Minh-Ngoc Tran

54 papers A* 1B 2Misc 1Journal 45Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Bures-Wasserstein Importance-Weighted Evidence Lower Bound: Exposition and Applications. CoRR Peiwen Jiang, Takuo Matsubara, Minh-Ngoc Tran
2026	J	`jnl`	Enabling Service Continuity for Stateful Service Segmentation in Mobile Edge Computing Toward 6G. IEEE Access Kiem Nguyen Trung, Minh-Ngoc Tran, Younghan Kim
2026	J	`jnl`	Importance Weighted Variational Inference without the Reparameterization Trick. CoRR Kamélia Daudel, Minh-Ngoc Tran, Cheng Zhang
2026	J	`jnl`	Wasserstein Gaussianization and Efficient Variational Bayes for Robust Bayesian Synthetic Likelihood. J. Comput. Graph. Stat. Nhat-Minh Nguyen, Minh-Ngoc Tran, Christopher C. Drovandi, David J. Nott
2025	J	`jnl`	CPformer - Concept and Physics enhanced Transformer for Time Series Forecasting. CoRR Hongwei Ma, Junbin Gao, Minh-Ngoc Tran
2025	J	`jnl`	Deep Learning Enhanced Multivariate GARCH. CoRR Haoyuan Wang, Chen Liu, Minh-Ngoc Tran, Chao Wang
2025	J	`jnl`	Design of 5G Architecture Enhancements for Supporting Edge Split Computing Service Pipeline. IEEE Access Minh-Ngoc Tran, Kiem Nguyen Trung, Young-Han Kim
2025	J	`jnl`	From Noise to Laws: Regularized Time-Series Forecasting via Denoised Dynamic Graphs. CoRR Hongwei Ma, Junbin Gao, Minh-Ngoc Tran
2025	J	`jnl`	PREIG: Physics-informed and Reinforcement-driven Interpretable GRU for Commodity Demand Forecasting. CoRR Hongwei Ma, Junbin Gao, Minh-Ngoc Tran
2025	J	`jnl`	Variational Bayesian inference for models with nuisance parameters and an intractable likelihood. Stat. Comput. Y. H. Paco Tseng, Minh-Ngoc Tran, Robert Kohn
2024	J	`jnl`	Concurrent service auto-scaling for Knative resource quota-based serverless system. Future Gener. Comput. Syst. Minh-Ngoc Tran, Young-Han Kim
2024	J	`jnl`	Design of 5G Architecture Enhancements for Supporting Serverless Computing. IEEE Access Minh-Ngoc Tran, Young-Han Kim
2024	J	`jnl`	Design of Computing-Aware Traffic Steering Architecture for 5G Mobile User Plane. IEEE Access Minh-Ngoc Tran, Van-Binh Duong, Young-Han Kim
2024	J	`jnl`	Optimized resource usage with hybrid auto-scaling system for knative serverless edge computing. Future Gener. Comput. Syst. Minh-Ngoc Tran, Young-Han Kim
2024	J	`jnl`	Sequential reversible jump MCMC for dynamic Bayesian neural networks. Neurocomputing Nhat Minh Nguyen, Minh-Ngoc Tran, Rohitash Chandra
2023	J	`jnl`	DeepVol: A Deep Transfer Learning Approach for Universal Asset Volatility Modeling. CoRR Chen Liu, Minh-Ngoc Tran, Chao Wang, Richard Gerlach, Robert Kohn
2023	J	`jnl`	Particle Mean Field Variational Bayes. CoRR Minh-Ngoc Tran, Paco Tseng, Robert Kohn
2023	Misc	`conf`	Quantum Variational Bayes on Manifolds. ICASSP Anna Lopatnikova, Minh-Ngoc Tran
2023	J	`jnl`	Realized recurrent conditional heteroskedasticity model for volatility modelling. CoRR Chen Liu, Chao Wang, Minh-Ngoc Tran, Robert Kohn
2022	—	`conf`	A Survey of Autoscaling in Kubernetes. ICUFN Minh-Ngoc Tran, Dinh Dai Vu, Younghan Kim
2022	J	`jnl`	Adaptive hierarchical hyper-gradient descent. Int. J. Mach. Learn. Cybern. Renlong Jie, Junbin Gao, Andrey Vasnev, Minh-Ngoc Tran
2022	B	`conf`	Network Performance Benchmarking for Containerized Infrastructure in NFV environment. NetSoft Minh-Ngoc Tran, Younghan Kim
2022	J	`jnl`	Predictive Hybrid Autoscaling for Containerized Applications. IEEE Access Dinh Dai Vu, Minh-Ngoc Tran, Young-Han Kim
2022	J	`jnl`	Proactive Stateful Fault-Tolerant System for Kubernetes Containerized Services. IEEE Access Minh-Ngoc Tran, Xuan Tuong Vu, Young-Han Kim
2022	—	`conf`	Serverless Computing Approach for Deploying Machine Learning Applications in Edge Layer. ICOIN Ta Phuong Bac, Minh-Ngoc Tran, Young-Han Kim
2021	—	`conf`	A Cloud QoS-driven Scheduler based on Deep Reinforcement Learning. ICTC Minh-Ngoc Tran, Younghan Kim
2021	J	`jnl`	An Introduction to Quantum Computing for Statisticians. CoRR Anna Lopatnikova, Minh-Ngoc Tran
