Philippe Preux
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2010 – today
- 2018
- [j9]Benjamin Danglot, Philippe Preux, Benoit Baudry, Martin Monperrus:
Correctness attraction: a study of stability of software behavior under runtime perturbation. Empirical Software Engineering 23(4): 2086-2119 (2018) - [c43]Florian Strub, Mathieu Seurin, Ethan Perez, Harm de Vries, Jérémie Mary, Philippe Preux, Aaron C. Courville, Olivier Pietquin:
Visual Reasoning with Multi-hop Feature Modulation. ECCV (5) 2018: 808-831 - [c42]Benjamin Danglot, Philippe Preux, Benoit Baudry, Martin Monperrus:
Correctness attraction: a study of stability of software behavior under runtime perturbation. ICSE 2018: 481 - [i18]Kiewan Villatel, Elena Smirnova, Jérémie Mary, Philippe Preux:
Recurrent Neural Networks for Long and Short-Term Sequential Recommendation. CoRR abs/1807.09142 (2018) - [i17]Florian Strub, Mathieu Seurin, Ethan Perez, Harm de Vries, Jérémie Mary, Philippe Preux, Aaron C. Courville, Olivier Pietquin:
Visual Reasoning with Multi-hop Feature Modulation. CoRR abs/1808.04446 (2018) - [i16]Vincenzo Musco, Martin Monperrus, Philippe Preux:
A Large-Scale Study of Call Graph-based Impact Prediction using Mutation Testing. CoRR abs/1812.06286 (2018) - 2017
- [j8]Vincenzo Musco, Martin Monperrus, Philippe Preux:
A large-scale study of call graph-based impact prediction using mutation testing. Software Quality Journal 25(3): 921-950 (2017) - [c41]Georgios Papoudakis, Philippe Preux, Martin Monperrus:
A Generative Model for Sparse, Evolving Digraphs. COMPLEX NETWORKS 2017: 531-542 - [c40]Crícia Z. Felício, Klérisson V. R. Paixão, Célia A. Zorzo Barcelos, Philippe Preux:
A Multi-Armed Bandit Model Selection for Cold-Start User Recommendation. UMAP 2017: 32-40 - [i15]Georgios Papoudakis, Philippe Preux, Martin Monperrus:
A generative model for sparse, evolving digraphs. CoRR abs/1710.06298 (2017) - 2016
- [j7]Crícia Z. Felício, Klérisson V. R. Paixão, Guilherme Alves, Sandra de Amo, Philippe Preux:
Exploiting Social Information in Pairwise Preference Recommender System. JIDM 7(2): 99-115 (2016) - [j6]Azadeh Khaleghi, Daniil Ryabko, Jérémie Mary, Philippe Preux:
Consistent Algorithms for Clustering Time Series. Journal of Machine Learning Research 17: 3:1-3:32 (2016) - [j5]Hachem Kadri, Emmanuel Duflos, Philippe Preux, Stéphane Canu, Alain Rakotomamonjy, Julien Audiffren:
Operator-valued Kernels for Learning from Functional Response Data. Journal of Machine Learning Research 17: 20:1-20:54 (2016) - [c39]Frédéric Guillou, Romaric Gaudel, Philippe Preux:
Sequential Collaborative Ranking Using (No-)Click Implicit Feedback. ICONIP (2) 2016: 288-296 - [c38]Vincenzo Musco, Antonin Carette, Martin Monperrus, Philippe Preux:
A learning algorithm for change impact prediction. RAISE@ICSE 2016: 8-14 - [c37]Crícia Z. Felício, Klérisson V. R. Paixão, Célia A. Z. Barcelos, Philippe Preux:
Preference-Like Score to Cope with Cold-Start User in Recommender Systems. ICTAI 2016: 62-69 - [c36]Frédéric Guillou, Romaric Gaudel, Philippe Preux:
Large-Scale Bandit Recommender System. MOD 2016: 204-215 - [c35]Frédéric Guillou, Romaric Gaudel, Philippe Preux:
Scalable Explore-Exploit Collaborative filtering. PACIS 2016: 309 - [c34]Vincenzo Musco, Martin Monperrus, Philippe Preux:
Mutation-Based Graph Inference for Fault Localization. SCAM 2016: 97-106 - [i14]Benjamin Danglot, Philippe Preux, Benoit Baudry, Martin Monperrus:
Correctness Attraction: A Study of Stability of Software Behavior Under Runtime Perturbation. CoRR abs/1611.09187 (2016) - 2015
- [c33]Bilel Derbel, Philippe Preux:
Simultaneous optimistic optimization on the noiseless BBOB testbed. CEC 2015: 2010-2017 - [c32]Vincenzo Musco, Martin Monperrus, Philippe Preux:
