Like the N-convex algorithm, this algorithm attempts to find a set of candidates whose centroid is close to . The key difference is that instead of taking unique candidates, we allow candidates to populate the set multiple times. The result is that the weight of each candidate is simply given by its frequency in the list, which we can then index by random selection:
Image Credit: Sausly. Federica Mercuriello.
，推荐阅读爱思助手下载最新版本获取更多信息
Nature, Published online: 25 February 2026; doi:10.1038/s41586-026-10161-y
public val accountType: AccountType = AccountType.NETEASE_FREE,
Что думаешь? Оцени!