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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这一转变，具体体现在对下沉市场的数字化基建、对中小商户的运营赋能，以及以前沿技术弥合服务鸿沟三个维度上。