An Experimental Protocol for Analyzing the Accuracy of Software Error Impact Analysis. AST@ICSE 2015: 60-64 - [c31]
- [i13]Hachem Kadri, Emmanuel Duflos, Philippe Preux, Stéphane Canu, Alain Rakotomamonjy, Julien Audiffren:
Operator-valued Kernels for Learning from Functional Response Data. CoRR abs/1510.08231 (2015) - [i12]Vincenzo Musco, Antonin Carette, Martin Monperrus, Philippe Preux:
A Learning Algorithm for Change Impact Prediction: Experimentation on 7 Java Applications. CoRR abs/1512.07435 (2015) - 2014
- [c30]Philippe Preux, Rémi Munos, Michal Valko:
Bandits attack function optimization. IEEE Congress on Evolutionary Computation 2014: 2245-2252 - [c29]Boris Baldassari, Flavien Huynh, Philippe Preux:
De l'ombre à la lumière : plus de visibilité sur l'Eclipse. EGC 2014: 513-516 - [c28]Jérémie Mary, Philippe Preux, Olivier Nicol:
Improving offline evaluation of contextual bandit algorithms via bootstrapping techniques. ICML 2014: 172-180 - [c27]Boris Baldassari, Philippe Preux:
Understanding software evolution: the maisqual ant data set. MSR 2014: 424-427 - [i11]Olivier Nicol, Jérémie Mary, Philippe Preux:
Improving offline evaluation of contextual bandit algorithms via bootstrapping techniques. CoRR abs/1405.3536 (2014) - [i10]Hai Thanh Nguyen, Jérémie Mary, Philippe Preux:
Cold-start Problems in Recommendation Systems via Contextual-bandit Algorithms. CoRR abs/1405.7544 (2014) - [i9]Jérémie Mary, Romaric Gaudel, Philippe Preux:
Bandits Warm-up Cold Recommender Systems. CoRR abs/1407.2806 (2014) - [i8]Vincenzo Musco, Martin Monperrus, Philippe Preux:
A Generative Model of Software Dependency Graphs to Better Understand Software Evolution. CoRR abs/1410.7921 (2014) - 2013
- [c26]Hachem Kadri, Mohammad Ghavamzadeh, Philippe Preux:
A Generalized Kernel Approach to Structured Output Learning. ICML (1) 2013: 471-479 - [i7]Hachem Kadri, Asma Rabaoui, Philippe Preux, Emmanuel Duflos, Alain Rakotomamonjy:
Functional Regularized Least Squares Classi cation with Operator-valued Kernels. CoRR abs/1301.2655 (2013) - [i6]Hachem Kadri, Philippe Preux, Emmanuel Duflos, Stéphane Canu:
Multiple functional regression with both discrete and continuous covariates. CoRR abs/1301.2656 (2013) - 2012
- [j4]Sertan Girgin, Jérémie Mary, Philippe Preux, Olivier Nicol:
Managing advertising campaigns - an approximate planning approach. Frontiers Comput. Sci. 6(2): 209-229 (2012) - [j3]Gabriel Dulac-Arnold, Ludovic Denoyer, Philippe Preux, Patrick Gallinari:
Sequential approaches for learning datum-wise sparse representations. Machine Learning 89(1-2): 87-122 (2012) - [c25]Hachem Kadri, Alain Rakotomamonjy, Francis R. Bach, Philippe Preux:
Multiple Operator-valued Kernel Learning. NIPS 2012: 2438-2446 - [c24]Gabriel Dulac-Arnold, Ludovic Denoyer, Philippe Preux, Patrick Gallinari:
Fast Reinforcement Learning with Large Action Sets Using Error-Correcting Output Codes for MDP Factorization. ECML/PKDD (2) 2012: 180-194 - [c23]Olivier Nicol, Jérémie Mary, Philippe Preux:
ICML Exploration & Exploitation Challenge: Keep it simple! ICML On-line Trading of Exploration and Exploitation 2012: 62-85 - [c22]Azadeh Khaleghi, Daniil Ryabko, Jérémie Mary, Philippe Preux:
Online Clustering of Processes. AISTATS 2012: 601-609 - [i5]Gabriel Dulac-Arnold, Ludovic Denoyer, Philippe Preux, Patrick Gallinari:
Fast Reinforcement Learning with Large Action Sets using Error-Correcting Output Codes for MDP Factorization. CoRR abs/1203.0203 (2012) - [i4]Hachem Kadri, Alain Rakotomamonjy, Francis R. Bach, Philippe Preux:
Multiple Operator-valued Kernel Learning. CoRR abs/1203.1596 (2012) - [i3]Hachem Kadri, Mohammad Ghavamzadeh, Philippe Preux:
A Generalized Kernel Approach to Structured Output Learning. CoRR abs/1205.2171 (2012) - 2011
