Vu Nguyen - RankMe

49 papers A* 12A 5B 4C 4Journal 17Unranked 7

Year	Rank	Type	Title / Venue / Authors
2025	A	`conf`	High Dimensional Bayesian Optimization using Lasso Variable Selection. AISTATS Vu Viet Hoang, Hung The Tran, Sunil Gupta, Vu Nguyen
2025	J	`jnl`	High Dimensional Bayesian Optimization using Lasso Variable Selection. CoRR Vu Viet Hoang, Hung The Tran, Sunil Gupta, Vu Nguyen
2025	A	`conf`	In-context Learning for Addressing User Cold-start in Sequential Movie Recommenders. RecSys Xurong Liang, Vu Nguyen, Vuong Le, Paul Albert, Julien Monteil
2025	J	`jnl`	On the Mechanisms of Collaborative Learning in VAE Recommenders. CoRR Tung-Long Vuong, Julien Monteil, Hien Dang, Volodymyr Vaskovych, Trung Le, Vu Nguyen
2025	J	`jnl`	Personalized home based neurostimulation via AI optimization augments sustained attention. npj Digit. Medicine Roi Cohen Kadosh, Delia Ciobotaru, Malin I. Karstens, Vu Nguyen
2024	C	`ed.`	Asian Conference on Machine Learning, 5-8 December 2024, Hanoi, Vietnam. ACML Vu Nguyen, Hsuan-Tien Lin
2024	A	`conf`	Self-Supervision Improves Diffusion Models for Tabular Data Imputation. CIKM Yixin Liu, Thalaiyasingam Ajanthan, Hisham Husain, Vu Nguyen
2024	J	`jnl`	Self-Supervision Improves Diffusion Models for Tabular Data Imputation. CoRR Yixin Liu, Thalaiyasingam Ajanthan, Hisham Husain, Vu Nguyen
2021	J	`jnl`	Personalized brain stimulation for effective neurointervention across participants. PLoS Comput. Biol. Nienke E. R. van Bueren, Thomas L. Reed, Vu Nguyen, James G. Sheffield, Sanne H. G. van der Ven, Michael A. Osborne, Evelyn H. Kroesbergen, Roi Cohen Kadosh
2020	J	`jnl`	Bayesian optimisation in unknown bounded search domains. Knowl. Based Syst. Julian Berk, Sunil Gupta, Santu Rana, Vu Nguyen, Svetha Venkatesh
2020	J	`jnl`	Incorporating Expert Prior Knowledge into Experimental Design via Posterior Sampling. CoRR Cheng Li, Sunil Gupta, Santu Rana, Vu Nguyen, Antonio Robles-Kelly, Svetha Venkatesh
2019	J	`jnl`	Accelerating Experimental Design by Incorporating Experimenter Hunches. CoRR Cheng Li, Santu Rana, Sunil Gupta, Vu Nguyen, Svetha Venkatesh, Alessandra Sutti, David Rubin de Celis Leal, Teo Slezak, Murray Height, Mazher Mohammed, Ian Gibson
2019	—	`conf`	Bayesian Optimization for Accelerating Hyper-Parameter Tuning. AIKE Vu Nguyen
2019	A*	`conf`	Efficient Bayesian Optimization for Uncertainty Reduction Over Perceived Optima Locations. ICDM Vu Nguyen, Sunil Gupta, Santu Rana, My T. Thai, Cheng Li, Svetha Venkatesh
2019	J	`jnl`	Filtering Bayesian optimization approach in weakly specified search space. Knowl. Inf. Syst. Vu Nguyen, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh
2019	J	`jnl`	GoGP: scalable geometric-based Gaussian process for online regression. Knowl. Inf. Syst. Trung Le, Khanh Nguyen, Vu Nguyen, Tu Dinh Nguyen, Dinh Q. Phung
2018	A*	`conf`	Accelerating Experimental Design by Incorporating Experimenter Hunches. ICDM Cheng Li, Santu Rana, Sunil Gupta, Vu Nguyen, Svetha Venkatesh, Alessandra Sutti, David Rubin de Celis Leal, Teo Slezak, Murray Height, Mazher Mohammed, Ian Gibson
2018	A*	`conf`	Algorithmic Assurance: An Active Approach to Algorithmic Testing using Bayesian Optimisation. NeurIPS Shivapratap Gopakumar, Sunil Gupta, Santu Rana, Vu Nguyen, Svetha Venkatesh
2018	—	`conf`	Exploration Enhanced Expected Improvement for Bayesian Optimization. ECML/PKDD (2) Julian Berk, Vu Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh
2018	A*	`conf`	Label-Sensitive Task Grouping by Bayesian Nonparametric Approach for Multi-Task Multi-Label Learning. IJCAI Xiao Zhang, Wenzhong Li, Vu Nguyen, Fuzhen Zhuang, Hui Xiong, Sanglu Lu
2018	J	`jnl`	Practical Batch Bayesian Optimization for Less Expensive Functions. CoRR Vu Nguyen, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh
2017	J	`jnl`	A Simultaneous Extraction of Context and Community from pervasive signals using nested Dirichlet process. Pervasive Mob. Comput. Nguyen Cong Thuong, Vu Nguyen, Flora D. Salim, Duc Viet Le, Dinh Q. Phung
