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07/12/2023
Online Inventory Problems: Beyond the i.i.d. Setting with Online Convex Optimization
We study multi-product inventory control problems where a manager makes ...
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06/20/2023
Convergence and concentration properties of constant step-size SGD through Markov chains
We consider the optimization of a smooth and strongly convex objective u...
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08/10/2022
Robust methods for high-dimensional linear learning
We propose statistically robust and computationally efficient linear lea...
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01/31/2022
Robust supervised learning with coordinate gradient descent
This paper considers the problem of supervised learning with linear meth...
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09/16/2021
WildWood: a new Random Forest algorithm
We introduce WildWood (WW), a new ensemble algorithm for supervised lear...
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12/02/2020
About contrastive unsupervised representation learning for classification and its convergence
Contrastive representation learning has been recently proved to be very ...
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12/23/2019
An improper estimator with optimal excess risk in misspecified density estimation and logistic regression
We introduce a procedure for predictive conditional density estimation u...
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11/13/2019
ZiMM: a deep learning model for long term adverse events with non-clinical claims data
This paper considers the problem of modeling long-term adverse events fo...
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10/15/2019
SCALPEL3: a scalable open-source library for healthcare claims databases
This article introduces SCALPEL3, a scalable open-source framework for s...
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06/25/2019
AMF: Aggregated Mondrian Forests for Online Learning
Random Forests (RF) is one of the algorithms of choice in many supervise...
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09/05/2018
Anytime Hedge achieves optimal regret in the stochastic regime
This paper is about a surprising fact: we prove that the anytime Hedge a...
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07/25/2018
Comparison of methods for early-readmission prediction in a high-dimensional heterogeneous covariates and time-to-event outcome framework
Background: Choosing the most performing method in terms of outcome pred...
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07/10/2018
Dual optimization for convex constrained objectives without the gradient-Lipschitz assumption
The minimization of convex objectives coming from linear supervised lear...
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03/15/2018
Minimax optimal rates for Mondrian trees and forests
Introduced by Breiman (2001), Random Forests are widely used as classifi...
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12/21/2017
ConvSCCS: convolutional self-controlled case series model for lagged adverse event detection
With the increased availability of large databases of electronic health ...
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12/07/2017
High-dimensional robust regression and outliers detection with SLOPE
The problems of outliers detection and robust regression in a high-dimen...
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11/08/2017
Universal consistency and minimax rates for online Mondrian Forests
We establish the consistency of an algorithm of Mondrian Forests, a rand...
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07/10/2017
Sparse inference of the drift of a high-dimensional Ornstein-Uhlenbeck process
Given the observation of a high-dimensional Ornstein-Uhlenbeck (OU) proc...
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07/10/2017
tick: a Python library for statistical learning, with a particular emphasis on time-dependent modeling
tick is a statistical learning library for Python 3, with a particular e...
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03/24/2017
Binarsity: a penalization for one-hot encoded features
This paper deals with the problem of large-scale linear supervised learn...
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10/24/2016
C-mix: a high dimensional mixture model for censored durations, with applications to genetic data
We introduce a mixture model for censored durations (C-mix), and develop...
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07/21/2016
Uncovering Causality from Multivariate Hawkes Integrated Cumulants
We design a new nonparametric method that allows one to estimate the mat...
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10/16/2015
SGD with Variance Reduction beyond Empirical Risk Minimization
We introduce a doubly stochastic proximal gradient algorithm for optimiz...
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07/02/2015
Learning the intensity of time events with change-points
We consider the problem of learning the inhomogeneous intensity of a cou...
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01/04/2015
A generalization error bound for sparse and low-rank multivariate Hawkes processes
We consider the problem of unveiling the implicit network structure of u...
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12/24/2014
Concentration for matrix martingales in continuous time and microscopic activity of social networks
This paper gives new concentration inequalities for the spectral norm of...
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01/30/2014
Sparse Bayesian Unsupervised Learning
This paper is about variable selection, clustering and estimation in an ...
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09/14/2012
Link Prediction in Graphs with Autoregressive Features
In the paper, we consider the problem of link prediction in time-evolvin...
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12/08/2009
