A new algorithm, Neighborhood MinMax Projections (NMMP), is proposed for supervised dimensionality reduction in this paper. The algorithm aims at learning a linear transformation, and focuses only on the pairwise points where the two points are neighbors of each other. After the transformation, the considered pairwise points within the same class are as close as possible, while those between di...

We present an algorithm to compute the set of perfect public equilibrium payoffs as the discount factor tends to one for stochastic games with observable states and public (but not necessarily perfect) monitoring when the limiting set of (long-run players’) equilibrium payoffs is independent of the state. This is the case, for instance, if the Markov chain induced by any Markov strategy profile...

This note studies the relationship between a player’s (stage game) minmax payoff and the (lowest) individually rational payoff in repeated games with imperfect monitoring. We characterize the signal structures under which these two payoffs coincide for any payoff matrix. Under an identifiability assumption, we further show that, if the monitoring structure of an infinitely repeated game ‘nearly...

In this paper we analyze the application of the Ant Colony Optimization to the Minimum Weight Vertex Covering Problem. We use the software system that we developed and implemented different standard ACO algorithms to this problem: Ant Colony System, the use of Elitism, Rank based approach and the MinMax system. We have made a comparative assessment of the effectiveness of these algorithms to th...

In this paper we consider the problem of computing an optimum set of watchmen routes in a histogram. A watchman, in the terminology of art galleries, is a mobile guard and in this version we want to minimize the length of the longest route in the solution. We give an O(n 2 log n) time algorithm to compute the MinMax optimum set of m watchmen in a histogram polygon and we extend the algorithm to...

Score normalization and results merging are important components of many IR applications. Recently MinMax—an unsupervised linear score normalization method—was shown to perform quite well across various distributed retrieval testbeds, although based on strong assumptions. The CORI results merging method relaxes these assumptions to some extent and significantly improves the performance of MinMa...

in this work we deal with the coefficients of a (e it ) 2 , where a is in a class of polynomialshaving unimodular coefficients. we first present a technique that calculates lower bounds for particularautocorrelations and then in a more general case we present an upper bound for their maximal order.

This paper focuses on the practice of serial correlation correcting of the Linear Regression Model (LRM) by modeling the error. Simple Monte Carlo experiments are used to demonstrate the following points regarding this practice. First, the common factor restrictions implicitly imposed on the temporal structure of yt and xt appear to be completely unreasonable for any real world application. Sec...