A Fast Wang kWTA With Application in Sealed-Bid Uniform Price Auction.

Sum, John; Leung, Chi-Sing; Chang, Janet Chun-Chi · IEEE Trans Neural Netw Learn Syst · 2025

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Abstract

In this brief, two fast discrete-time Wang kWTA (Fast Wang kWTA) algorithms are presented with an application in sealed-bid uniform price auctions. These algorithms can either be implemented in centralized or distributed manner. The structure of the Fast Wang kWTA is essentially the same as the original Wang k-winner-take-all (kWTA), except that our state update method is based on bisection method instead of gradient descent. By that, the number of iterations for getting correct output is largely reduced. Besides, the number is just a factor depended on the guess of the maximum input value. It is independent of the number of inputs, the number of winners, and the learning step size. The number of iterations is far smaller than the number required in the original Wang kWTA. In sequel, this Fast Wang kWTA is particularly suitable to be applied in solving the winner (resp. price) determination in real time and in distributed manner for a sealed-bid auction. In addition, the Fast Wang kWTA can ensure bidding price protection even if the communicated data are not encrypted and leaked.