In this paper we propose a methodology for estimating preference parameters in matching models. Our estimator applies to repeated observations of matchings among a fixed group of individuals, which is a similar data structure as in Fox (2010). Our estimator is based on stability conditions in the matching models; we consider both transferable (TU) and non-transferable utility (NTU) models. In b...

In this paper we propose a methodology for estimating preference parameters in matching models. Our estimator applies to repeated observations of matchings among a fixed group of individuals, which is a similar data structure as in Fox (2010). Our estimator is based on stability conditions in the matching models; we consider both transferable (TU) and non-transferable utility (NTU) models. In b...

A crucial issue for addressing decision-making problems under uncertainty is the approximate representation of multivariate stochastic processes in the form of scenario tree. This paper proposes a scenario generation approach based on the idea of integrating simulation and optimization techniques. In particular, simulation is used to generate outcomes associated with the nodes of the scenario t...

We address the problem of learning the parameters in graphical models when inference is intractable. A common strategy in this case is to replace the partition function with its Bethe approximation. We show that there exists a regime of empirical marginals where such Bethe learning will fail. By failure we mean that the empirical marginals cannot be recovered from the approximated maximum likel...

Markov Decision Process Tayloring for Approximation Design Optimal control problems are difficult to solve on large state spaces, calling the development of approximate solution methods. In “A Low-rank MDPs via Moment Coupling,” Zhang and Gurvich introduce a novel framework decision processes (MDPs) that stands two pillars: (i) aggregation, as algorithmic infrastructure, (ii) central-limit-theo...

In this paper, we study matching integral graphs of small order. A graph is called matching integral if the zeros of its matching polynomial are all integers. Matching integral graphs were first studied by Akbari, Khalashi, etc. They characterized all traceable graphs which are matching integral. They studied matching integral regular graphs. Furthermore, it has been shown that there is no matc...

schema matching is a critical step in many applications, such as data warehouse loading, online analytical process (olap), data mining, semantic web [2] and schema integration. this task is defined for finding the semantic correspondences between elements of two schemas. recently, schema matching has found considerable interest in both research and practice. in this paper, we present a new impr...

A FETI-DP formulation for three dimensional elasticity problems on non-matching grids is considered. To resolve the nonconformity of the finite elements, a mortar matching condition is imposed on subdomain interfaces. The mortar matching condition are considered as weak continuity constraints in the FETIDP formulation. A relatively large set of primal constraints, which include average and mome...

This paper characterizes the testable implications of stability for aggregate matchings. We consider data on matchings where individuals are aggregated, based on their observable characteristics, into types, and we know how many agents of each type match. We derive stability conditions for an aggregate matching, and, based on these, provide a simple necessary and sufficient condition for an obs...

-A novel approach of image matching for rotating transformation is presented and studied. The approach is inspired by electromagnetic interaction force between physical currents. The virtual current in images is proposed based on the significant edge lines extracted as the fundamental structural feature of images. The virtual electromagnetic force and the corresponding moment is studied between...