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机器学习中Inference 和predict的区别是什么? - 知乎 Inference: You want to understand how ozone levels are influenced by temperature, solar radiation, and wind Since you assume that the residuals are normally distributed, you use a linear regression model
如何简单易懂地理解变分推断 (variational inference)? - 知乎 How can we perform efficient inference and learning in directed probabilistic models, in the presence of continuous latent variables with intractable posterior distributions, and large datasets? 其中有几个关键词:inference and learning, intractable posterior distributions, large datasets 我们要明确 inference 的是什么?
请问因果推断领域有什么比较推荐的公开课吗? - 知乎 刚好最近写了个 因果推断系列文章,以下是我觉得比较好学习资料: Brady Neal的课程: Brady Neal《因果推理导论》中英字幕_哔哩哔哩_bilibili , 英文教学,但语速很慢。 2 清华大学 丁鹏教授 : 《因果推断简介》 ,中文材料。丁鹏教授是发过Natural 的大佬。 3 Gitbook: Causal Inference for the Brave and True
统计里面Post Selection主要是解决什么问题? - 知乎 [2]的主要贡献在于解决了如何在LASSO selection之后进行valid inference的问题,通过LASSO解的KKT condition刻画了LASSO selection event的性质(这是一个比较复杂的model selection问题,可以证明LASSO selection is a subset of some polyhetral set, and we can construct valid test by conditioning on this
如何入门分布上的优化 Wasserstein gradient flow? - 知乎 建议读我advisor这篇入门: proceedings mlr press v 这篇有很多详细的review和对比,例如欧氏空间优化的一些概念和假设推广到概率分布空间是啥?对于概率分布而言又等价于什么? 然后再去读Sinho的书(可能也需要理解Riemannian manifold上的一些基本几何定义,书上都有) 顺便提一个比较有趣的open problem