Khoat Than - RankMe

73 papers A* 6C 3Journal 43Unranked 21

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Generalized ordered Wasserstein distance for sequential data. Pattern Recognit. Tung Doan, Hiep To, Thi Hong Vuong, Muriel Visani, Atsuhiro Takasu, Khoat Than
2026	J	`jnl`	LCA: Local Classifier Alignment for Continual Learning. CoRR Tung Tran, Danilo Vasconcellos Vargas, Khoat Than
2026	J	`jnl`	Using Synthetic Data to Estimate the True Error is Theoretically and Practically Doable. Mach. Learn. Thanh Hai Hoang, Duy-Tung Nguyen, Hung The Tran, Khoat Than
2025	A*	`conf`	Boosting Multiple Views for pretrained-based Continual Learning. ICLR Quyen Tran, Tung Lam Tran, Khanh Doan, Toan Tran, Dinh Q. Phung, Khoat Than, Trung Le
2025	A*	`conf`	DPaI: Differentiable Pruning at Initialization with Node-Path Balance Principle. ICLR Lichuan Xiang, Quan Nguyen-Tri, Lan-Cuong Nguyen, Hoang Pham, Khoat Than, Long Tran-Thanh, Hongkai Wen
2025	J	`jnl`	Gentle local robustness implies generalization. Mach. Learn. Khoat Than, Dat Phan, Giang Vu
2025	J	`jnl`	Non-vacuous Generalization Bounds for Deep Neural Networks without any modification to the trained models. CoRR Khoat Than, Dat Phan
2025	J	`jnl`	Out-of-vocabulary handling and topic quality control strategies in streaming topic models. Neurocomputing Tung Nguyen, Tung Pham, Ngo Van Linh, Ha-Bang Ban, Khoat Than
2025	J	`jnl`	Provably Improving Generalization of Few-Shot Models with Synthetic Data. CoRR Lan-Cuong Nguyen, Quan Nguyen-Tri, Bang Tran Khanh, Dung D. Le, Long Tran-Thanh, Khoat Than
2025	A*	`conf`	Provably Improving Generalization of Few-shot models with Synthetic Data. ICML Lan-Cuong Nguyen, Quan Nguyen-Tri, Bang Tran Khanh, Dung D. Le, Long Tran-Thanh, Khoat Than
2025	J	`jnl`	The Hidden Power of Normalization: Exponential Capacity Control in Deep Neural Networks. CoRR Khoat Than
2025	J	`jnl`	Using Synthetic Data to estimate the True Error is theoretically and practically doable. CoRR Thanh Hai Hoang, Duy-Tung Nguyen, Hung The Tran, Khoat Than
2025	J	`jnl`	Weighted Integrated Gradients for Feature Attribution. CoRR Kien Tran Duc Tuan, Tam Nguyen Trong, Son Nguyen Hoang, Khoat Than, Duc Anh Nguyen
2024	J	`jnl`	Continual variational dropout: a view of auxiliary local variables in continual learning. Mach. Learn. Nam Le Hai, Trang Nguyen, Ngo Van Linh, Thien Huu Nguyen, Khoat Than
2024	J	`jnl`	Gentle robustness implies Generalization. CoRR Khoat Than, Dat Phan, Giang Vu
2024	A*	`conf`	On Inference Stability for Diffusion Models. AAAI Viet Nguyen, Giang Vu, Tung Nguyen Thanh, Khoat Than, Toan Tran
2024	J	`jnl`	Partial ordered Wasserstein distance for sequential data. Neurocomputing Tung Doan, Tuan Phan, Phu Nguyen, Khoat Than, Muriel Visani, Atsuhiro Takasu
2024	—	`conf`	Robust Visual Reinforcement Learning by Prompt Tuning. ACCV (9) Tung Tran, Khoat Than, Danilo Vasconcellos Vargas
2023	—	`conf`	Bayesian method for bee counting with noise-labeled data. SoICT Duy-Tung Nguyen, Duc-Manh Nguyen, Dinh-Tan Pham, Khoat Than, Hong-Thai Pham, Hai Vu
2023	J	`jnl`	Dynamic Transformation of Prior Knowledge Into Bayesian Models for Data Streams. IEEE Trans. Knowl. Data Eng. Tran Xuan Bach, Nguyen Duc Anh, Ngo Van Linh, Khoat Than
2023	J	`jnl`	KOPPA: Improving Prompt-based Continual Learning with Key-Query Orthogonal Projection and Prototype-based One-Versus-All. CoRR Quyen Tran, Lam Tran, Khoat Than, Toan Tran, Dinh Q. Phung, Trung Le
2023	J	`jnl`	On Inference Stability for Diffusion Models. CoRR Viet Nguyen, Giang Vu, Tung Nguyen Thanh, Khoat Than, Toan Tran
2023	—	`conf`	Sharpness and Gradient Aware Minimization for Memory-based Continual Learning. SoICT Lam Tran Tung, Viet Nguyen Van, Phi Nguyen Hoang, Khoat Than
