贝叶斯优化（Bayesian Optimization, BO）虽然是超参数调优的利器，但在实际落地中往往会出现收敛慢、计算开销大等问题。很多时候直接“裸跑”标准库里的 BO，效果甚至不如多跑几次 Random Search。 所以要想真正发挥 BO 的威力，必须在搜索策略、先验知识注入以及 ...

The presentation below, “Using Bayesian Optimization to Tune Machine Learning Models” by Scott Clark of SigOpt is from MLconf. The talk briefly introduces Bayesian Global Optimization as an efficient ...

Background Conventionally, frequentist approach has been used to model health state valuation data. Recently, researchers started to explore the use of Bayesian methods in this area. Objectives This ...

Empirical Bayes is a versatile approach to “learn from a lot” in two ways: first, from a large number of variables and, second, from a potentially large amount of prior information, for example, ...