Paris Dauphine University

About: Paris Dauphine University is a education organization based out in Paris, France. It is known for research contribution in the topics: Context (language use) & Population. The organization has 1766 authors who have published 6909 publications receiving 162747 citations. The organization is also known as: Paris Dauphine & Dauphine.

Gender diversity and board performance: women's experiences and perspectives

Abstract: Despite considerable progress that organizations have made during the past 20 years to increase the representation of women at board level, they still hold few board seats. Drawing on a qualitative study involving 30 companies with women directors in the United Kingdom, the United States, and Ghana, we investigate how the relationship between gender in the boardroom and corporate governance operates. The findings indicate that the presence of a minority of women on the board has an insignificant effect on board performance. Yet the chairperson's role is vital in leading the change for recruiting and evaluating candidates and their commitment to the board with diversity and governance in mind. Our study also sheds light on the multifaceted reasons why women directors appear to be resisting the discourse of gender quotas.

A review of Bandlet methods for geometrical image representation

Abstract: This article reviews bandlet approaches to geometric image representations. Orthogonal bandlets using an adaptive segmentation and a local geometric flow well suited to capture the anisotropic regularity of edge structures. They are constructed with a “bandletization” which is a local orthogonal transformation applied to wavelet coefficients. The approximation in these bandlet bases exhibits an asymptotically optimal decay for images that are regular outside a set of regular edges. These bandlets can be used to perform image compression and noise removal. More flexible orthogonal bandlets with less vanishing moments are constructed with orthogonal grouplets that group wavelet coefficients alon a multiscale association field. Applying a translation invariant grouplet transform over a translation invariant wavelet frame leads to state of the art results for image denoising and super-resolution.