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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:
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首先，蔚来需要打破规模的诅咒。要么主品牌销量爆发至百万级，要么乐道品牌大获成功摊薄成本，要么神玑真正走向外部市场成为独立供应商——否则，神玑将永远是一座昂贵的“孤岛”。
7 AI coding techniques that quietly make you elite
Senior news editor: China Collins