How Quasiconvexity works part8(Machine Learning)

We establish that for any non-empty, compact set K⊂R3×3sym the 1- and ∞-symmetric div-quasiconvex hulls K(1) and K(∞) coincide. This settles a conjecture in a recent work of Conti, Müller and Ortiz (Symmetric Div-Quasiconvexity and the Relaxation of Static Problems. Arch. Ration. Mech. Anal. 235(2):841–880) in the affirmative. As a key novelty, we construct an L∞-truncation that preserves both symmetry and solenoidality of matrix-valued maps in L 2.Dual representations of quasiconvex compositions with applications to systemic risk (arXiv) Author : <a href="https://arxiv.org/search/?searchtype=author&query=Ararat%2C+%C3%87" rel="noopener ugc nofollow" target="_blank">Çağın Ararat</a>, <a href="https://arxiv.org/search/?searchtype=author&query=Ayg%C3%BCn%2C+M" rel="noopener ugc nofollow" target="_blank">Mücahit Aygün</a> Abstract : Motivated by the problem of finding dual representations for quasiconvex systemic risk measures in financial mathematics, we study quasiconvex compositions in an abstract infinite-dimensional setting. We calculate an explicit formula for the penalty function of the composition in terms of the penalty functions of the ingredient functions. The proof makes use of a nonstandard minimax inequality (rather than equality as in the standard case) that is available in the literature. In the second part of the paper, we apply our results in concrete probabilistic settings for systemic risk measures, in particular, in the context of Eisenberg-Noe clearing model. We also provide novel economic interpretations of the dual representations in these settings. <a href="https://medium.com/@monocosmo77/how-quasiconvexity-works-part8-machine-learning-b2ca715df2dc">Website</a>