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math.ST2019
An improper estimator with optimal excess risk in misspecified density estimation and logistic regression
Jaouad Mourtada, Stéphane Gaïffas
We introduce a procedure for conditional density estimation under logarithmic loss, which we call SMP (Sample Minmax Predictor). This estimator minimizes a new general excess risk…
math.ST2019
Exact minimax risk for linear least squares, and the lower tail of sample covariance matrices
Jaouad Mourtada
We consider random-design linear prediction and related questions on the lower tail of random matrices. It is known that, under boundedness constraints, the minimax risk is of orde…
stat.ML2019
AMF: Aggregated Mondrian Forests for Online Learning
Jaouad Mourtada, Stéphane Gaïffas, Erwan Scornet
Random Forests (RF) is one of the algorithms of choice in many supervised learning applications, be it classification or regression. The appeal of such tree-ensemble methods comes…