2023	J	`jnl`	Unsupervised image segmentation with robust virtual class contrast. Pattern Recognit. Lett. Khang Nguyen, Kien Do, Truong Vu, Khoat Than
2022	J	`jnl`	A graph convolutional topic model for short and noisy text streams. Neurocomputing Ngo Van Linh, Tran Xuan Bach, Khoat Than
2022	J	`jnl`	Adaptive infinite dropout for noisy and sparse data streams. Mach. Learn. Ha Nguyen, Hoang Pham, Son Nguyen, Ngo Van Linh, Khoat Than
2022	—	`conf`	Auxiliary Local Variables for Improving Regularization/Prior Approach in Continual Learning. PAKDD (1) Ngo Van Linh, Nam Le Hai, Hoang Pham, Khoat Than
2022	J	`jnl`	Balancing stability and plasticity when learning topic models from short and noisy text streams. Neurocomputing Tung Nguyen, Trung Mai, Nam Nguyen, Linh Ngo Van, Khoat Than
2022	J	`jnl`	Continual Learning with Optimal Transport based Mixture Model. CoRR Quyen Tran, Hoang Phan, Khoat Than, Dinh Q. Phung, Trung Le
2022	J	`jnl`	Face Swapping as A Simple Arithmetic Operation. CoRR Truong Vu, Kien Do, Khang Nguyen, Khoat Than
2022	J	`jnl`	From implicit to explicit feedback: A deep neural network for modeling sequential behaviours and long-short term preferences of online users. Neurocomputing Quyen Tran, Lam Tran, Linh Chu Hai, Ngo Van Linh, Khoat Than
2022	—	`conf`	Random Generative Adversarial Networks. SoICT Khoa Nguyen, Nghia Vu, Dung Nguyen, Khoat Than
2022	—	`conf`	Reducing Catastrophic Forgetting in Neural Networks via Gaussian Mixture Approximation. PAKDD (1) Hoang Phan, Anh Phan Tuan, Son Nguyen, Ngo Van Linh, Khoat Than
2022	J	`jnl`	Revisiting Supervised Word Embeddings. J. Inf. Sci. Eng. Dieu Vu, Khang Truong, Khanh Nguyen, Ngo Van Linh, Khoat Than
2021	J	`jnl`	Boosting prior knowledge in streaming variational Bayes. Neurocomputing Duc Anh Nguyen, Ngo Van Linh, Nguyen Kim Anh, Canh Hao Nguyen, Khoat Than
2021	J	`jnl`	From Implicit to Explicit feedback: A deep neural network for modeling sequential behaviours and long-short term preferences of online users. CoRR Quyen Tran, Lam Tran, Linh Chu Hai, Ngo Van Linh, Khoat Than
2021	J	`jnl`	Generalization of GANs under Lipschitz continuity and data augmentation. CoRR Khoat Than, Nghia Vu
2021	J	`jnl`	Improving Bayesian Inference in Deep Neural Networks with Variational Structured Dropout. CoRR Son Nguyen, Duong Nguyen, Khai Nguyen, Nhat Ho, Khoat Than, Hung Bui
2021	A*	`conf`	Structured Dropout Variational Inference for Bayesian Neural Networks. NeurIPS Son Nguyen, Duong Nguyen, Khai Nguyen, Khoat Than, Hung Bui, Nhat Ho
2020	J	`jnl`	Bag of biterms modeling for short texts. CoRR Anh Phan Tuan, Tran Xuan Bach, Thien Huu Nguyen, Ngo Van Linh, Khoat Than
2020	J	`jnl`	Bag of biterms modeling for short texts. Knowl. Inf. Syst. Anh Phan Tuan, Tran Xuan Bach, Thien Huu Nguyen, Ngo Van Linh, Khoat Than
2020	J	`jnl`	Dynamic transformation of prior knowledge into Bayesian models for data streams. CoRR Tran Xuan Bach, Nguyen Duc Anh, Ngo Van Linh, Khoat Than
2020	J	`jnl`	Graph Convolutional Topic Model for Data Streams. CoRR Ngo Van Linh, Tran Xuan Bach, Khoat Than
2020	J	`jnl`	MAP Estimation With Bernoulli Randomness, and Its Application to Text Analysis and Recommender Systems. IEEE Access Xuan Bui, Hieu Vu, Thi-Oanh Nguyen, Khoat Than
2020	J	`jnl`	Neural Poisson Factorization. IEEE Access Ngo Van Linh, Duc Anh Nguyen, Thai Binh Nguyen, Khoat Than
2020	A*	`conf`	Predictive Coding for Locally-Linear Control. ICML Rui Shu, Tung Nguyen, Yinlam Chow, Tuan Pham, Khoat Than, Mohammad Ghavamzadeh, Stefano Ermon, Hung H. Bui
2020	J	`jnl`	Predictive Coding for Locally-Linear Control. CoRR Rui Shu, Tung Nguyen, Yinlam Chow, Tuan Pham, Khoat Than, Mohammad Ghavamzadeh, Stefano Ermon, Hung H. Bui
