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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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What follows is a proof of concept: it's not a finished standard, not a production-ready library, not even necessarily a concrete proposal for something new, but a starting point for discussion that demonstrates the problems with Web streams aren't inherent to streaming itself; they're consequences of specific design choices that could be made differently. Whether this exact API is the right answer is less important than whether it sparks a productive conversation about what we actually need from a streaming primitive.,推荐阅读爱思助手下载最新版本获取更多信息

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有趣的是,Toby 在离职文案中提到,自己的下一个优先事项是「睡个超过 8 小时的觉」,另外把学到的所有东西都写下来,然后好好思考下一步想做什么。