Voting Operators in the Space of Choice Functions

Assuming the individual and collective opinions are given as choice functions, a new formalization of the voting problem is considered. The notions of a local functional operator and the closedness of domains in choice-functional space relative to local operators are introduced. The problem of voting is reduced to an analysis of three kinds of operator classes and their mutual relations. The functional analogues well known in the theory of Arrow's paradox results are established

Lexicographic choice functions without archimedeanicity

We investigate the connection between choice functions and lexicographic probabilities, by means of the convexity axiom considered by Seidenfeld, Schervisch and Kadane (2010) but without imposing any Archimedean condition. We show that lexicographic probabilities are related to a particular type of sets of desirable gambles, and investigate the properties of the coherent choice function this induces via maximality. Finally, we show that the convexity axiom is necessary but not sufficient for a coherent choice function to be the infimum of a class of lexicographic ones

Real-time human action recognition on an embedded, reconfigurable video processing architecture

Copyright @ 2008 Springer-Verlag.In recent years, automatic human motion recognition has been widely researched within the computer vision and image processing communities. Here we propose a real-time embedded vision solution for human motion recognition implemented on a ubiquitous device. There are three main contributions in this paper. Firstly, we have developed a fast human motion recognition system with simple motion features and a linear Support Vector Machine (SVM) classifier. The method has been tested on a large, public human action dataset and achieved competitive performance for the temporal template (eg. “motion history image”) class of approaches. Secondly, we have developed a reconfigurable, FPGA based video processing architecture. One advantage of this architecture is that the system processing performance can be reconfiured for a particular application, with the addition of new or replicated processing cores. Finally, we have successfully implemented a human motion recognition system on this reconfigurable architecture. With a small number of human actions (hand gestures), this stand-alone system is performing reliably, with an 80% average recognition rate using limited training data. This type of system has applications in security systems, man-machine communications and intelligent environments.DTI and Broadcom Ltd

Voting Operators in the Space of Choice Functions

Assuming the individual and collective opinions are given as choice functions, a new formalization of the voting problem is considered. The notions of a local functional operator and the closedness of domains in choice-functional space relative to local operators are introduced. The problem of voting is reduced to an analysis of three kinds of operator classes and their mutual relations. The functional analogues well known in the theory of Arrow's paradox results are established

Theory, Politics... and History? Early post-war Soviet Control Engineering

A fascinating feature of post-war control engineering in the former Soviet Union was the rôle played by the study of the history of the discipline. Even before and during World War II some Soviet control scientists were actively researching the history of their subject; while after the war, historical studies played an important part both in technical developments and in legitimating a native Russian tradition. Two of the most important figures in this historical activity were A. A. Andronov and I. N. Voznesenskii, whose contributions are briefly considered

Natural extension of choice functions

International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU (17 th, 2018, Cádiz, Spain

Notes About Theory of Pseudo-Criteria and Binary Pseudo-Relations and Their Application to the Theory of Choice and Voting

The pages of this working paper are copies of transparencies used in a lecture on the general theory of choice given at the California Institute of Technology June 1991

Notes About Theory of Pseudo-Criteria and Binary Pseudo-Relations and Their Application to the Theory of Choice and Voting

The pages of this working paper are copies of transparencies used in a lecture on the general theory of choice given at the California Institute of Technology June 1991

Geometrical Insights for Implicit Generative Modeling

Learning algorithms for implicit generative models can optimize a variety of criteria that measure how the data distribution differs from the implicit model distribution, including the Wasserstein distance, the Energy distance, and the Maximum Mean Discrepancy criterion. A careful look at the geometries induced by these distances on the space of probability measures reveals interesting differences. In particular, we can establish surprising approximate global convergence guarantees for the $1$-Wasserstein distance,even when the parametric generator has a nonconvex parametrization.Comment: this version fixes a typo in a definitio