Fully Sparse Topic Models. - Khoat Than; Tu Bao Ho (ECML/PKDD (1), 2012)

Managing sparsity, time, and quality of inference in topic models - Khoat Than; Tu Bao Ho (CoRR, 2012)

Supervised dimension reduction with topic models. - Khoat Than; Tu Bao Ho; Duy Khuong Nguyen; Pham Ngoc Khanh (ACML, 2012)

Simplicial nonnegative matrix factorization. - Duy Khuong Nguyen; Khoat Than; Tu Bao Ho (RIVF, 2013)

Probable convexity and its application to Correlated Topic Models. - Khoat Than; Tu Bao Ho (CoRR, 2013)

Dual online inference for latent Dirichlet allocation. - Khoat Than; Tung Doan 001 (ACML, 2014)

An Effective NMF-Based Method for Supervised Dimension Reduction. - Ngo Van Linh 001; Nguyen Kim Anh; Khoat Than (KSE, 2014)

Modeling the diversity and log-normality of data. - Khoat Than; Tu Bao Ho (Intell. Data Anal., 2014)

An effective framework for supervised dimension reduction. - Khoat Than; Tu Bao Ho; Duy Khuong Nguyen (Neurocomputing, 2014)

Effective and Interpretable Document Classification Using Distinctly Labeled Dirichlet Process Mixture Models of von Mises-Fisher Distributions. - Ngo Van Linh 001; Nguyen Kim Anh; Khoat Than; Nguyen Nguyen Tat (DASFAA (2), 2015)

Enabling Hierarchical Dirichlet Processes to Work Better for Short Texts at Large Scale. - Khai Mai; Sang Mai; Anh Nguyen; Ngo Van Linh 001; Khoat Than (PAKDD (2), 2016)

Streaming aspect-sentiment analysis. - Vu Le Anh; Chien Phung Van; Cuong Vu Cao; Ngo Van Linh 001; Khoat Than (RIVF, 2016)

Sparse Stochastic Inference with Regularization. - Tung Doan 001; Khoat Than (PAKDD (1), 2017)

Keeping Priors in Streaming Bayesian Learning. - Duc Anh Nguyen; Ngo Van Linh 001; Nguyen Kim Anh; Khoat Than (PAKDD (2), 2017)

An effective and interpretable method for document classification. - Ngo Van Linh 001; Nguyen Kim Anh; Khoat Than; Chien Nguyen Dang (Knowl. Inf. Syst., 2017)

A Fast Algorithm for Posterior Inference with Latent Dirichlet Allocation. - Bui Thi-Thanh-Xuan; Vu Van-Tu; Atsuhiro Takasu; Khoat Than (ACIIDS (2), 2018)

Evaluating Named-Entity Recognition Approaches in Plant Molecular Biology. - Huy Do; Khoat Than; Pierre Larmande (MIWAI, 2018)

Reducing Class Overlapping in Supervised Dimension Reduction. - Nguyen Trong Tung; Vu Hoang Dieu; Khoat Than; Ngo Van Linh 001 (SoICT, 2018)

A Flexible Stochastic Method for Solving the MAP Problem in Topic Models. - Tu Vu; Xuan Bui; Khoat Than; Ryutaro Ichise (Computación y Sistemas, 2018)

Collaborative Topic Model for Poisson distributed ratings. - Hoa M. Le; Son Ta Cong; Quyen Pham The; Ngo Van Linh 001; Khoat Than (Int. J. Approx. Reason., 2018)

Employing the Correspondence of Relations and Connectives to Identify Implicit Discourse Relations via Label Embeddings. - Linh The Nguyen; Ngo Van Linh 001; Khoat Than; Thien Huu Nguyen (ACL (1), 2019)

From Implicit to Explicit Feedback: A deep neural network for modeling the sequential behavior of online users. - Anh Phan Tuan; Nhat Nguyen Trong; Duong Bui Trong; Ngo Van Linh 001; Khoat Than (ACML, 2019)

Infinite Dropout for training Bayesian models from data streams. - Van-Son Nguyen; Duc-Tung Nguyen; Ngo Van Linh 001; Khoat Than (IEEE BigData, 2019)

