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2020 – today
- 2022
[c46]Alexander Gerniers
, Pierre Dupont:
MicroCellClust 2: a hybrid approach for multivariate rare cell mining in large-scale single-cell data. BIBM 2022: 148-153- 2021
- [j13]Alexander Gerniers, Orian Bricard, Pierre Dupont:
MicroCellClust: mining rare and highly specific subpopulations from single-cell expression data. Bioinform. 37(19): 3220-3227 (2021) - [j12]Victor Hamer, Pierre Dupont:
An Importance Weighted Feature Selection Stability Measure. J. Mach. Learn. Res. 22: 116:1-116:57 (2021) - [c45]Victor Hamer, Pierre Dupont:
Robust Selection Stability Estimation in Correlated Spaces. ECML/PKDD (3) 2021: 446-461 - 2020
- [c44]Victor Hamer, Pierre Dupont:
Joint optimization of predictive performance and selection stability. ESANN 2020: 381-386
2010 – 2019
- 2019
- [j11]Vincent Branders, Pierre Schaus, Pierre Dupont:
Identifying gene-specific subgroups: an alternative to biclustering. BMC Bioinform. 20(1): 625 (2019) - [c43]Guillaume Derval, Vincent Branders, Pierre Dupont, Pierre Schaus:
The Maximum Weighted Submatrix Coverage Problem: A CP Approach. CPAIOR 2019: 258-274 - [c42]Vincent Branders, Guillaume Derval, Pierre Schaus, Pierre Dupont:
Mining a Maximum Weighted Set of Disjoint Submatrices. DS 2019: 18-28 - 2017
- [c41]Vincent Branders, Pierre Schaus, Pierre Dupont:
Combinatorial Optimization Algorithms to Mine a Sub-Matrix of Maximal Sum. NFMCP@PKDD/ECML 2017: 65-79 - [i2]Vincent Branders, Pierre Schaus, Pierre Dupont:
Mining a Sub-Matrix of Maximal Sum. CoRR abs/1709.08461 (2017) - 2015
- [j10]Jérôme Paul, Pierre Dupont:
Inferring statistically significant features from random forests. Neurocomputing 150: 471-480 (2015) - [j9]Jérôme Paul, Roberto D'Ambrosio, Pierre Dupont:
Kernel methods for heterogeneous feature selection. Neurocomputing 169: 187-195 (2015) - [c40]Samuel Branders, Benoît Frénay, Pierre Dupont:
Survival Analysis with Cox Regression and Random Non-linear Projections. ESANN 2015 - [i1]Samuel Branders, Roberto D'Ambrosio, Pierre Dupont:
A mixture Cox-Logistic model for feature selection from survival and classification data. CoRR abs/1502.01493 (2015) - 2014
- [c39]Samuel Branders, Roberto D'Ambrosio, Pierre Dupont:
The Coxlogit model: Feature selection from survival and classification data. MCDM 2014: 137-143 - [c38]Jérôme Paul, Pierre Dupont:
Kernel methods for mixed feature selection. ESANN 2014 - 2013
- [j8]Neil Walkinshaw, Bernard Lambeau, Christophe Damas, Kirill Bogdanov, Pierre Dupont:
STAMINA: a competition to encourage the development and assessment of software model inference techniques. Empir. Softw. Eng. 18(4): 791-824 (2013) - [j7]John Aldo Lee, Emilie Renard, Guillaume Bernard, Pierre Dupont, Michel Verleysen:
Type 1 and 2 mixtures of Kullback-Leibler divergences as cost functions in dimensionality reduction based on similarity preservation. Neurocomputing 112: 92-108 (2013) - [j6]Daniel Hernández-Lobato, José Miguel Hernández-Lobato, Pierre Dupont:
