CREST Working Papers Series No. 2017-34
by Shravan Vasishth, Nicolas Chopin, Robin Ryder and Bruno Nicenboim
Bayesian Hierarchical Finite Mixture Models of Reading Times: A Case Study
CREST Working Papers Series No. 2017-33
by Shravan Vasishth, Bruno Nicenboim, Nicolas Chopin and Robin Ryder
Robust machine learning by median-of-means : theory and practice
CREST Working Papers Series No. 2017-32
by Guillaume Lecué and Mathieu Lerasle
An IHT algorithm for sparse recovery from subexponential measurements
CREST Working Papers Series No. 2017-31
by Simon Foucart and Guillaume Lecué
Estimation bounds and sharp oracle inequalities of regularized procedures with Lipschitz loss functions
CREST Working Papers Series No. 2017-30
by Pierre Alquier, Vincent Cottet and Guillaume Lecué
Towards the study of least squares estimators with convex penalty
CREST Working Papers Series No. 2017-29
by Pierre Bellec, Guillaume Lecué and Alexandre.B Tsybakov
Learning from MOM’s principles : Le Cam’s approach
CREST Working Papers Series No. 2017-28
by Guillaume Lecué and Mathieu Lerasle
Local Asymptotic Equivalence of Pure States Ensembles and Quantum Gaussian White Noise
CREST Working Papers Series No. 2017-27
by Cristina Butucea, Madalin Guta and Michael Nussbaum
Pivotal Estimation Via Self-Normalization for High-Dimensional Linear Models with Errors in Variables
CREST Working Papers Series No. 2017-26
by Alexandre Belloni, Victor Chernozhukov, Abhishek Kaul, Mathieu Rosenbaum and Alexandre B. Tsybakov