Vu C. Dinh

According to our database, Vu C. Dinh authored at least 18 papers between 2012 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Simple Transferability Estimation for Regression Tasks.

Cuong N. Nguyen, Phong Tran, Lam Si Tung Ho, Vu C. Dinh, Anh T. Tran, Tal Hassner, Cuong V. Nguyen

Proceedings of the Uncertainty in Artificial Intelligence, 2023

2022

Bayesian active learning with abstention feedbacks.

Cuong V. Nguyen, Lam Si Tung Ho, Huan Xu, Vu C. Dinh, Binh T. Nguyen

Neurocomputing, 2022

Generalization Bounds for Deep Transfer Learning Using Majority Predictor Accuracy.

Cuong N. Nguyen, Lam Si Tung Ho, Vu C. Dinh, Tal Hassner, Cuong V. Nguyen

Proceedings of the International Symposium on Information Theory and Its Applications, 2022

2021

Posterior concentration and fast convergence rates for generalized Bayesian learning.

Lam Si Tung Ho, Binh T. Nguyen, Vu C. Dinh, Duy Nguyen

CoRR, 2021

Searching for Minimal Optimal Neural Networks.

Lam Si Tung Ho, Vu C. Dinh

CoRR, 2021

OASIS: An Active Framework for Set Inversion.

Binh T. Nguyen, Duy M. Nguyen, Lam Si Tung Ho, Vu C. Dinh

CoRR, 2021

2020

Posterior concentration and fast convergence rates for generalized Bayesian learning.

Lam Si Tung Ho, Binh T. Nguyen, Vu C. Dinh, Duy M. H. Nguyen

Inf. Sci., 2020

Consistent feature selection for neural networks via Adaptive Group Lasso.

Lam Si Tung Ho, Vu C. Dinh

CoRR, 2020

Consistent feature selection for analytic deep neural networks.

Vu C. Dinh, Lam Si Tung Ho

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

An active learning framework for set inversion.

Binh T. Nguyen, Duy M. H. Nguyen, Lam Si Tung Ho, Vu C. Dinh

Knowl. Based Syst., 2019

2018

OASIS: An Active Framework for Set Inversion.

Binh T. Nguyen, Duy M. H. Nguyen, Lam Si Tung Ho, Vu C. Dinh

Proceedings of the New Trends in Intelligent Software Methodologies, Tools and Techniques, 2018

2017

Support Vector Machine Informed Explicit Nonlinear Model Predictive Control Using Low-Discrepancy Sequences.

Ankush Chakrabarty, Vu C. Dinh, Martin J. Corless, Ann E. Rundell, Stanislaw H. Zak, Gregery T. Buzzard

IEEE Trans. Autom. Control., 2017

2016

Fast learning rates with heavy-tailed losses.

Vu C. Dinh, Lam Si Tung Ho, Binh T. Nguyen, Duy M. H. Nguyen

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015

Learning from Non-iid Data: Fast Rates for the One-vs-All Multiclass Plug-in Classifiers.

Vu C. Dinh, Lam Si Tung Ho, Viet Cuong Nguyen, Duy M. H. Nguyen, Binh T. Nguyen

Proceedings of the Theory and Applications of Models of Computation, 2015

2014

Robust explicit nonlinear model predictive control with integral sliding mode.

Ankush Chakrabarty, Vu C. Dinh, Gregery T. Buzzard, Stanislaw H. Zak, Ann E. Rundell

Proceedings of the American Control Conference, 2014

2013

Generalization and Robustness of Batched Weighted Average Algorithm with V-Geometrically Ergodic Markov Data.

Viet Cuong Nguyen, Lam Si Tung Ho, Vu C. Dinh

Proceedings of the Algorithmic Learning Theory - 24th International Conference, 2013

2012

Mel-frequency Cepstral Coefficients for Eye Movement Identification.

Viet Cuong Nguyen, Vu C. Dinh, Lam Si Tung Ho

Proceedings of the IEEE 24th International Conference on Tools with Artificial Intelligence, 2012

Systematically manipulating T-cell signaling dynamics via multiple model informed open-loop controller design.

Jeffrey P. Perley, Judith Mikolajczak, Vu C. Dinh, Marietta L. Harrison, Gregery T. Buzzard, Ann E. Rundell

Proceedings of the 51th IEEE Conference on Decision and Control, 2012