599 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- École Nationale Supérieure des Mines de ParisFR13 papers
- InsermFR11 papers
- Institut CurieFR11 papers
- Université Paris Sciences et LettresFR9 papers
- Cancer et génome: Bioinformatique, biostatistiques et épidémiologie des systèmes complexes6 papers
- École Normale Supérieure - PSLFR5 papers
- University of LeicesterGB5 papers
- N. I. Lobachevsky State University of Nizhny NovgorodRU4 papers
- Centre National de la Recherche ScientifiqueFR3 papers
- Département de mathématiques et applicationsFR3 papers
- Mathématiques Appliquées à Paris 5FR2 papers
- Broad InstituteUS1 paper
22 papers
Domain Adaptation Principal Component Analysis: base linear method for learning with out-of-distribution data
Evgeny M Mirkes, Jonathan Bac, Aziz Fouché +3
Domain adaptation is a popular paradigm in modern machine learning which aims at tackling the problem of divergence (or shift) between the labeled training and validation datasets…
Graph-Based Spatial Segmentation of Health-Related Areal Data
Vivien Goepp, Jan van de Kassteele
Smoothing is often used to improve the readability and interpretability of noisy areal data. However there are many instances where the underlying quantity is discontinuous. In thi…
Scikit-dimension: a Python package for intrinsic dimension estimation
Jonathan Bac, Evgeny M. Mirkes, Alexander N. Gorban +2
Dealing with uncertainty in applications of machine learning to real-life data critically depends on the knowledge of intrinsic dimensionality (ID). A number of methods have been s…
Trajectories, bifurcations and pseudotime in large clinical datasets: applications to myocardial infarction and diabetes data
Sergey E. Golovenkin, Jonathan Bac, Alexander Chervov +5
Large observational clinical datasets become increasingly available for mining associations between various disease traits and administered therapy. These datasets can be considere…
Equitable and Optimal Transport with Multiple Agents
Meyer Scetbon, Laurent Meunier, Jamal Atif +1
We introduce an extension of the Optimal Transport problem when multiple costs are involved. Considering each cost as an agent, we aim to share equally between agents the work of t…
Robust Seriation and Applications to Cancer Genomics
Antoine Recanati, Nicolas Servant, Jean-Philippe Vert +1
The seriation problem seeks to reorder a set of elements given pairwise similarity information, so that elements with higher similarity are closer in the resulting sequence. When a…
Robust And Scalable Learning Of Complex Dataset Topologies Via Elpigraph
Luca Albergante, Evgeny M. Mirkes, Huidong Chen +6
Large datasets represented by multidimensional data point clouds often possess non-trivial distributions with branching trajectories and excluded regions, with the recent single-ce…
Regularized Bidimensional Estimation of the Hazard Rate
Vivien Goepp, Jean-Christophe Thalabard, Grégory Nuel +1
In epidemiological or demographic studies, with variable age at onset, a typical quantity of interest is the incidence of a disease (for example the cancer incidence). In these stu…
DropLasso: A robust variant of Lasso for single cell RNA-seq data
Beyrem Khalfaoui, Jean-Philippe Vert
Single-cell RNA sequencing (scRNA-seq) is a fast growing approach to measure the genome-wide transcriptome of many individual cells in parallel, but results in noisy data with many…
WHInter: A Working set algorithm for High-dimensional sparse second order Interaction models
Marine Le Morvan, Jean-Philippe Vert
Learning sparse linear models with two-way interactions is desirable in many application domains such as genomics. l1-regularised linear models are popular to estimate sparse model…
Machine learning and genomics: precision medicine vs. patient privacy
Chloé-Agathe Azencott
Machine learning can have major societal impact in computational biology applications. In particular, it plays a central role in the development of precision medicine, whereby trea…
The Weighted Kendall and High-order Kernels for Permutations
Yunlong Jiao, Jean-Philippe Vert
We propose new positive definite kernels for permutations. First we introduce a weighted version of the Kendall kernel, which allows to weight unequally the contributions of differ…
Dynamic read mapping and online consensus calling for better variant detection
Karel Břinda, Valentina Boeva, Gregory Kucherov
Variant detection from high-throughput sequencing data is an essential step in identification of alleles involved in complex diseases and cancer. To deal with these massive data, e…
Consistency of random forests
Erwan Scornet, Gérard Biau, Jean-Philippe Vert
Random forests are a learning algorithm proposed by Breiman [Mach. Learn. 45 (2001) 5--32] that combines several randomized decision trees and aggregates their predictions by avera…
Group Lasso with Overlaps: the Latent Group Lasso approach
Guillaume Obozinski, Laurent Jacob, Jean-Philippe Vert
We study a norm for structured sparsity which leads to sparse linear predictors whose supports are unions of prede ned overlapping groups of variables. We call the obtained formula…
Analysis of the impact degree distribution in metabolic networks using branching process approximation
Kazuhiro Takemoto, Takeyuki Tamura, Yang Cong +3
Theoretical frameworks to estimate the tolerance of metabolic networks to various failures are important to evaluate the robustness of biological complex systems in systems biology…
The influence of feature selection methods on accuracy, stability and interpretability of molecular signatures
Anne-Claire Haury, Pierre Gestraud, Jean-Philippe Vert
Motivation: Biomarker discovery from high-dimensional data is a crucial problem with enormous applications in biology and medicine. It is also extremely challenging from a statisti…
Increasing stability and interpretability of gene expression signatures
Anne-Claire Haury, Laurent Jacob, Jean-Philippe Vert
Motivation : Molecular signatures for diagnosis or prognosis estimated from large-scale gene expression data often lack robustness and stability, rendering their biological interpr…
Dynamical modeling of microRNA action on the protein translation process
Andrei Zinovyev, Nadya Morozova, Nora Nonne +3
Protein translation is a multistep process which can be represented as a cascade of biochemical reactions (initiation, ribosome assembly, elongation, etc.), the rate of which can b…
Kernel matrix regression
Yoshihiro Yamanishi, Jean-Philippe Vert
We address the problem of filling missing entries in a kernel Gram matrix, given a related full Gram matrix. We attack this problem from the viewpoint of regression, assuming that…
Graph kernels based on tree patterns for molecules
Pierre Mahé, Jean-Philippe Vert
Motivated by chemical applications, we revisit and extend a family of positive definite kernels for graphs based on the detection of common subtrees, initially proposed by Ramon et…
Kernel methods in genomics and computational biology
Jean-Philippe Vert
Support vector machines and kernel methods are increasingly popular in genomics and computational biology, due to their good performance in real-world applications and strong modul…