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Journal of Machine Learning Research, ISSN 1532-4435, 2013, Volume 30, pp. 3 - 24
Journal Article
SIAM journal on optimization, ISSN 1095-7189, 2012, Volume 22, Issue 2, pp. 341 - 362
In this paper we propose new methods for solving huge-scale optimization problems. For problems of this size, even the simplest full-dimensional vector... 
Google problem | Fast gradient schemes | Convex optimization | Coordinate relaxation | Worst-case efficiency estimates | MATHEMATICS, APPLIED | worst-case efficiency estimates | MINIMIZATION | fast gradient schemes | convex optimization | CONVERGENCE | coordinate relaxation
Journal Article
Journal of Machine Learning Research, ISSN 1532-4435, 04/2016, Volume 17
CVXPY is a domain-specific language for convex optimization embedded in Python. It allows the user to express convex optimization problems in a natural syntax... 
Convexity verification | Domain-specific languages | Convex optimization | Conic programming | Python | domain-specific languages | convexity verification | conic programming | convex optimization | AUTOMATION & CONTROL SYSTEMS | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Journal Article
IEEE Transactions on Signal Processing, ISSN 1053-587X, 05/2017, Volume 65, Issue 9, pp. 2363 - 2378
This paper considers the jointly optimal pilot and data power allocation in single-cell uplink massive multiple-input-multiple-output systems. Using the... 
Power control | Channel estimation | Interference | Massive MIMO | power allocation | convex optimization | MIMO | Uplink | Payloads | Signal to noise ratio | power control | OPTIMIZATION | ALLOCATION | ENGINEERING, ELECTRICAL & ELECTRONIC | Mathematical optimization | Usage | MIMO communications
Journal Article
Journal of Machine Learning Research, ISSN 1532-4435, 01/2009, Volume 10, pp. 207 - 244
Journal Article
2010, ISBN 9780521762229, Volume 9780521762229, xiv, 498
Over the past two decades there have been significant advances in the field of optimization. In particular, convex optimization has emerged as a powerful... 
Signal processing | Mathematical optimization | Convex functions
Book
IEEE Transactions on Signal Processing, ISSN 1053-587X, 03/2014, Volume 62, Issue 5, pp. 1078 - 1092
Journal Article
Journal Article
Journal of Machine Learning Research, ISSN 1532-4435, 08/2010, Volume 11, pp. 2287 - 2322
We use convex relaxation techniques to provide a sequence of regularized low-rank solutions for large-scale matrix completion problems. Using the nuclear norm... 
Large scale convex optimization | Netflix prize | Nuclear norm | Collaborative filtering | Spectral regularization | collaborative filtering | large scale convex optimization | spectral regularization | netflix prize | nuclear norm | SELECTION | AUTOMATION & CONTROL SYSTEMS | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Journal Article
International Journal of Control, ISSN 0020-7179, 03/2020, Volume 93, Issue 3, pp. 575 - 587
This paper fully studies distributed optimal consensus problem in undirected dynamical networks. We consider a group of networked agents that are supposed to... 
Networked systems | consensus | convex optimisation | interior-point method | DISTRIBUTED CONVEX-OPTIMIZATION | TRACKING | NETWORKS | AGENTS | ALGORITHMS | AUTOMATION & CONTROL SYSTEMS | Multiagent systems | Algorithms | Constraints | Double integrators | Stability analysis | Control stability | Rendezvous | Nonlinear programming | Optimization
Journal Article
SIAM journal on optimization, ISSN 1095-7189, 2017, Volume 27, Issue 3, pp. 1283 - 1313
Journal Article
Journal of analytical atomic spectrometry, ISSN 0267-9477, 2017, Volume 32, Issue 11, pp. 2164 - 2172
In quantitative laser-induced breakdown spectroscopy (LIBS) analysis, spectral signals are usually represented by the linear combination of characteristic... 
Journal Article
Journal of Machine Learning Research, ISSN 1532-4435, 10/2011, Volume 12, pp. 2777 - 2824
We consider the empirical risk minimization problem for linear supervised learning, with regularization by structured sparsity-inducing norms. These are... 
Sparsity | Convex optimization | Active set algorithm | Consistency | Variable selection | RECOVERY | active set algorithm | MODEL SELECTION | GROUP LASSO | convex optimization | sparsity | variable selection | consistency | SOFTWARE | AUTOMATION & CONTROL SYSTEMS | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Statistics | Machine Learning
Journal Article
ISPRS Journal of Photogrammetry and Remote Sensing, ISSN 0924-2716, 07/2018, Volume 141, pp. 46 - 58
Sparse unmixing aims at recovering pure materials from hyperpspectral images and estimating their abundance fractions. Sparse unmixing is actually ℓ0 problem... 
Sparse unmixing | Non-convex optimization | Multi-objective | Hyperspectral image
Journal Article
IEEE Transactions on Signal Processing, ISSN 1053-587X, 06/2017, Volume 65, Issue 12, pp. 3062 - 3077
Journal Article
SIAM journal on optimization, ISSN 1052-6234, 2012, Volume 22, Issue 4, pp. 1469 - 1492
In this paper we present a generic algorithmic framework, namely, the accelerated stochastic approximation (AC-SA) algorithm, for solving strongly convex... 
Stochastic approximation | Convex optimization | Complexity | Large deviation | Stochastic programming | MATHEMATICS, APPLIED | convex optimization | stochastic approximation | stochastic programming | complexity large deviation
Journal Article
Journal of Machine Learning Research, ISSN 1532-4435, 03/2008, Volume 9, pp. 485 - 516
We consider the problem of estimating the parameters of a Gaussian or binary distribution in such a way that the resulting undirected graphical model is... 
Binary data | Maximum likelihood estimation | Gaussian graphical model | Convex optimization | Model selection | binary data | MINIMIZATION | LASSO | model selection | convex optimization | maximum likelihood estimation | AUTOMATION & CONTROL SYSTEMS | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | GRAPHS
Journal Article
Automatica, ISSN 0005-1098, 2012, Volume 48, Issue 1, pp. 56 - 67
Journal Article
IEEE Journal on Selected Topics in Signal Processing, ISSN 1932-4553, 12/2007, Volume 1, Issue 4, pp. 606 - 617
Recently, a lot of attention has been paid to regularization based methods for sparse signal reconstruction (e.g., basis pursuit denoising and compressed... 
Convex optimization | regularization | Basis pursuit denoising | Least squares | Preconditioned conjugate gradients | Interior-point methods | Compressive sampling | Compressed sensing | Studies | Methods | Algorithms
Journal Article
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