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Consider a sensing system using a large number of N microphones placed in multiple dimensions to monitor a broadband acoustic field. Using all the microphones at once is impractical because of the amo...
In this paper, we study small perturbations of a class of non-convex integrable Hamiltonians with two degrees offreedom, and we prove a result of diffusion for an open and dense set of perturbations, ...
We introduce a new estimator for the vector of coefficients β in the linear model y = Xβ +z, where X has dimensions n × p with p possibly larger than n. SLOPE, short for Sorted L-One Penalized Estimat...
Closed characteristics on compact convex hypersurfaces in R8.
Lambert’s theorem, convex optimization, and minimizing solutions of the n-body problems.
Although many factors determine Google's overall ranking of search engine results, Google maintains that the heart of its search engine software is PageRank, the eigenvector corresponds to the maximal...
A real projective orbifold is an $n$-dimensional orbifold modeled on $RP^n$ with groups $\PGL(n+1, \bR)$. We concentrate on orbifolds with a compact codimension $0$ submanifold whose complement is a u...
The purpose of this note is to present an explicit iteration method that converges strongly for solving convex feasibility problems in Hilbert spaces.
The convex deficiency has been recently used to characterize the convex kernel of a set. This kind of result, central for Visibility Theory, suggests to study the convex deficiency in terms of some Vi...
This paper presents a new algorithm for minimizing a product of two positive convex functions. The given problem is firstly converted to an equivalent quasi-concave minimization problem in the outcom...
Making use of Linear operator theory, we define a new subclass of uniformly convex functions and a corresponding subclass of starlike functions with negative coefficients. The main object of this pape...
S-quasiconvex functions (Phu and An, Optimization, Vol. 38, 1996) are stable with respect to the properties: "every lower level set is convex", "each local minimizer is a global minimizer", and "each ...
The main result of this paper shows that -convex functions can be characterized in terms of a lower second-order generalized derivative.

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