Relational Data Mining Through Extraction of Representative Exemplars

With the growing interest on Network Analysis, Relational Data Mining is becoming an emphasized domain of Data Mining. This paper addresses the problem of extracting representative elements from a relational dataset. After defining the notion of degree of representativeness, computed using the Borda aggregation procedure, we present the extraction of exemplars which are the representative elements of the dataset. We use these concepts to build a network on the dataset. We expose the main properties of these notions and we propose two typical applications of our framework. The first application consists in resuming and structuring a set of binary images and the second in mining co-authoring relation in a research team

Financial development, international trade and welfare.

Differences between domestic financial systems can lead to international trade. A country with relatively developed or decentralized financial systems will export innovative commodities while a country with less developed and centralized financial systems will export traditional commodities. Trade is always welfare improving before the resolution of uncertainty but the country with the more risk averse financial system and the world as a whole can be worse off with trade after the resolution of uncertainty. A temporary protection can be welfare improving for such risk averse countries which are often the less developed ones.Free trade commitment; Financial systems; Idiosyncratic risk; Risk aversion; Trade losses;

Optimism, pessimism, and the gains from trade.

This paper examines the debate over the gains from trade when international differences in the risk perception of heterogeneous managers provide the basis for trade: the relatively optimistic country exports the risky commodity whereas the relatively pessimistic country exports the certain commodity. We show that optimal trade policy depends on the choice of the welfare criterion, as ex-ante and ex-post criteria often lead to opposing conclusions. The more optimistic country is always better off ex-ante whereas it can end up worse off ex-post. The more pessimistic country may be worse off/better off ex-ante but better off/worse off according to the ex-post welfare criterion.Heterogeneity; Trade losses; Ex-ante and ex-post welfare; Idiosyncratic risk; Optimism; Pessimism;

Psychological trade.

Idiosyncratic risk; Free trade commitment; Trade losses; Financial systems; Risk aversion;

The welfare effects of international trade with optimistic and pessimistic managers.

This paper investigates the welfare effects of international trade when technological idiosyncratic risk is distorted by optimistic and pessimistic managers. We show that free trade always improves the ex-ante welfare but sometimes lowers the ex-post welfare. Free trade commitment can be regretted ex-post.Optimism; Free trade commitment; Trade losses; Idiosyncratic risk;

Rates of convergence for robust geometric inference

Distances to compact sets are widely used in the field of Topological Data Analysis for inferring geometric and topological features from point clouds. In this context, the distance to a probability measure (DTM) has been introduced by Chazal et al. (2011) as a robust alternative to the distance a compact set. In practice, the DTM can be estimated by its empirical counterpart, that is the distance to the empirical measure (DTEM). In this paper we give a tight control of the deviation of the DTEM. Our analysis relies on a local analysis of empirical processes. In particular, we show that the rates of convergence of the DTEM directly depends on the regularity at zero of a particular quantile fonction which contains some local information about the geometry of the support. This quantile function is the relevant quantity to describe precisely how difficult is a geometric inference problem. Several numerical experiments illustrate the convergence of the DTEM and also confirm that our bounds are tight

Modelling aeronautical composite laminates behaviour under impact using a saturation damage and delamination continuous material model

We show that the behavior of T700/M21s and T800/M21s composite panels are affected by the influence of strain rates together with local shear and crush punch or global flexural strengths of the structure. A deterministic continuous composite material model has been developed as a LS-DYNA user defined material model for unidirectional composites on the basis of the Matzenmiller model widely used for woven composites. Initiation and evolution up to saturation and fracture are implemented for various and coupled damage mechanisms including delamination. Quasi-static and dynamic characterization tests laminates have been carried out on balanced angle ply [±θ] and used for calibration of numerical values. Impact induced damage from experiment's measures and numerical predictions are compared for T800/M21S aeronautical samples impacted at 15J

"Intelligent" controllers on cheap and small programmable devices

It is shown that the "intelligent" controllers which are associated to the recently introduced model-free control synthesis may be easily implemented on cheap and small programmable devices. Several successful numerical experiments are presented with a special emphasis on fault tolerant control

Data driven estimation of Laplace-Beltrami operator

Approximations of Laplace-Beltrami operators on manifolds through graph Lapla-cians have become popular tools in data analysis and machine learning. These discretized operators usually depend on bandwidth parameters whose tuning remains a theoretical and practical problem. In this paper, we address this problem for the unnormalized graph Laplacian by establishing an oracle inequality that opens the door to a well-founded data-driven procedure for the bandwidth selection. Our approach relies on recent results by Lacour and Massart [LM15] on the so-called Lepski's method