Generalized spike-and-slab priors for Bayesian group feature selection using expectation propagation. J. Mach. Learn. Res. 14(1): 1891-1945 (2013) - [c37]Emilie Renard, Pierre Dupont, Michel Verleysen:
User Control for Adjusting Conflicting Objectives in Parameter-dependent Visualization of Data. VAMP@EuroVis 2013 - 2012
- [c36]Jérôme Paul, Michel Verleysen, Pierre Dupont:
The stability of feature selection and class prediction from ensemble tree classifiers. ESANN 2012 - 2011
- [c35]Daniel Hernández-Lobato, José Miguel Hernández-Lobato, Pierre Dupont:
Robust Multi-Class Gaussian Process Classification. NIPS 2011: 280-288 - [c34]Roman Zakharov, Pierre Dupont:
Ensemble Logistic Regression for Feature Selection. PRIB 2011: 133-144 - 2010
- [j5]Thomas Abeel, Thibault Helleputte, Yves Van de Peer, Pierre Dupont, Yvan Saeys:
Robust biomarker identification for cancer diagnosis with ensemble feature selection methods. Bioinform. 26(3): 392-398 (2010) - [j4]Karoline Faust, Pierre Dupont, Jérôme Callut, Jacques van Helden:
Pathway discovery in metabolic networks by subgraph extraction. Bioinform. 26(9): 1211-1218 (2010) - [c33]Daniel Hernández-Lobato, José Miguel Hernández-Lobato, Thibault Helleputte, Pierre Dupont:
Expectation Propagation for Bayesian Multi-task Feature Selection. ECML/PKDD (1) 2010: 522-537
2000 – 2009
- 2009
- [c32]Thibault Helleputte, Pierre Dupont:
Partially supervised feature selection with regularized linear models. ICML 2009: 409-416 - [c31]Thibault Helleputte, Pierre Dupont:
Feature Selection by Transfer Learning with Linear Regularized Models. ECML/PKDD (1) 2009: 533-547 - 2008
- [j3]Pierre Dupont, Bernard Lambeau, Christophe Damas, Axel van Lamsweerde:
The QSM Algorithm and its Application to Software Behavior Model Induction. Appl. Artif. Intell. 22(1&2): 77-115 (2008) - [c30]Bernard Lambeau, Christophe Damas, Pierre Dupont:
State-Merging DFA Induction Algorithms with Mandatory Merge Constraints. ICGI 2008: 139-153 - [c29]Jérôme Callut, Kevin Françoisse, Marco Saerens, Pierre Dupont:
Semi-supervised Classification from Discriminative Random Walks. ECML/PKDD (1) 2008: 162-177 - 2007
- [c28]Pierre Schaus, Yves Deville, Pierre Dupont:
Bound-Consistent Deviation Constraint. CP 2007: 620-634 - [c27]Stéphane Zampelli, Yves Deville, Christine Solnon, Sébastien Sorlin, Pierre Dupont:
Filtering for Subgraph Isomorphism. CP 2007: 728-742 - [c26]Jean-Noël Monette, Yves Deville, Pierre Dupont:
A Position-Based Propagator for the Open-Shop Problem. CPAIOR 2007: 186-199 - [c25]Pierre Schaus, Yves Deville, Pierre Dupont, Jean-Charles Régin:
The Deviation Constraint. CPAIOR 2007: 260-274 - [c24]Jérôme Callut, Pierre Dupont:
Learning Partially Observable Markov Models from First Passage Times. ECML 2007: 91-103 - 2006
- [c23]Jérôme Callut, Pierre Dupont:
Sequence Discrimination Using Phase-Type Distributions. ECML 2006: 78-89 - 2005
- [j2]Pierre Dupont, François Denis, Yann Esposito:
Links between probabilistic automata and hidden Markov models: probability distributions, learning models and induction algorithms. Pattern Recognit. 38(9): 1349-1371 (2005) - [j1]Christophe Damas, Bernard Lambeau, Pierre Dupont, Axel van Lamsweerde:
