Vu Dinh
Cited by
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Support Vector Machine Informed Explicit Nonlinear Model Predictive Control Using Low-Discrepancy Sequences
A Chakrabarty, V Dinh, M Corless, AE Rundell, SH Zak, GT Buzzard
IEEE, 2016
Mel-frequency cepstral coefficients for eye movement identification
NV Cuong, V Dinh, LST Ho
2012 ieee 24th international conference on tools with artificial …, 2012
Probabilistic path hamiltonian monte carlo
V Dinh, A Bilge, C Zhang, FA Matsen IV
International Conference on Machine Learning, 1009-1018, 2017
Effective online Bayesian phylogenetics via sequential Monte Carlo with guided proposals
M Fourment, BC Claywell, V Dinh, C McCoy, FA Matsen IV, AE Darling
Systematic biology 67 (3), 490-502, 2018
Online Bayesian phylogenetic inference: theoretical foundations via sequential Monte Carlo
V Dinh, AE Darling, FA Matsen IV
Systematic biology 67 (3), 503-517, 2018
Binary complementary filters for compressive Raman spectroscopy
OG Rehrauer, VC Dinh, BR Mankani, GT Buzzard, BJ Lucier, ...
Applied spectroscopy 72 (1), 69-78, 2018
Robust explicit nonlinear model predictive control with integral sliding mode
A Chakrabarty, V Dinh, GT Buzzard, SH Żak, AE Rundell
2014 American Control Conference, 2851-2856, 2014
Learning from non-iid data: Fast rates for the one-vs-all multiclass plug-in classifiers
V Dinh, LST Ho, NV Cuong, D Nguyen, BT Nguyen
Theory and Applications of Models of Computation: 12th Annual Conference …, 2015
Fast learning rates with heavy-tailed losses
VC Dinh, LS Ho, B Nguyen, D Nguyen
Advances in neural information processing systems 29, 2016
Consistent feature selection for analytic deep neural networks
VC Dinh, LS Ho
Advances in Neural Information Processing Systems 33, 2420-2431, 2020
Generalization and robustness of batched weighted average algorithm with V-geometrically ergodic Markov data
NV Cuong, LST Ho, V Dinh
Algorithmic Learning Theory: 24th International Conference, ALT 2013 …, 2013
Experimental design for dynamics identification of cellular processes
V Dinh, AE Rundell, GT Buzzard
Bulletin of mathematical biology 76, 597-626, 2014
Consistency and convergence rate of phylogenetic inference via regularization
V Dinh, LST Ho, MA Suchard, FA Matsen IV
Annals of statistics 46 (4), 1481, 2018
Consistent feature selection for neural networks via Adaptive Group Lasso
V Dinh, LST Ho
arXiv preprint arXiv:2006.00334, 2020
Nonbifurcating Phylogenetic Tree Inference via the Adaptive LASSO
C Zhang, V Dinh, FA Matsen IV
Journal of the American Statistical Association 116 (534), 858-873, 2021
Multi-task learning improves ancestral state reconstruction
LST Ho, V Dinh, CV Nguyen
Theoretical Population Biology 126, 33-39, 2019
The shape of the one-dimensional phylogenetic likelihood function
V Dinh, FA Matsen IV
A machine learning approach to identifying important features for achieving step thresholds in individuals with chronic stroke
AE Miller, E Russell, DS Reisman, HE Kim, V Dinh
Plos one 17 (6), e0270105, 2022
Posterior concentration and fast convergence rates for generalized Bayesian learning
LST Ho, BT Nguyen, V Dinh, D Nguyen
Information Sciences 538, 372-383, 2020
An active learning framework for set inversion
BT Nguyen, DM Nguyen, LST Ho, V Dinh
Knowledge-Based Systems 185, 104917, 2019
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