The paper describes the K-winner machine (KWM) model for classification. KWM training uses unsupervised vector quantization and subsequent calibration to label data-space partitions. A K-winner classifier seeks the largest set of best-matching prototypes agreeing on a test pattern, and provides a local-level measure of confidence. A theoretical analysis characterizes the growth function of a K-...

Abstract This study investigates the design of royalty rate in a first-price auction across three types investments: incremental and lumpy with or without an exogenously given intensity. A bidder’s investment cost comprises private information. This, together stochastic evolution price output generated from auctioned project, precludes seller setting exact dates winner. However, can set to equa...

the notion of absorbent ordered filters in implicative semigroupsis introduced, and its fuzzification is considered. relations among (fuzzy) orderedfilters, (fuzzy) absorbent ordered filters, and (fuzzy) positive implicativeordered filters are stated. the extensionproperty for (fuzzy) absorbent orderedfilters is established. conditions for (fuzzy) ordered filters to be (fuzzy)absorbent ordered ...

This paper proposes a discrete recurrent neural network model to implement winner-take-all function. This network model has simple organizations and clear dynamic behaviours. The dynamic properties of the proposed winner-take-all networks are studied in detail. Simulation results are given to show network performance. Since the network model is formulated as discrete time systems , it has advan...

The runtime of winner determination for each round of a sequential bundle-bid auction (= SBB auction) has recently been shown to be linear in the number of submitted bids, which makes SBB auctions appealing for solving cooperative task-assignment problems. In this paper, we introduce the Shrewd (= SHrewd Resource Efficient Winner Determination) algorithm, whose runtime is linear in the number o...

This election uses the Approval method of voting. Mark each candidate that you approve of to serve in the particular position. You may vote for as many candidates as you wish. You may vote for all the candidates if you approve of them all; such a ballot will not help select a winner, but it will show that you voted and that you approved of the winner. The candidate with the largest number of vo...

In this paper, we propose a fast winner-take-all (WTA) neural network. The fast winner-take-all neural network with the dynamic ratio in mutual-inhibition is developed from the general mean-based neural network (GEMNET), which adopts the mean of the active neurons as the threshold of mutual inhibition. Furthermore, the other winner-take-all neural network enhances the convergence speed to becom...

This paper studies voting over quadratic taxation when income is fixed and taxation non distortionary. We first show that, if a Condorcet winner (a tax function preferred by a majority to any other feasible tax function) exists, it involves maximum progressivity. We then give necessary and sufficient conditions on the income distribution for a Condorcet winner to exist, and show numerically tha...

This paper is concerned with the phenomenon of winner-take-all competition. In this paper, we propose a continuous-time dynamic model, which is described by an ordinary differential equation and is able to produce the winner-take-all competition by taking advantage of selective positive–negative feedback. The global convergence is proven analytically and the convergence rate is also discussed. ...

This paper is an axiomatic study of consistent approval-based multi-winner rules, i.e., voting rules that select a fixed-size group of candidates based on approval ballots. We introduce the class of counting rules, provide an axiomatic characterization of this class and, in particular, show that counting rules are consistent. Building upon this result, we axiomatically characterize three import...