Posted in 2023

On Problem Landscape and Conformal Prediction vs. Bayes Dilemma

There are a lot of ongoing debates between the Bayesian approach and doing conformal prediction. And I think this debate should not exist at all. Conformal prediction is a great approach, and it is more or less orthogonal to the Bayesian analysis. I’ll try to explain my vision about how conformal prediction relates to Bayesian analysis, what they share in common and why they are still very different.

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Bayes in the Wild

I talk about the Bayesian approach to wide range of problems. Show how it is related to traditional methods in ML and what tasks benefit from an alternative view.

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Bayesian AB Testing

I talk about how Bayesian AB testing can drive conclusions from data. There is always the whole pipeline of decision making process: panning, execution and delivery. Each of the stages benefits from domain knowledge about the experimental setting. In the talk I explain how this can be framed from a Bayesian perspective.

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The R2D2M2 Prior, the Awwwesome Linear Regression

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