Khoat Than

Orcid: 0000-0001-8615-2854

According to our database1, Khoat Than authored at least 52 papers between 2012 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Continual variational dropout: a view of auxiliary local variables in continual learning.
Mach. Learn., January, 2024

On Inference Stability for Diffusion Models.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Unsupervised image segmentation with robust virtual class contrast.
Pattern Recognit. Lett., September, 2023

Dynamic Transformation of Prior Knowledge Into Bayesian Models for Data Streams.
IEEE Trans. Knowl. Data Eng., April, 2023

KOPPA: Improving Prompt-based Continual Learning with Key-Query Orthogonal Projection and Prototype-based One-Versus-All.
CoRR, 2023

Sharpness and Gradient Aware Minimization for Memory-based Continual Learning.
Proceedings of the 12th International Symposium on Information and Communication Technology, 2023

Bayesian method for bee counting with noise-labeled data.
Proceedings of the 12th International Symposium on Information and Communication Technology, 2023

2022
Adaptive infinite dropout for noisy and sparse data streams.
Mach. Learn., 2022

Revisiting Supervised Word Embeddings.
J. Inf. Sci. Eng., 2022

From implicit to explicit feedback: A deep neural network for modeling sequential behaviours and long-short term preferences of online users.
Neurocomputing, 2022

Balancing stability and plasticity when learning topic models from short and noisy text streams.
Neurocomputing, 2022

A graph convolutional topic model for short and noisy text streams.
Neurocomputing, 2022

Continual Learning with Optimal Transport based Mixture Model.
CoRR, 2022

Face Swapping as A Simple Arithmetic Operation.
CoRR, 2022

Random Generative Adversarial Networks.
Proceedings of the 11th International Symposium on Information and Communication Technology, 2022

Reducing Catastrophic Forgetting in Neural Networks via Gaussian Mixture Approximation.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2022

Auxiliary Local Variables for Improving Regularization/Prior Approach in Continual Learning.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2022

2021
Boosting prior knowledge in streaming variational Bayes.
Neurocomputing, 2021

Generalization of GANs under Lipschitz continuity and data augmentation.
CoRR, 2021

Improving Bayesian Inference in Deep Neural Networks with Variational Structured Dropout.
CoRR, 2021

Structured Dropout Variational Inference for Bayesian Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020
Bag of biterms modeling for short texts.
Knowl. Inf. Syst., 2020

Graph Convolutional Topic Model for Data Streams.
CoRR, 2020

Neural Poisson Factorization.
IEEE Access, 2020

MAP Estimation With Bernoulli Randomness, and Its Application to Text Analysis and Recommender Systems.
IEEE Access, 2020

Predictive Coding for Locally-Linear Control.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Eliminating overfitting of probabilistic topic models on short and noisy text: The role of dropout.
Int. J. Approx. Reason., 2019

Enriching User Representation in Neural Matrix Factorization.
Proceedings of the 2019 IEEE-RIVF International Conference on Computing and Communication Technologies, 2019

Marking Mechanism in Sequence-to-sequence Model for Mapping Language to Logical Form.
Proceedings of the 11th International Conference on Knowledge and Systems Engineering, 2019

Infinite Dropout for training Bayesian models from data streams.
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

From Implicit to Explicit Feedback: A deep neural network for modeling the sequential behavior of online users.
Proceedings of The 11th Asian Conference on Machine Learning, 2019

Employing the Correspondence of Relations and Connectives to Identify Implicit Discourse Relations via Label Embeddings.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018
Collaborative Topic Model for Poisson distributed ratings.
Int. J. Approx. Reason., 2018

A Flexible Stochastic Method for Solving the MAP Problem in Topic Models.
Computación y Sistemas, 2018

Reducing Class Overlapping in Supervised Dimension Reduction.
Proceedings of the Ninth International Symposium on Information and Communication Technology, 2018

Evaluating Named-Entity Recognition Approaches in Plant Molecular Biology.
Proceedings of the Multi-disciplinary Trends in Artificial Intelligence, 2018

A Fast Algorithm for Posterior Inference with Latent Dirichlet Allocation.
Proceedings of the Intelligent Information and Database Systems - 10th Asian Conference, 2018

2017
An effective and interpretable method for document classification.
Knowl. Inf. Syst., 2017

Keeping Priors in Streaming Bayesian Learning.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2017

Sparse Stochastic Inference with Regularization.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2017

2016
Streaming aspect-sentiment analysis.
Proceedings of the 2016 IEEE RIVF International Conference on Computing & Communication Technologies, 2016

Enabling Hierarchical Dirichlet Processes to Work Better for Short Texts at Large Scale.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2016

2015
Effective and Interpretable Document Classification Using Distinctly Labeled Dirichlet Process Mixture Models of von Mises-Fisher Distributions.
Proceedings of the Database Systems for Advanced Applications, 2015

2014
An effective framework for supervised dimension reduction.
Neurocomputing, 2014

Modeling the diversity and log-normality of data.
Intell. Data Anal., 2014

An Effective NMF-Based Method for Supervised Dimension Reduction.
Proceedings of the Knowledge and Systems Engineering, 2014

Dual online inference for latent Dirichlet allocation.
Proceedings of the Sixth Asian Conference on Machine Learning, 2014

2013
Probable convexity and its application to Correlated Topic Models.
CoRR, 2013

Simplicial nonnegative matrix factorization.
Proceedings of the 2013 IEEE RIVF International Conference on Computing and Communication Technologies, 2013

2012
Supervised dimension reduction with topic models.
Proceedings of the 4th Asian Conference on Machine Learning, 2012

Managing sparsity, time, and quality of inference in topic models
CoRR, 2012

Fully Sparse Topic Models.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012


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