2017	J	`jnl`	Approximation Vector Machines for Large-scale Online Learning. J. Mach. Learn. Res. Trung Le, Tu Dinh Nguyen, Vu Nguyen, Dinh Q. Phung
2017	A*	`conf`	Bayesian Optimization in Weakly Specified Search Space. ICDM Vu Nguyen, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh
2017	J	`jnl`	Budgeted Batch Bayesian Optimization With Unknown Batch Sizes. CoRR Vu Nguyen, Santu Rana, Sunil Gupta, Cheng Li, Svetha Venkatesh
2017	A*	`conf`	Discriminative Bayesian Nonparametric Clustering. IJCAI Vu Nguyen, Dinh Q. Phung, Trung Le, Hung Bui
2017	A*	`conf`	GoGP: Fast Online Regression with Gaussian Processes. ICDM Trung Le, Khanh Nguyen, Vu Nguyen, Tu Dinh Nguyen, Dinh Q. Phung
2017	A*	`conf`	High Dimensional Bayesian Optimization using Dropout. IJCAI Cheng Li, Sunil Gupta, Santu Rana, Vu Nguyen, Svetha Venkatesh, Alistair Shilton
2017	A*	`conf`	High Dimensional Bayesian Optimization with Elastic Gaussian Process. ICML Santu Rana, Cheng Li, Sunil Gupta, Vu Nguyen, Svetha Venkatesh
2017	C	`conf`	Regret for Expected Improvement over the Best-Observed Value and Stopping Condition. ACML Vu Nguyen, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh
2016	C	`conf`	A Bayesian Nonparametric Approach for Multi-label Classification. ACML Vu Nguyen, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh
2016	J	`jnl`	Approximation Vector Machines for Large-scale Online Learning. CoRR Trung Le, Tu Dinh Nguyen, Vu Nguyen, Dinh Q. Phung
2016	A*	`conf`	Budgeted Batch Bayesian Optimization. ICDM Vu Nguyen, Santu Rana, Sunil Kumar Gupta, Cheng Li, Svetha Venkatesh
2016	A	`conf`	Budgeted Semi-supervised Support Vector Machine . UAI Trung Le, Phuong Duong, Mi Dinh, Tu Dinh Nguyen, Vu Nguyen, Dinh Q. Phung
2016	—	`conf`	Cascade Bayesian Optimization. Australasian Conference on Artificial Intelligence Thanh Dai Nguyen, Sunil Gupta, Santu Rana, Vu Nguyen, Svetha Venkatesh, Kyle J. Deane, Paul G. Sanders
2016	B	`conf`	Distributed data augmented support vector machine on Spark. ICPR Tu Dinh Nguyen, Vu Nguyen, Trung Le, Dinh Q. Phung
2016	—	`conf`	Dual Space Gradient Descent for Online Learning. NIPS Trung Le, Tu Dinh Nguyen, Vu Nguyen, Dinh Q. Phung
2016	—	`conf`	Learning Multi-faceted Activities from Heterogeneous Data with the Product Space Hierarchical Dirichlet Processes. PAKDD Workshops Nguyen Thanh Binh, Vu Nguyen, Svetha Venkatesh, Dinh Q. Phung
2016	B	`conf`	Learning Multifaceted Latent Activities from Heterogeneous Mobile Data. DSAA Nguyen Thanh Binh, Vu Nguyen, Nguyen Cong Thuong, Svetha Venkatesh, Mohan Kumar, Dinh Q. Phung
2016	B	`conf`	MCNC: Multi-Channel Nonparametric Clustering from heterogeneous data. ICPR Nguyen Thanh Binh, Vu Nguyen, Svetha Venkatesh, Dinh Q. Phung
2016	C	`conf`	Multiple Kernel Learning with Data Augmentation. ACML Khanh Nguyen, Trung Le, Vu Nguyen, Tu Dinh Nguyen, Dinh Q. Phung
2016	B	`conf`	Multiple adverse effects prediction in longitudinal cancer treatment. ICPR Cheng Li, Sunil Gupta, Santu Rana, Vu Nguyen, Svetha Venkatesh, David Ashely, Trish Livingston
2016	A	`conf`	Nonparametric Budgeted Stochastic Gradient Descent. AISTATS Trung Le, Vu Nguyen, Tu Dinh Nguyen, Dinh Q. Phung
2016	A*	`conf`	One-Pass Logistic Regression for Label-Drift and Large-Scale Classification on Distributed Systems. ICDM Vu Nguyen, Tu Dinh Nguyen, Trung Le, Svetha Venkatesh, Dinh Q. Phung
2016	A*	`conf`	SECC: Simultaneous extraction of context and community from pervasive signals. PerCom Nguyen Cong Thuong, Vu Nguyen, Flora D. Salim, Dinh Q. Phung
2016	J	`jnl`	Scalable Support Vector Machine for Semi-supervised Learning. CoRR Trung Le, Khanh Nguyen, Van Nguyen, Vu Nguyen, Dinh Q. Phung
2016	—	`conf`	Sparse Adaptive Multi-hyperplane Machine. PAKDD (1) Khanh Nguyen, Trung Le, Vu Nguyen, Dinh Q. Phung
2015	—	`conf`	A Bayesian Nonparametric Approach to Multilevel Regression. PAKDD (1) Vu Nguyen, Dinh Q. Phung, Svetha Venkatesh, Hung Hai Bui
2014	J	`jnl`	Bayesian Nonparametric Multilevel Clustering with Group-Level Contexts. CoRR Vu Nguyen, Dinh Q. Phung, XuanLong Nguyen, Svetha Venkatesh, Hung Hai Bui