| Extragradient algorithms extended to equilibrium problems¶ DQ Tran, M Le Dung, Van Hien Nguyen Optimization 57 (6), 749-776, 2008 | 189 | 2008 |
| Learning with tensors: a framework based on convex optimization and spectral regularization M Signoretto, QT Dinh, L De Lathauwer, JAK Suykens Machine Learning 94 (3), 303-351, 2014 | 181 | 2014 |
| Combining convex–concave decompositions and linearization approaches for solving BMIs, with application to static output feedback QT Dinh, S Gumussoy, W Michiels, M Diehl IEEE Transactions on Automatic Control 57 (6), 1377-1390, 2011 | 131 | 2011 |
| WASP: Scalable Bayes via barycenters of subset posteriors S Srivastava, V Cevher, Q Dinh, D Dunson Artificial Intelligence and Statistics, 912-920, 2015 | 83 | 2015 |
| Composite self-concordant minimization Q Tran Dinh, A Kyrillidis, V Cevher Journal of Machine Learning Research 16 (ARTICLE), 371-416, 2015 | 72 | 2015 |
| Dual extragradient algorithms extended to equilibrium problems TD Quoc, PN Anh, LD Muu Journal of Global Optimization 52 (1), 139-159, 2012 | 68 | 2012 |
| Computational complexity of inexact gradient augmented Lagrangian methods: application to constrained MPC V Nedelcu, I Necoara, Q Tran-Dinh SIAM Journal on Control and Optimization 52 (5), 3109-3134, 2014 | 66 | 2014 |
| Local convergence of sequential convex programming for nonconvex optimization QT Dinh, M Diehl Recent Advances in Optimization and its Applications in Engineering, 93-102, 2010 | 66 | 2010 |
| Regularization algorithms for solving monotone Ky Fan inequalities with application to a Nash-Cournot equilibrium model LD Muu, TD Quoc Journal of optimization theory and applications 142 (1), 185-204, 2009 | 65 | 2009 |
| Time-optimal path following for robots with convex–concave constraints using sequential convex programming F Debrouwere, W Van Loock, G Pipeleers, QT Dinh, M Diehl, ... IEEE Transactions on Robotics 29 (6), 1485-1495, 2013 | 54 | 2013 |
| Adjoint-based predictor-corrector sequential convex programming for parametric nonlinear optimization QT Dinh, C Savorgnan, M Diehl SIAM Journal on Optimization 22 (4), 1258-1284, 2012 | 50 | 2012 |
| A universal primal-dual convex optimization framework A Yurtsever, QT Dinh, V Cevher Advances in Neural Information Processing Systems, 3150-3158, 2015 | 45 | 2015 |
| Convexity in source separation: Models, geometry, and algorithms MB McCoy, V Cevher, QT Dinh, A Asaei, L Baldassarre IEEE Signal Processing Magazine 31 (3), 87-95, 2014 | 44 | 2014 |
| A Smooth Primal-Dual Optimization Framework for Nonsmooth Composite Convex Minimization Q Tran-Dinh, O Fercoq, V Cevher arXiv preprint arXiv:1507.06243, 2015 | 41 | 2015 |
| An inexact perturbed path-following method for Lagrangian decomposition in large-scale separable convex optimization QT Dinh, I Necoara, C Savorgnan, M Diehl SIAM Journal on Optimization 23 (1), 95-125, 2013 | 40 | 2013 |
| Combining Lagrangian decomposition and excessive gap smoothing technique for solving large-scale separable convex optimization problems QT Dinh, C Savorgnan, M Diehl Computational Optimization and Applications 55 (1), 75-111, 2013 | 37 | 2013 |
| Sequential convex programming methods for solving nonlinear optimization problems with DC constraints TD Quoc, M Diehl arXiv preprint arXiv:1107.5841, 2011 | 36 | 2011 |
| Distributed nonlinear optimal control using sequential convex programming and smoothing techniques I Necoara, C Savorgnan, DQ Tran, J Suykens, M Diehl Decision and Control, 2009 held jointly with the 2009 28th Chinese Control …, 2009 | 32 | 2009 |
| A primal-dual algorithmic framework for constrained convex minimization Q Tran-Dinh, V Cevher arXiv preprint arXiv:1406.5403, 2014 | 31 | 2014 |
| A proximal Newton framework for composite minimization: Graph learning without Cholesky decompositions and matrix inversions QT Dinh, A Kyrillidis, V Cevher International Conference on Machine Learning, 271-279, 2013 | 26 | 2013 |
Moritz DiehlProfessor of Systems, Control and Optimization at the University of FreiburgVerified email at imtek.uni-freiburg.de
