Examples of 'convex optimization' in a sentence
Meaning of "convex optimization"
convex optimization: a mathematical optimization technique used to minimize convex functions over convex sets
How to use "convex optimization" in a sentence
Basic
Advanced
convex optimization
Linear programming belongs to the theory of convex optimization.
A hierarchy of convex optimization problems.
We study three simple subgradient algorithms for nonsmooth convex optimization.
The second one concerns some non convex optimization problem in portfolio selection.
The special class of concave fractional programs can be transformed to a convex optimization problem.
The third part contains some non convex optimization problems in production management.
The problem of scoring function reconstruction is formulated and solved as a convex optimization problem.
The approximations are found through a convex optimization process simplified by the kernel trick.
The following resources contain additional information on Convex Optimization.
A major breakthrough in convex optimization lies in the introduction of interior-point methods.
It can also be used to produce time averaged solutions to convex optimization problems.
Most kernel algorithms are based on convex optimization or eigenproblems and are statistically well-founded.
Lipschitz-type properties in linear and convex optimization.
For convex optimization problems, the duality gap is zero under a constraint qualification condition.
This can be done by convex optimization.
See also
Among the major contribution areas are discrete optimization, integer programming and convex optimization.
Semidefinite programming ( SDP ) is a subfield of convex optimization where the underlying variables are semidefinite matrices.
However, this penalty corresponds to a non differentiable and non - convex optimization problem.
Convex Optimization, this sub-theme covers both fundamental, geometrica and algorothmic aspects around convexity.
Training the classifier may include formulating a training problem as a convex optimization problem dual training algorithm.
Convex optimization problems can be solved by the following contemporary methods, [ 16 ].
The composition of each sub-clip is automatically computed in a novel convex optimization framework.
In this thesis, we address two different problems within the framework of convex optimization.
Proximal gradient methods are a generalized form of projection used to solve non-differentiable convex optimization problems.
B-determination of a control law by LMI convex optimization.
To establish whether a form h ( x ) is SOS amounts to solving a convex optimization problem.
CVXPY is an open source Python-embedded modeling language for convex optimization problems.
You'll also be interested in:
Examples of using Optimization
Show more
As a tool for optimization of the supply chain
Optimization and standardization of nucleic acid extractions
Active routes for the optimization of resources
Examples of using Convex
Show more
Shoulder extremely convex and extremely thick
Convex geometry is a relatively young mathematical discipline
Shoulder very convex and very thick
