Examples of 'convex function' in a sentence
Meaning of "convex function"
convex function: In mathematics, a convex function is a type of function where the line segment between any two points on the graph of the function lies above or on the graph itself
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- A mathematical function where the line segment between any two points on the graph of the function lies above the graph in a vector space of at least two dimensions.
How to use "convex function" in a sentence
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convex function
A function is concave if its negative is a convex function.
Any local minimum of a convex function is also a global minimum.
We establish a universal bound on the variations of bounded convex function.
There are placed solutions for convex function of initial conditions.
The technical term for this is that this is called a convex function.
Every convex function is quasiconvex.
Logarithmically convex function.
A strictly convex function will have at most one global minimum.
Concave function Is the negative of a convex function.
This is a convex function.
In mathematics, a concave function is the negative of a convex function.
Proper convex function.
Thus, the resulting relaxation is a convex function.
Strictly convex function.
The Phragmen-Lindelöf theorem implies that μ is a convex function.
See also
Quasi convex function.
However, a function whose sublevel sets are convex sets may fail to be a convex function.
The convex conjugate of a closed convex function is again a closed convex function.
We need to make P a positive semi-definite matrix in order to reformulate a convex function.
Where φ is a convex function and i denotes the position of the pixel in the image.
We say that f is a Convex Function if.
A proper convex function is closed if and only if it is lower semi-continuous.
In other words, revenue is a convex function of talent.
A strongly convex function is also strictly convex, but not vice versa.
A real-valued function is defined to be a convex function if its epigraph is a convex set.
A convex function of a martingale is a submartingale, by Jensen 's inequality.
Convex: traditional logistic regression is used; the objective is a convex function in the linear weights.
If a suitable strictly convex function is used, the problem will always have a unique solution.
A function f is log-convex iff log ( f ) is a convex function.
For any convex function f on Rn, one has.
Jensen 's inequality applies to every convex function f { \ displaystyle f.
If is a convex function defined on a real interval, then is Schur-convex.
So is a decreasing, convex function of.
A proper concave function is any function g such that f - g {\displaystyle f=-g} is a proper convex function.
For instance, a ( strictly ) convex function on an open set has no more than one minimum.
The sum of two convex functions ( for example, L2 loss + L1 regularization ) is a convex function.
Let f, I → R be a real-valued convex function defined on an open interval of the real line.
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Shoulder extremely convex and extremely thick
Convex geometry is a relatively young mathematical discipline
Shoulder very convex and very thick
