Minh-Ngoc Tran

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 36

Top Topics

Bayesian Models

Variational Bayes

Top Venues

J. Comput. Graph. Stat.

Publications

Minh-Ngoc Tran, Young-Han Kim
Optimized resource usage with hybrid auto-scaling system for knative serverless edge computing. Future Gener. Comput. Syst. 152 (2024)
Minh-Ngoc Tran, Young-Han Kim
Concurrent service auto-scaling for Knative resource quota-based serverless system. Future Gener. Comput. Syst. 160 (2024)
Minh-Ngoc Tran, Van-Binh Duong, Young-Han Kim
Design of Computing-Aware Traffic Steering Architecture for 5G Mobile User Plane. IEEE Access 12 (2024)
Nhat Minh Nguyen, Minh-Ngoc Tran, Rohitash Chandra
Sequential reversible jump MCMC for dynamic Bayesian neural networks. Neurocomputing 564 (2024)
Anna Lopatnikova, Minh-Ngoc Tran
Quantum Variational Bayes on Manifolds. ICASSP (2023)
Minh-Ngoc Tran, Paco Tseng, Robert Kohn
Particle Mean Field Variational Bayes. CoRR (2023)
Chen Liu, Minh-Ngoc Tran, Chao Wang, Richard Gerlach, Robert Kohn
DeepVol: A Deep Transfer Learning Approach for Universal Asset Volatility Modeling. CoRR (2023)
Chen Liu, Chao Wang, Minh-Ngoc Tran, Robert Kohn
Realized recurrent conditional heteroskedasticity model for volatility modelling. CoRR (2023)
Ta Phuong Bac, Minh-Ngoc Tran, Young-Han Kim
Serverless Computing Approach for Deploying Machine Learning Applications in Edge Layer. ICOIN (2022)
Minh-Ngoc Tran, Xuan Tuong Vu, Young-Han Kim
Proactive Stateful Fault-Tolerant System for Kubernetes Containerized Services. IEEE Access 10 (2022)
Minh-Ngoc Tran, Younghan Kim
Network Performance Benchmarking for Containerized Infrastructure in NFV environment. NetSoft (2022)
Renlong Jie, Junbin Gao, Andrey Vasnev, Minh-Ngoc Tran
Adaptive hierarchical hyper-gradient descent. Int. J. Mach. Learn. Cybern. 13 (12) (2022)
Dinh Dai Vu, Minh-Ngoc Tran, Young-Han Kim
Predictive Hybrid Autoscaling for Containerized Applications. IEEE Access 10 (2022)
Minh-Ngoc Tran, Dinh Dai Vu, Younghan Kim
A Survey of Autoscaling in Kubernetes. ICUFN (2022)
Bingxin Zhou, Junbin Gao, Minh-Ngoc Tran, Richard Gerlach
Manifold Optimization-Assisted Gaussian Variational Approximation. J. Comput. Graph. Stat. 30 (4) (2021)
Anna Lopatnikova, Minh-Ngoc Tran
An Introduction to Quantum Computing for Statisticians. CoRR (2021)
Matias Quiroz, Minh-Ngoc Tran, Mattias Villani, Robert Kohn, Khue-Dung Dang
The Block-Poisson Estimator for Optimally Tuned Exact Subsampling MCMC. J. Comput. Graph. Stat. 30 (4) (2021)
Briytone Mutichiro, Minh-Ngoc Tran, Young-Han Kim
QoS-Based Service-Time Scheduling in the IoT-Edge Cloud. Sensors 21 (17) (2021)
Minh-Ngoc Tran, Younghan Kim
A Cloud QoS-driven Scheduler based on Deep Reinforcement Learning. ICTC (2021)
Xuejun Yu, David J. Nott, Minh-Ngoc Tran, Nadja Klein
Assessment and Adjustment of Approximate Inference Algorithms Using the Law of Total Variance. J. Comput. Graph. Stat. 30 (4) (2021)
Renlong Jie, Junbin Gao, Andrey Vasnev, Minh-Ngoc Tran
