Vu Nguyen

发表

Filtering Bayesian optimization approach in weakly specified search space

Cheng Li, Santu Rana, Vu Nguyen, 2018, Knowledge and Information Systems.

Predictive Variance Reduction Search

S. Rana, S. Venkatesh, Vu Nguyen, 2017 .

Bayesian Optimization with Monotonicity Information

S. Rana, S. Venkatesh, Vu Nguyen, 2017 .

Graph-based Kernel Machine for Scalable Semi-supervised Learning

Dinh Q. Phung, Vu Nguyen, Khanh-Duy Nguyen, 2016 .

Sparkling Vector Machines

Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, 2015 .

GoGP: scalable geometric-based Gaussian process for online regression

Dinh Q. Phung, Vu Nguyen, Khanh-Duy Nguyen, 2018, Knowledge and Information Systems.

Practical Batch Bayesian Optimization for Less Expensive Functions pdf

Cheng Li, Svetha Venkatesh, Santu Rana, 2018, ArXiv.

Learning Multifaceted Latent Activities from Heterogeneous Mobile Data

Mohan Kumar, Svetha Venkatesh, Dinh Q. Phung, 2016, 2016 IEEE International Conference on Data Science and Advanced Analytics (DSAA).

A Simultaneous Extraction of Context and Community from pervasive signals using nested Dirichlet process

Flora D. Salim, Dinh Q. Phung, Duc V. Le, 2017, Pervasive Mob. Comput..

High Dimensional Bayesian Optimization using Dropout

Cheng Li, Svetha Venkatesh, Alistair Shilton, 2018, IJCAI.

Exploration Enhanced Expected Improvement for Bayesian Optimization

Svetha Venkatesh, Santu Rana, Vu Nguyen, 2018, ECML/PKDD.

Budgeted Batch Bayesian Optimization With Unknown Batch Sizes pdf

Cheng Li, Svetha Venkatesh, Santu Rana, 2017, ArXiv.

Multiple Kernel Learning with Data Augmentation

Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, 2016, ACML.

Tuning Mixed Input Hyperparameters on the Fly for Efficient Population Based AutoRL pdf

Stephen Roberts, Vu Nguyen, Shaan Desai, 2021, NeurIPS.

Provably Efficient Online Hyperparameter Optimization with Population-Based Bandits

Stephen Roberts, Vu Nguyen, Jack Parker-Holder, 2020, NeurIPS.

Knowing The What But Not The Where in Bayesian Optimization pdf

Michael A. Osborne, Vu Nguyen, Vu Nguyen, 2019, ICML.

Regret for Expected Improvement over the Best-Observed Value and Stopping Condition

Cheng Li, Svetha Venkatesh, Santu Rana, 2017, ACML.

Budgeted Batch Bayesian Optimization

Cheng Li, Svetha Venkatesh, Santu Rana, 2016, 2016 IEEE 16th International Conference on Data Mining (ICDM).

Approximation Vector Machines for Large-scale Online Learning

Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, 2016, J. Mach. Learn. Res..

Algorithmic Assurance: An Active Approach to Algorithmic Testing using Bayesian Optimisation

Svetha Venkatesh, Santu Rana, Vu Nguyen, 2018, NeurIPS.

Label-Sensitive Task Grouping by Bayesian Nonparametric Approach for Multi-Task Multi-Label Learning

Hui Xiong, Xiao Zhang, Wenzhong Li, 2018, IJCAI.

Bayesian Optimization for Accelerating Hyper-Parameter Tuning

Vu Nguyen, Vu Nguyen, 2019, 2019 IEEE Second International Conference on Artificial Intelligence and Knowledge Engineering (AIKE).

Think Global and Act Local: Bayesian Optimisation over High-Dimensional Categorical and Mixed Search Spaces pdf

Michael A. Osborne, Vu Nguyen, Huong Ha, 2021, ICML.

A Bayesian Nonparametric Approach for Multi-label Classification

Cheng Li, Svetha Venkatesh, Santu Rana, 2016, ACML.

Bayesian Topic Regression for Causal Inference pdf

Vu Nguyen, Maximilian Ahrens, Julian Ashwin, 2021, EMNLP.

Bayesian Optimisation over Multiple Continuous and Categorical Inputs pdf

Michael A. Osborne, Vu Nguyen, Binxin Ru, 2019, ICML.

One-Pass Logistic Regression for Label-Drift and Large-Scale Classification on Distributed Systems

Trung Le, Svetha Venkatesh, Tu Dinh Nguyen, 2016, 2016 IEEE 16th International Conference on Data Mining (ICDM).

Indian Buffet Neural Networks for Continual Learning pdf

Stefan Zohren, Stephen Roberts, Vu Nguyen, 2019, ArXiv.

Hierarchical Indian buffet neural networks for Bayesian continual learning

Stefan Zohren, Stephen Roberts, Vu Nguyen, 2019, UAI.

Cascade Bayesian Optimization

Svetha Venkatesh, Santu Rana, Vu Nguyen, 2016, Australasian Conference on Artificial Intelligence.

Sparse Adaptive Multi-hyperplane Machine

Trung Le, Dinh Q. Phung, Khanh Nguyen, 2016, PAKDD.

Nonparametric Budgeted Stochastic Gradient Descent

Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, 2016, AISTATS.

Dual Space Gradient Descent for Online Learning

Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, 2016, NIPS.

Budgeted Semi-supervised Support Vector Machine

Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, 2016, UAI.

Mixed-Variable Black-Box Optimisation Using Value Proposal Trees

I. Chades, A. Dezfouli, Vu Nguyen, 2023, AAAI.

Discriminative Bayesian Nonparametric Clustering

Trung Le, Dinh Q. Phung, Vu Nguyen, 2017, IJCAI.

Hierarchical Indian Buffet Neural Networks for Bayesian Continual Learning Supplementary material

Stephen J. Roberts, S. Zohren, Vu Nguyen, 2021 .

Learning Multi-faceted Activities from Heterogeneous Data with the Product Space Hierarchical Dirichlet Processes

Svetha Venkatesh, Dinh Q. Phung, Vu Nguyen, 2016, PAKDD Workshops.

High Dimensional Bayesian Optimization with Elastic Gaussian Process

Cheng Li, Svetha Venkatesh, Santu Rana, 2017, ICML.

Bayesian Optimization in Weakly Specified Search Space

Cheng Li, Svetha Venkatesh, Santu Rana, 2017, 2017 IEEE International Conference on Data Mining (ICDM).

Tuning Mixed Input Hyperparameters on the Fly for Efficient Population Based AutoRL

Stephen J. Roberts, K. Kavukcuoglu, Jack Parker-Holder, 2021, Neural Information Processing Systems.

Hierarchical Indian buffet neural networks for Bayesian continual learning

Stephen J. Roberts, S. Zohren, Vu Nguyen, 2019, UAI.