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RISOn non strictly convexity of norm in Banach spaces
In this paper, a non-strictly convex norm is exhibited. More precisely, we will show that X/c0 is not strictly convexifiable, where X is subspace of l$^\\\\infty$....
q-norms are really norms
ABSTRACT. Replacing the triangle inequality, in the definition of a norm, by kx + yk
q
≤
2q−1 (kxk
q
+ kyk
q
), we introduce the notion of a q-norm. We establish that every ...
A lasso for hierarchical interactions
Counterexamples to convexity of k-intersection bodies
A joint convex penalty for inverse covariance matrix estimation
A VIF based optimization model to alleviate collinearity problems in multiple linear regression
A determinantal inequality for correlation matrices
Solving a Class of Separated Continuous Programming Problems Using Linearization and Discretization
In this paper we present a new approach for solving a class of separated
continuous programming (SCP) problems using convex combination property of intervals. By
convex combination property of intervals, we transform the SCP problems...
Operator maps of Jensen-type
operators C, D acting on H with C∗C+D∗D=I, where I denotes the identity operator. We show that a Jensen-type map on an infinite dimensional Hilbert space is of the form Φ(A)=f(A) for some operator convex function f defined in J....
A new nonlinear neural network for solving a class of constrained parametric optimization problems
The paper deals with convex parametric programming problems. In this paper convex parametric programming transform to a neural network model and then we solve neural network model with one of numerical methods. Finally, simple numerical examples...