Generating Annotated Behavior Models from End-User Scenarios. IEEE Trans. Software Eng. 31(12): 1056-1073 (2005) - [c22]Jérôme Callut, Pierre Dupont:
Séparateurs à Vaste Marge Optimisant la Fonction Fbeta. CAP 2005: 79-92 - [c21]Grégoire Dooms, Yves Deville, Pierre Dupont:
CP(Graph): Introducing a Graph Computation Domain in Constraint Programming. CP 2005: 211-225 - [c20]Stéphane Zampelli, Yves Deville, Pierre Dupont:
Approximate Constrained Subgraph Matching. CP 2005: 832-836 - [c19]Jérôme Callut, Pierre Dupont:
Inducing Hidden Markov Models to Model Long-Term Dependencies. ECML 2005: 513-521 - 2004
- [c18]Marco Saerens, François Fouss, Luh Yen, Pierre Dupont:
The Principal Components Analysis of a Graph, and Its Relationships to Spectral Clustering. ECML 2004: 371-383 - [c17]Jérôme Callut, Pierre Dupont:
A Markovian Approach to the Induction of Regular String Distributions. ICGI 2004: 77-90 - [c16]Grégoire Dooms, Yves Deville, Pierre Dupont:
Recherche de chemins contraints dans les réseaux biochimiques. JFPLC 2004 - [c15]Grégoire Dooms, Yves Deville, Pierre Dupont:
A Mozart Implementation of CP(BioNet). MOZ 2004: 237-250 - [c14]Christopher Kermorvant, Colin de la Higuera, Pierre Dupont:
Improving Probabilistic Automata Learning with Additional Knowledge. SSPR/SPR 2004: 260-268 - 2002
- [c13]Christopher Kermorvant, Pierre Dupont:
Improved Smoothing for Probabilistic Suffix Trees Seen as Variable Order Markov Chains. ECML 2002: 185-194 - [c12]Yann Esposito, Aurélien Lemay, François Denis, Pierre Dupont:
Learning Probabilistic Residual Finite State Automata. ICGI 2002: 77-91 - [c11]Christopher Kermorvant, Pierre Dupont:
Stochastic Grammatical Inference with Multinomial Tests. ICGI 2002: 149-160 - 2000
- [c10]Pierre Dupont, Juan-Carlos Amengual:
Smoothing Probabilistic Automata: An Error-Correcting Approach. ICGI 2000: 51-64 - [c9]Franck Thollard, Pierre Dupont, Colin de la Higuera:
Probabilistic DFA Inference using Kullback-Leibler Divergence and Minimality. ICML 2000: 975-982
1990 – 1999
- 1998
- [c8]Pierre Dupont, Lin Lawrence Chase:
Using Symbol Clustering to Improve Probabilistic Automaton Inference. ICGI 1998: 232-243 - [c7]Peter R. Kraus, Vijay Kumar, Pierre Dupont:
Analysis of Frictional Contact Models for Dynamic Simulation. ICRA 1998: 976-981 - 1996
- [c6]Tim Melanchuk, Pierre Dupont, Simon Backer:
CDPD and Emerging Digital Cellular Systems. COMPCON 1996: 2-8 - [c5]Pierre Dupont:
Incremental regular inference. ICGI 1996: 222-237 - 1994
- [c4]Pierre Dupont, Laurent Miclet, Enrique Vidal:
What Is the Search Space of the Regular Inference? ICGI 1994: 25-37 - [c3]Pierre Dupont:
Regular Grammatical Inference from Positive and Negative Samples by Genetic Search: the GIG Method. ICGI 1994: 236-245 - [c2]Pierre Dupont:
Overview of Current Virtual Reality Applications. IFIP Congress (3) 1994: 159-162 - 1993
- [c1]Pierre Dupont:
Dynamic use of syntactical knowledge in continuous speech recognition. EUROSPEECH 1993: 1959-1962
Coauthor Index
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