Marking Mechanism in Sequence-to-sequence Model for Mapping Language to Logical Form. - Minh-Tien Nguyen; Khoat Than; Minh Le Nguyen 001 (KSE, 2019)

Enriching User Representation in Neural Matrix Factorization. - Thanh Hai Hoang; Anh Phan Tuan; Ngo Van Linh 001; Khoat Than (RIVF, 2019)

Eliminating overfitting of probabilistic topic models on short and noisy text: The role of dropout. - Cuong Ha; Van-Dang Tran; Ngo Van Linh 001; Khoat Than (Int. J. Approx. Reason., 2019)

Predictive Coding for Locally-Linear Control. - Rui Shu; Tung Nguyen; Yinlam Chow; Tuan Pham; Khoat Than; Mohammad Ghavamzadeh; Stefano Ermon; Hung H. Bui (ICML, 2020)

MAP Estimation With Bernoulli Randomness, and Its Application to Text Analysis and Recommender Systems. - Xuan Bui; Hieu Vu; Thi-Oanh Nguyen; Khoat Than (IEEE Access, 2020)

Neural Poisson Factorization. - Ngo Van Linh 001; Duc Anh Nguyen; Thai Binh Nguyen 001; Khoat Than (IEEE Access, 2020)

Graph Convolutional Topic Model for Data Streams. - Ngo Van Linh 001; Tran Xuan Bach; Khoat Than (CoRR, 2020)

Bag of biterms modeling for short texts. - Anh Phan Tuan; Tran Xuan Bach; Thien Huu Nguyen; Ngo Van Linh 001; Khoat Than (Knowl. Inf. Syst., 2020)

Structured Dropout Variational Inference for Bayesian Neural Networks. - Son Nguyen; Duong Nguyen; Khai Nguyen; Khoat Than; Hung Bui; Nhat Ho (NeurIPS, 2021)

Improving Bayesian Inference in Deep Neural Networks with Variational Structured Dropout. - Son Nguyen; Duong Nguyen; Khai Nguyen; Nhat Ho; Khoat Than; Hung Bui (CoRR, 2021)

Generalization of GANs under Lipschitz continuity and data augmentation. - Khoat Than; Nghia Vu (CoRR, 2021)

Boosting prior knowledge in streaming variational Bayes. - Duc Anh Nguyen; Ngo Van Linh 001; Nguyen Kim Anh; Canh Hao Nguyen; Khoat Than (Neurocomputing, 2021)

Auxiliary Local Variables for Improving Regularization/Prior Approach in Continual Learning. - Ngo Van Linh 001; Nam Le Hai; Hoang Pham; Khoat Than (PAKDD (1), 2022)

Reducing Catastrophic Forgetting in Neural Networks via Gaussian Mixture Approximation. - Hoang Phan; Anh Phan Tuan; Son Nguyen; Ngo Van Linh 001; Khoat Than (PAKDD (1), 2022)

Random Generative Adversarial Networks. - Khoa Nguyen 003; Nghia Vu; Dung Nguyen; Khoat Than (SoICT, 2022)

Face Swapping as A Simple Arithmetic Operation. - Truong Vu; Kien Do; Khang Nguyen; Khoat Than (CoRR, 2022)

Continual Learning with Optimal Transport based Mixture Model. - Quyen Tran; Hoang Phan; Khoat Than; Dinh Q. Phung; Trung Le 001 (CoRR, 2022)

A graph convolutional topic model for short and noisy text streams. - Ngo Van Linh 001; Tran Xuan Bach; Khoat Than (Neurocomputing, 2022)

Balancing stability and plasticity when learning topic models from short and noisy text streams. - Tung Nguyen; Trung Mai; Nam Nguyen; Linh Ngo Van 001; Khoat Than (Neurocomputing, 2022)

From implicit to explicit feedback: A deep neural network for modeling sequential behaviours and long-short term preferences of online users. - Quyen Tran; Lam Tran; Linh Chu Hai; Ngo Van Linh 001; Khoat Than (Neurocomputing, 2022)

