Results 51 to 60 of about 174 (149)

Performance Bounds For Co-/Sparse Box Constrained Signal Recovery

Analele Stiintifice ale Universitatii Ovidius Constanta: Seria Matematica, 2019
The recovery of structured signals from a few linear measurements is a central point in both compressed sensing (CS) and discrete tomography. In CS the signal structure is described by means of a low complexity model e.g. co-/sparsity.
Kuske Jan, Petra Stefania
doaj   +1 more source

Alternating direction method for bi-quadratic programming

Alternating direction method, Bi-quadratic programming, Quadratic semidefinite programming, 65F15, 65K05, 90C90,
Sheng-Long Hu, Zheng-Hai Huang
core   +1 more source

Eliciting vague but proper maximal entropy priors in Bayesian experiments

Bayesian inference, Expert opinion, Kullback–Leibler distance, Shannon’s entropy, Noninformative priors, Channel coding, Sensitivity study, Weibull, 65K05, 90C35,
Nicolas Bousquet
core   +1 more source

A constrained-optimization based half-quadratic algorithm for robustly fitting sets of linearly parametrized curves

Non-convex problem, Constrained optimisation, Primal and dual problem, Robust estimators, Image analysis, 62J05, 90C26, 90C55, 90C90, 49M29, 65K05, 62H12, 62H35,
Jean-Philippe Tarel, Pierre Charbonnier, Sio-Song Ieng   +2 more
core   +1 more source

Sensor Location Problem for a Multigraph [PDF]

, 2013
MSC 2010: 05C50, 15A03, 15A06, 65K05, 90C08, 90C35We introduce sparse linear underdetermined systems with embedded network structure. Their structure is inherited from the non-homogeneous network ow programming problems with nodes of variable intensities.
Vishnevetskaya, T. S., Pesheva, Y. H., Pilipchuk, L. A.   +2 more
core  

A novel four-term conjugate gradient method for large-scale optimization problems involving formulation and application

Franklin Open
The conjugate gradient (CG) method is widely employed for solving unconstrained optimization problems due to its independence from second derivatives or their approximations. It has found extensive applications in fields such as image restoration, neural
Ahmad Alhawarat, Sulaiman M. Ibrahim, Abdullah S. Al-Jawarneh, Mohammad N Al Smadi, Shahrina Ismail   +4 more
doaj   +1 more source

$${{\mathcal {D}(\mathcal {C})}}$$ -optimization and robust global optimization

Nonconvex global optimization, Approximate optimal solution, Robust approach, Essential optimal solution, dc optimization, dm (monotonic) optimization, $${{\mathcal {D}(\mathcal {C})}}$$ -optimization, Successive Incumbent Transcending Algorithm, 90C26 ...
Hoang Tuy
core   +1 more source

A fast continuous time approach with time scaling for nonsmooth convex optimization. [PDF]

Adv Contin Discret Model, 2022
Boţ RI, Karapetyants MA.
europepmc   +1 more source

LIGHTENINGS OF ASSUMPTIONS FOR PONTRYAGIN PRINCIPLES IN INFINITE HORIZON AND DISCRETE TIME

, 2016
In the infinite-horizon and discrete-time framework we establish maximum principles of Pontryagin under assumptions which weaker than these ones of existing results.
Ngo, Thoi-Nhan, Blot, Joël
core  

Fast Augmented Lagrangian Method in the convex regime with convergence guarantees for the iterates. [PDF]

Math Program, 2023
Boţ RI, Csetnek ER, Nguyen DK.
europepmc   +1 more source