HyperTube: A Framework for Population-Based Online Hyperparameter Optimization with Resource Constraints. IEEE Access 8 (2020)
Robert Salomone, Matias Quiroz, Robert Kohn, Mattias Villani, Minh-Ngoc Tran
Spectral Subsampling MCMC for Stationary Time Series. ICML (2020)
Renlong Jie, Junbin Gao, Andrey Vasnev, Minh-Ngoc Tran
Regularized Flexible Activation Function Combination for Deep Neural Networks. ICPR (2020)
Zhengkun Li, Minh-Ngoc Tran, Chao Wang, Richard Gerlach, Junbin Gao
A Bayesian Long Short-Term Memory Model for Value at Risk and Expected Shortfall Joint Forecasting. CoRR (2020)
Renlong Jie, Junbin Gao, Andrey Vasnev, Minh-Ngoc Tran
Adaptive Multi-level Hyper-gradient Descent. CoRR (2020)
Ngoc-Thanh Dinh, Minh-Ngoc Tran, Youngki Park, Younghan Kim
An Information-centric NFV-based System Implementation for Disaster Management Services. ICOIN (2020)
Minh-Ngoc Tran, Younghan Kim
NDN-based Emergency Communication over Edge Computing Infrastructure. ICTC (2020)
David Gunawan, Khue-Dung Dang, Matias Quiroz, Robert Kohn, Minh-Ngoc Tran
Subsampling sequential Monte Carlo for static Bayesian models. Stat. Comput. 30 (6) (2020)
Dao Thanh Tung, Minh-Ngoc Tran, Tran Manh Cuong
Bayesian adaptive lasso with variational Bayes for variable selection in high-dimensional generalized linear mixed models. Commun. Stat. Simul. Comput. 48 (2) (2019)
Minh-Ngoc Tran, Dang Hai Nguyen, Duy Nguyen
Variational Bayes on Manifolds. CoRR (2019)
Khue-Dung Dang, Matias Quiroz, Robert Kohn, Minh-Ngoc Tran, Mattias Villani
Hamiltonian Monte Carlo with Energy Conserving Subsampling. J. Mach. Learn. Res. 20 (2019)
Bingxin Zhou, Junbin Gao, Minh-Ngoc Tran, Richard Gerlach
Manifold Optimisation Assisted Gaussian Variational Approximation. CoRR (2019)
David Gunawan, Minh-Ngoc Tran, Kosuke Suzuki, Josef Dick, Robert Kohn
Computationally efficient Bayesian estimation of high-dimensional Archimedean copulas with discrete and mixed margins. Stat. Comput. 29 (5) (2019)
Victor M. H. Ong, David J. Nott, Minh-Ngoc Tran, Scott A. Sisson, Christopher C. Drovandi
Variational Bayes with synthetic likelihood. Stat. Comput. 28 (4) (2018)
Victor M. H. Ong, David J. Nott, Minh-Ngoc Tran, Scott A. Sisson, Christopher C. Drovandi
Likelihood-free inference in high dimensions with synthetic likelihood. Comput. Stat. Data Anal. 128 (2018)
Minh-Ngoc Tran, Michael K. Pitt, Robert Kohn
Adaptive Metropolis-Hastings sampling using reversible dependent mixture proposals. Stat. Comput. 26 (1-2) (2016)
David J. Nott, Lucy Marshall, Minh-Ngoc Tran
The ensemble Kalman filter is an ABC algorithm. Stat. Comput. 22 (6) (2012)
David J. Nott, Minh-Ngoc Tran, Chenlei Leng
Variational approximation for heteroscedastic linear models and matching pursuit algorithms. Stat. Comput. 22 (2) (2012)
Minh-Ngoc Tran, David J. Nott, Chenlei Leng
The predictive Lasso. Stat. Comput. 22 (5) (2012)
Marcus Hutter, Minh-Ngoc Tran
Model selection with the Loss Rank Principle. Comput. Stat. Data Anal. 54 (5) (2010)
Marcus Hutter, Minh-Ngoc Tran
Model Selection with the Loss Rank Principle CoRR (2010)