2019	J	`jnl`	Eliminating overfitting of probabilistic topic models on short and noisy text: The role of dropout. Int. J. Approx. Reason. Cuong Ha, Van-Dang Tran, Ngo Van Linh, Khoat Than
2019	—	`conf`	Employing the Correspondence of Relations and Connectives to Identify Implicit Discourse Relations via Label Embeddings. ACL (1) Linh The Nguyen, Ngo Van Linh, Khoat Than, Thien Huu Nguyen
2019	—	`conf`	Enriching User Representation in Neural Matrix Factorization. RIVF Thanh Hai Hoang, Anh Phan Tuan, Ngo Van Linh, Khoat Than
2019	C	`conf`	From Implicit to Explicit Feedback: A deep neural network for modeling the sequential behavior of online users. ACML Anh Phan Tuan, Nhat Nguyen Trong, Duong Bui Trong, Ngo Van Linh, Khoat Than
2019	—	`conf`	Infinite Dropout for training Bayesian models from data streams. IEEE BigData Van-Son Nguyen, Duc-Tung Nguyen, Ngo Van Linh, Khoat Than
2019	—	`conf`	Marking Mechanism in Sequence-to-sequence Model for Mapping Language to Logical Form. KSE Minh-Tien Nguyen, Khoat Than, Minh Le Nguyen
2018	—	`conf`	A Fast Algorithm for Posterior Inference with Latent Dirichlet Allocation. ACIIDS (2) Bui Thi-Thanh-Xuan, Vu Van-Tu, Atsuhiro Takasu, Khoat Than
2018	J	`jnl`	A Flexible Stochastic Method for Solving the MAP Problem in Topic Models. Computación y Sistemas Tu Vu, Xuan Bui, Khoat Than, Ryutaro Ichise
2018	J	`jnl`	Collaborative Topic Model for Poisson distributed ratings. Int. J. Approx. Reason. Hoa M. Le, Son Ta Cong, Quyen Pham The, Ngo Van Linh, Khoat Than
2018	—	`conf`	Evaluating Named-Entity Recognition Approaches in Plant Molecular Biology. MIWAI Huy Do, Khoat Than, Pierre Larmande
2018	—	`conf`	Reducing Class Overlapping in Supervised Dimension Reduction. SoICT Nguyen Trong Tung, Vu Hoang Dieu, Khoat Than, Ngo Van Linh
2017	J	`jnl`	An effective and interpretable method for document classification. Knowl. Inf. Syst. Ngo Van Linh, Nguyen Kim Anh, Khoat Than, Chien Nguyen Dang
2017	—	`conf`	Keeping Priors in Streaming Bayesian Learning. PAKDD (2) Duc Anh Nguyen, Ngo Van Linh, Nguyen Kim Anh, Khoat Than
2017	—	`conf`	Sparse Stochastic Inference with Regularization. PAKDD (1) Tung Doan, Khoat Than
2016	—	`conf`	Enabling Hierarchical Dirichlet Processes to Work Better for Short Texts at Large Scale. PAKDD (2) Khai Mai, Sang Mai, Anh Nguyen, Ngo Van Linh, Khoat Than
2016	—	`conf`	Streaming aspect-sentiment analysis. RIVF Vu Le Anh, Chien Phung Van, Cuong Vu Cao, Ngo Van Linh, Khoat Than
2015	—	`conf`	Effective and Interpretable Document Classification Using Distinctly Labeled Dirichlet Process Mixture Models of von Mises-Fisher Distributions. DASFAA (2) Ngo Van Linh, Nguyen Kim Anh, Khoat Than, Nguyen Nguyen Tat
2014	—	`conf`	An Effective NMF-Based Method for Supervised Dimension Reduction. KSE Ngo Van Linh, Nguyen Kim Anh, Khoat Than
2014	J	`jnl`	An effective framework for supervised dimension reduction. Neurocomputing Khoat Than, Tu Bao Ho, Duy Khuong Nguyen
2014	C	`conf`	Dual online inference for latent Dirichlet allocation. ACML Khoat Than, Tung Doan
2014	J	`jnl`	Modeling the diversity and log-normality of data. Intell. Data Anal. Khoat Than, Tu Bao Ho
2013	J	`jnl`	Probable convexity and its application to Correlated Topic Models. CoRR Khoat Than, Tu Bao Ho
2013	—	`conf`	Simplicial nonnegative matrix factorization. RIVF Duy Khuong Nguyen, Khoat Than, Tu Bao Ho
2012	—	`conf`	Fully Sparse Topic Models. ECML/PKDD (1) Khoat Than, Tu Bao Ho
2012	J	`jnl`	Managing sparsity, time, and quality of inference in topic models CoRR Khoat Than, Tu Bao Ho
2012	C	`conf`	Supervised dimension reduction with topic models. ACML Khoat Than, Tu Bao Ho, Duy Khuong Nguyen, Pham Ngoc Khanh