Revisiting Supervised Word Embeddings. - Dieu Vu; Khang Truong; Khanh Nguyen; Ngo Van Linh 001; Khoat Than (J. Inf. Sci. Eng., 2022)

Adaptive infinite dropout for noisy and sparse data streams. - Ha Nguyen; Hoang Pham; Son Nguyen; Ngo Van Linh 001; Khoat Than (Mach. Learn., 2022)

Bayesian method for bee counting with noise-labeled data. - Duy-Tung Nguyen; Duc-Manh Nguyen; Dinh-Tan Pham; Khoat Than; Hong-Thai Pham; Hai Vu (SoICT, 2023)

Sharpness and Gradient Aware Minimization for Memory-based Continual Learning. - Lam Tran Tung; Viet Nguyen Van; Phi Nguyen Hoang; Khoat Than (SoICT, 2023)

KOPPA: Improving Prompt-based Continual Learning with Key-Query Orthogonal Projection and Prototype-based One-Versus-All. - Quyen Tran; Lam Tran; Khoat Than; Toan Tran 003; Dinh Q. Phung; Trung Le 001 (CoRR, 2023)

Dynamic Transformation of Prior Knowledge Into Bayesian Models for Data Streams. - Tran Xuan Bach; Nguyen Duc Anh; Ngo Van Linh 001; Khoat Than (IEEE Trans. Knowl. Data Eng., 2023)

Unsupervised image segmentation with robust virtual class contrast. - Khang Nguyen; Kien Do; Truong Vu; Khoat Than (Pattern Recognit. Lett., 2023)

On Inference Stability for Diffusion Models. - Viet Nguyen; Giang Vu; Tung Nguyen Thanh; Khoat Than; Toan Tran (AAAI, 2024)

Robust Visual Reinforcement Learning by Prompt Tuning. - Tung Tran 006; Khoat Than; Danilo Vasconcellos Vargas (ACCV (9), 2024)

Gentle robustness implies Generalization. - Khoat Than; Dat Phan; Giang Vu (CoRR, 2024)

Partial ordered Wasserstein distance for sequential data. - Tung Doan 001; Tuan Phan; Phu Nguyen; Khoat Than; Muriel Visani; Atsuhiro Takasu (Neurocomputing, 2024)

Continual variational dropout: a view of auxiliary local variables in continual learning. - Nam Le Hai; Trang Nguyen; Ngo Van Linh 001; Thien Huu Nguyen; Khoat Than (Mach. Learn., 2024)

Boosting Multiple Views for pretrained-based Continual Learning. - Quyen Tran; Tung Lam Tran; Khanh Doan; Toan Tran 003; Dinh Q. Phung; Khoat Than; Trung Le 001 (ICLR, 2025)

DPaI: Differentiable Pruning at Initialization with Node-Path Balance Principle. - Lichuan Xiang; Quan Nguyen-Tri; Lan-Cuong Nguyen; Hoang Pham; Khoat Than; Long Tran-Thanh; Hongkai Wen 001 (ICLR, 2025)

Out-of-vocabulary handling and topic quality control strategies in streaming topic models. - Tung Nguyen; Tung Pham; Ngo Van Linh 001; Ha-Bang Ban; Khoat Than (Neurocomputing, 2025)

Non-vacuous Generalization Bounds for Deep Neural Networks without any modification to the trained models. - Khoat Than; Dat Phan (CoRR, 2025)

Weighted Integrated Gradients for Feature Attribution. - Kien Tran Duc Tuan; Tam Nguyen Trong; Son Nguyen Hoang; Khoat Than; Duc Anh Nguyen (CoRR, 2025)

Provably Improving Generalization of Few-Shot Models with Synthetic Data. - Lan-Cuong Nguyen; Quan Nguyen-Tri; Bang Tran Khanh; Dung D. Le; Long Tran-Thanh; Khoat Than (CoRR, 2025)

Gentle local robustness implies generalization. - Khoat Than; Dat Phan; Giang Vu (Mach. Learn., 2025)

Generalized ordered Wasserstein distance for sequential data. - Tung Doan 001; Hiep To; Thi Hong Vuong; Muriel Visani; Atsuhiro Takasu; Khoat Than (Pattern Recognit., 2026)