A conversation with Lucien Le Cam

Statistical estimation with model selection Lucien

The purpose of this paper is to explain the interest and importance of (approximate) models and model selection in Statistics. Starting from the very elementary example of histograms we present a general notion of finite dimensional model for statistical estimation and we explain what type of risk bounds can be expected from the use of one such model. We then give the performance of suitable mo...

Laurent Le Cam , Elena Vigo , Claude Sardet and Kristian

Le Cam meets LeCun: Deficiency and Generic Feature Learning

Deep Learning” methods attempt to learn generic features in an unsupervised fashion from a large unlabelled data set. These generic features should perform as well as the best hand crafted features for any learning problem that makes use of this data. We provide a definition of generic features, characterize when it is possible to learn them and provide algorithms closely related to the deep be...

Some thoughts on Le Cam ’ s statistical decision theory

The paper contains some musings about the abstractions introduced by Lucien Le Cam into the asymptotic theory of statistical inference and decision theory. A short, self-contained proof of a key result (existence of randomizations via convergence in distribution of likelihood ratios), and an outline of a proof of a local asymptotic minimax theorem, are presented as an illustration of how Le Cam...

Philosophy, Art and Critique: A (short) conversation with the “other”

The article sketches a nexus between philosophy, art (poetry) and critique with a particular emphasis on the contribution of classical Muslim philosophers. At the same time, it demonstrates how luminaries such as Omar Khayyam and Ibn Sina, contributed to the renewal of philosophy as a freedom seeking exercise and as a means to pursue happiness through knowledge. In the second&nbs...