Vu Dinh
Cited by
Cited by
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
Consistent feature selection for analytic deep neural networks
VC Dinh, LS Ho
Advances in Neural Information Processing Systems 33, 2420-2431, 2020
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
Proceedings of the 34th International Conference on Machine Learning. Proceedings of Machine Learning Research
V Dinh, A Bilge, C Zhang, FA Matsen
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
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
Consistent feature selection for neural networks via Adaptive Group Lasso
V Dinh, LST Ho
arXiv preprint arXiv:2006.00334, 2020
Experimental design for dynamics identification of cellular processes
V Dinh, AE Rundell, GT Buzzard
Bulletin of mathematical biology 76, 597-626, 2014
Multi-task learning improves ancestral state reconstruction
LST Ho, V Dinh, CV Nguyen
Theoretical Population Biology 126, 33-39, 2019
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
The shape of the one-dimensional phylogenetic likelihood function
V Dinh, FA Matsen IV
The annals of applied probability: an official journal of the Institute of …, 2017
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
Searching for minimal optimal neural networks
LST Ho, V Dinh
Statistics & Probability Letters 183, 109353, 2022
Bayesian active learning with abstention feedbacks
CV Nguyen, LST Ho, H Xu, V Dinh, BT Nguyen
Neurocomputing 471, 242-250, 2022
The system can't perform the operation now. Try again later.
Articles 1–20