many issues,...
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12/23/2022
HiTSKT: A Hierarchical Transformer Model for Session-Aware Knowledge Tracing
Knowledge tracing (KT) aims to leverage students' learning histories to ...
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12/09/2022
AUC Maximization for Low-Resource Named Entity Recognition
Current work in named entity recognition (NER) uses either cross entropy...
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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...
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11/07/2022
Learning Semantic Textual Similarity via Topic-informed Discrete Latent Variables
Recently, discrete latent variable models have received a surge of inter...
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10/06/2022
Uncertainty Estimation for Multi-view Data: The Power of Seeing the Whole Picture
Uncertainty estimation is essential to make neural networks trustworthy ...
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03/08/2022
SpeechFormer: A Hierarchical Efficient Framework Incorporating the Characteristics of Speech
Transformer has obtained promising results on cognitive speech signal pr...
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10/27/2021
Diversity Enhanced Active Learning with Strictly Proper Scoring Rules
We study acquisition functions for active learning (AL) for text classif...
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10/15/2021
Multilingual Neural Machine Translation:Can Linguistic Hierarchies Help?
Multilingual Neural Machine Translation (MNMT) trains a single NMT model...
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10/14/2021
Neural Attention-Aware Hierarchical Topic Model
Neural topic models (NTMs) apply deep neural networks to topic modelling...
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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...
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10/04/2021
Leveraging Information Bottleneck for Scientific Document Summarization
This paper presents an unsupervised extractive approach to summarize sci...
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08/28/2021
Prototypes-Guided Memory Replay for Continual Learning
Continual learning (CL) refers to a machine learning paradigm that using...
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03/08/2021
Learning Graph Neural Networks with Positive and Unlabeled Nodes
Graph neural networks (GNNs) are important tools for transductive learni...
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03/05/2021
Stratified Sampling for Extreme Multi-Label Data
Extreme multi-label classification (XML) is becoming increasingly releva...
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02/28/2021
Topic Modelling Meets Deep Neural Networks: A Survey
Topic modelling has been a successful technique for text analysis for al...
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01/21/2021
Collaborative Teacher-Student Learning via Multiple Knowledge Transfer
Knowledge distillation (KD), as an efficient and effective model compres...
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10/15/2020
Multi-label Few/Zero-shot Learning with Knowledge Aggregated from Multiple Label Graphs
Few/Zero-shot learning is a big challenge of many classifications tasks,...
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07/17/2020
SummPip: Unsupervised Multi-Document Summarization with Sentence Graph Compression
Obtaining training data for multi-document summarization (MDS) is time c...
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02/21/2020
Leveraging Cross Feedback of User and Item Embeddings for Variational Autoencoder based Collaborative Filtering
Matrix factorization (MF) has been widely applied to collaborative filte...
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10/12/2019
Variational Auto-encoder Based Bayesian Poisson Tensor Factorization for Sparse and Imbalanced Count Data
Non-negative tensor factorization models enable predictive analysis on c...
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05/02/2019
Deep Generative Models for Sparse, High-dimensional, and Overdispersed Discrete Data
Many applications, such as text modelling, high-throughput sequencing, a...
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11/02/2018
Dirichlet belief networks for topic structure learning
Recently, considerable research effort has been devoted to developing de...
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10/15/2018
Improving Topic Models with Latent Feature Word Representations
Probabilistic topic models are widely used to discover latent topics in ...
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09/19/2017
MetaLDA: a Topic Model that Efficiently Incorporates Meta information
Besides the text content, documents and their associated words usually c...
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06/14/2017
Leveraging Node Attributes for Incomplete Relational Data
Relational data are usually highly incomplete in practice, which inspire...
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09/22/2016