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Institution

HEC Paris

EducationJouy-en-Josas, France
About: HEC Paris is a education organization based out in Jouy-en-Josas, France. It is known for research contribution in the topics: Investment (macroeconomics) & Market liquidity. The organization has 584 authors who have published 2756 publications receiving 104467 citations. The organization is also known as: Ecole des Hautes Etudes Commerciales & HEC School of Management Paris.


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TL;DR: In this article, the authors studied the convergence and convergence rates of resampling schemes and showed that the convergence rate of a particle algorithm based on a stochastic rounding technique converges regardless of the order of the input samples.
Abstract: We study convergence and convergence rates for resampling schemes. Our first main result is a general consistency theorem based on the notion of negative association, which is applied to establish the almost-sure weak convergence of measures output from Kitagawa's (1996) stratified resampling method. Carpenter et al's (1999) systematic resampling method is similar in structure but can fail to converge depending on the order of the input samples. We introduce a new resampling algorithm based on a stochastic rounding technique of Srinivasan (2001), which shares some attractive properties of systematic resampling, but which exhibits negative association and therefore converges irrespective of the order of the input samples. We confirm a conjecture made by Kitagawa (1996) that ordering input samples by their states in $\mathbb{R}$ yields a faster rate of convergence; we establish that when particles are ordered using the Hilbert curve in $\mathbb{R}^d$, the variance of the resampling error is ${\scriptscriptstyle\mathcal{O}}(N^{-(1+1/d)})$ under mild conditions, where $N$ is the number of particles. We use these results to establish asymptotic properties of particle algorithms based on resampling schemes that differ from multinomial resampling.

36 citations

Journal ArticleDOI
TL;DR: The hypothesis is that name stereotypes can be manifested in facial appearance, producing a face-name matching effect, whereby both a social perceive and a computer are able to accurately match a person’s name to his or her face.
Abstract: Research demonstrates that facial appearance affects social perceptions. The current research investigates the reverse possibility: Can social perceptions influence facial appearance? We examine a social tag that is associated with us early in life-our given name. The hypothesis is that name stereotypes can be manifested in facial appearance, producing a face-name matching effect, whereby both a social perceiver and a computer are able to accurately match a person's name to his or her face. In 8 studies we demonstrate the existence of this effect, as participants examining an unfamiliar face accurately select the person's true name from a list of several names, significantly above chance level. We replicate the effect in 2 countries and find that it extends beyond the limits of socioeconomic cues. We also find the effect using a computer-based paradigm and 94,000 faces. In our exploration of the underlying mechanism, we show that existing name stereotypes produce the effect, as its occurrence is culture-dependent. A self-fulfilling prophecy seems to be at work, as initial evidence shows that facial appearance regions that are controlled by the individual (e.g., hairstyle) are sufficient to produce the effect, and socially using one's given name is necessary to generate the effect. Together, these studies suggest that facial appearance represents social expectations of how a person with a specific name should look. In this way a social tag may influence one's facial appearance. (PsycINFO Database Record

36 citations

BookDOI
16 Jun 2016

36 citations

Journal ArticleDOI
TL;DR: This article introduced a Language Complexity × Processing Mode Framework for classifying linguistic devices based on two continuous dimensions: language complexity, ranging from simple to complex, and processing mode, varying from automatic to controlled, and used the framework as a basis for reviewing and synthesizing extant research on the effects of linguistic devices on persuasion, determining the conditions under which the effectiveness of the linguistic devices can be maximized.

36 citations


Authors

Showing all 605 results

NameH-indexPapersCitations
Sandor Czellar133126391049
Jean-Yves Reginster110119558146
Pierre Hansen7857532505
Gilles Laurent7726427052
Olivier Bruyère7257924788
David Dubois5016912396
Rodolphe Durand4917310075
Itzhak Gilboa4925913352
Yves Dallery471706373
Duc Khuong Nguyen472358639
Eric Jondeau451557088
Jean-Noël Kapferer4515112264
David Thesmar411617242
Bruno Biais411448936
Barbara B. Stern40896001
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20239
202233
2021129
2020141
2019110
2018136