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How good is the Bayes posterior for prediction really?

It might not be common courtesy of this blog to make comments on a very-recently-arxiv-ed paper. But I have seen two copies of this paper entitled “how good is the Bayes posterior in deep neural networks really”¬†left on the tray of the department printer during the past weekend, so I cannot underestimate the popularity of […]

“Machine Learning Under a Modern Optimization Lens” Under a Bayesian Lens

I (Yuling) read this new book Machine Learning Under a Modern Optimization Lens (by Dimitris Bertsimas and Jack Dunn) after I grabbed it from Andrew’s desk. Apparently machine learning is now such a wide-ranging area that we have to access it through some sub-manifold so as to evade dimension curse, and it is the same […]