2021	J	`jnl`	Assessment and Adjustment of Approximate Inference Algorithms Using the Law of Total Variance. J. Comput. Graph. Stat. Xuejun Yu, David J. Nott, Minh-Ngoc Tran, Nadja Klein
2021	J	`jnl`	Manifold Optimization-Assisted Gaussian Variational Approximation. J. Comput. Graph. Stat. Bingxin Zhou, Junbin Gao, Minh-Ngoc Tran, Richard Gerlach
2021	J	`jnl`	QoS-Based Service-Time Scheduling in the IoT-Edge Cloud. Sensors Briytone Mutichiro, Minh-Ngoc Tran, Young-Han Kim
2021	J	`jnl`	The Block-Poisson Estimator for Optimally Tuned Exact Subsampling MCMC. J. Comput. Graph. Stat. Matias Quiroz, Minh-Ngoc Tran, Mattias Villani, Robert Kohn, Khue-Dung Dang
2021	J	`jnl`	Variational Bayes on manifolds. Stat. Comput. Minh-Ngoc Tran, Dang H. Nguyen, Duy Nguyen
2020	J	`jnl`	A Bayesian Long Short-Term Memory Model for Value at Risk and Expected Shortfall Joint Forecasting. CoRR Zhengkun Li, Minh-Ngoc Tran, Chao Wang, Richard Gerlach, Junbin Gao
2020	J	`jnl`	Adaptive Multi-level Hyper-gradient Descent. CoRR Renlong Jie, Junbin Gao, Andrey Vasnev, Minh-Ngoc Tran
2020	—	`conf`	An Information-centric NFV-based System Implementation for Disaster Management Services. ICOIN Ngoc-Thanh Dinh, Minh-Ngoc Tran, YoungKi Park, Younghan Kim
2020	J	`jnl`	HyperTube: A Framework for Population-Based Online Hyperparameter Optimization with Resource Constraints. IEEE Access Renlong Jie, Junbin Gao, Andrey Vasnev, Minh-Ngoc Tran
2020	—	`conf`	NDN-based Emergency Communication over Edge Computing Infrastructure. ICTC Minh-Ngoc Tran, Younghan Kim
2020	B	`conf`	Regularized Flexible Activation Function Combination for Deep Neural Networks. ICPR Renlong Jie, Junbin Gao, Andrey Vasnev, Minh-Ngoc Tran
2020	J	`jnl`	Regularized Flexible Activation Function Combinations for Deep Neural Networks. CoRR Renlong Jie, Junbin Gao, Andrey Vasnev, Minh-Ngoc Tran
2020	A*	`conf`	Spectral Subsampling MCMC for Stationary Time Series. ICML Robert Salomone, Matias Quiroz, Robert Kohn, Mattias Villani, Minh-Ngoc Tran
2020	J	`jnl`	Subsampling sequential Monte Carlo for static Bayesian models. Stat. Comput. David Gunawan, Khue-Dung Dang, Matias Quiroz, Robert Kohn, Minh-Ngoc Tran
2019	J	`jnl`	Bayesian adaptive lasso with variational Bayes for variable selection in high-dimensional generalized linear mixed models. Commun. Stat. Simul. Comput. Dao Thanh Tung, Minh-Ngoc Tran, Tran Manh Cuong
2019	J	`jnl`	Computationally efficient Bayesian estimation of high-dimensional Archimedean copulas with discrete and mixed margins. Stat. Comput. David Gunawan, Minh-Ngoc Tran, Kosuke Suzuki, Josef Dick, Robert Kohn
2019	J	`jnl`	Hamiltonian Monte Carlo with Energy Conserving Subsampling. J. Mach. Learn. Res. Khue-Dung Dang, Matias Quiroz, Robert Kohn, Minh-Ngoc Tran, Mattias Villani
2019	J	`jnl`	Manifold Optimisation Assisted Gaussian Variational Approximation. CoRR Bingxin Zhou, Junbin Gao, Minh-Ngoc Tran, Richard Gerlach
2019	J	`jnl`	Variational Bayes on Manifolds. CoRR Minh-Ngoc Tran, Dang Hai Nguyen, Duy Nguyen
2018	J	`jnl`	Likelihood-free inference in high dimensions with synthetic likelihood. Comput. Stat. Data Anal. Victor M. H. Ong, David J. Nott, Minh-Ngoc Tran, Scott A. Sisson, Christopher C. Drovandi
2018	J	`jnl`	Variational Bayes with synthetic likelihood. Stat. Comput. Victor M. H. Ong, David J. Nott, Minh-Ngoc Tran, Scott A. Sisson, Christopher C. Drovandi
2016	J	`jnl`	Adaptive Metropolis-Hastings sampling using reversible dependent mixture proposals. Stat. Comput. Minh-Ngoc Tran, Michael K. Pitt, Robert Kohn
2012	J	`jnl`	The ensemble Kalman filter is an ABC algorithm. Stat. Comput. David J. Nott, Lucy A. Marshall, Minh-Ngoc Tran
2012	J	`jnl`	The predictive Lasso. Stat. Comput. Minh-Ngoc Tran, David J. Nott, Chenlei Leng
2012	J	`jnl`	Variational approximation for heteroscedastic linear models and matching pursuit algorithms. Stat. Comput. David J. Nott, Minh-Ngoc Tran, Chenlei Leng
2010	J	`jnl`	Model Selection with the Loss Rank Principle CoRR Marcus Hutter, Minh-Ngoc Tran
2010	J	`jnl`	Model selection with the Loss Rank Principle. Comput. Stat. Data Anal. Marcus Hutter, Minh-Ngoc Tran