- [c21]Hachem Kadri, Emmanuel Duflos, Philippe Preux:
Learning vocal tract variables with multi-task kernels. ICASSP 2011: 2200-2203 - [c20]Hachem Kadri, Asma Rabaoui, Philippe Preux, Emmanuel Duflos, Alain Rakotomamonjy:
Functional Regularized Least Squares Classication with Operator-valued Kernels. ICML 2011: 993-1000 - [c19]Gabriel Dulac-Arnold, Ludovic Denoyer, Philippe Preux, Patrick Gallinari:
Datum-Wise Classification: A Sequential Approach to Sparsity. ECML/PKDD (1) 2011: 375-390 - [i2]Gabriel Dulac-Arnold, Ludovic Denoyer, Philippe Preux, Patrick Gallinari:
Datum-Wise Classification: A Sequential Approach to Sparsity. CoRR abs/1108.5668 (2011) - 2010
- [c18]Victor Gabillon, Jérémie Mary, Philippe Preux:
Affichage de publicités sur des portails web. EGC 2010: 67-78 - [c17]Sertan Girgin, Jérémie Mary, Philippe Preux, Olivier Nicol:
Advertising Campaigns Management: Should We Be Greedy? ICDM 2010: 821-826 - [c16]Manuel Loth, Philippe Preux:
The Iso-regularization Descent Algorithm for the LASSO. ICONIP (1) 2010: 454-461 - [c15]Hachem Kadri, Emmanuel Duflos, Philippe Preux, Stéphane Canu, Manuel Davy:
Nonlinear functional regression: a functional RKHS approach. AISTATS 2010: 374-380
2000 – 2009
- 2009
- [c14]Philippe Preux, Sertan Girgin, Manuel Loth:
Feature discovery in approximate dynamic programming. ADPRL 2009: 109-116 - [c13]Manuel Loth, Philippe Preux, Samuel Delepoulle, Christophe Renaud:
ECON: A Kernel Basis Pursuit Algorithm with Automatic Feature Parameter Tuning, and its Application to Photometric Solids Approximation. ICMLA 2009: 162-169 - 2008
- [c12]Sertan Girgin, Philippe Preux:
Feature Discovery in Reinforcement Learning Using Genetic Programming. EuroGP 2008: 218-229 - [c11]
- [c10]Sertan Girgin, Philippe Preux:
Basis Function Construction in Reinforcement Learning Using Cascade-Correlation Learning Architecture. ICMLA 2008: 75-82 - [e1]Sertan Girgin, Manuel Loth, Rémi Munos, Philippe Preux, Daniil Ryabko:
Recent Advances in Reinforcement Learning, 8th European Workshop, EWRL 2008, Villeneuve d'Ascq, France, June 30 - July 3, 2008, Revised and Selected Papers. Lecture Notes in Computer Science 5323, Springer 2008, ISBN 978-3-540-89721-7 [contents] - 2007
- [c9]Manuel Loth, Philippe Preux, Manuel Davy:
A unified view of TD algorithms, introducing Full-gradient TD and Equi-gradient descent TD. ESANN 2007: 289-294 - 2006
- [i1]Manuel Loth, Philippe Preux:
A Unified View of TD Algorithms; Introducing Full-Gradient TD and Equi-Gradient Descent TD. CoRR abs/cs/0611145 (2006) - 2004
- [j2]Philippe Preux, Samuel Delepoulle, Jean-Claude Darcheville:
A generic architecture for adaptive agents based on reinforcement learning. Inf. Sci. 161(1-2): 37-55 (2004) - 2003
- [j1]Éric Ramat, Philippe Preux:
"Virtual laboratory environment" (VLE): a software environment oriented agent and object for modeling and simulation of complex systems. Simulation Modelling Practice and Theory 11(1): 45-55 (2003) - 2002
- [c8]
- 2001
- [c7]Samuel Delepoulle, Philippe Preux, Jean-Claude Darcheville:
Learning as a Consequence of Selection. Artificial Evolution 2001: 350-361 - [c6]Samuel Delepoulle, Philippe Preux, Jean-Claude Darcheville:
Selection of Behavior in Social Situations. EvoWorkshops 2001: 384-393 - 2000
- [c5]Éric Ramat, Philippe Preux:
Virtual Laboratory Environment (VLE) : un environnement multi-agents pour la modélisation et la simulation d'écosystèmes (démonstration). JFIADSMA 2000: 253-258
1990 – 1999
- 1999
- [c4]Samuel Delepoulle, Philippe Preux, Jean-Claude Darcheville:
Evolution of Cooperation within a Behavior-Based Perspective: Confronting Nature and Animats. Artificial Evolution 1999: 204-216 - 1998
- [c3]Cyril Fonlupt, Denis Robilliard, Philippe Preux:
A Bit-Wise Epistasis Measure for Binary Search Spaces. PPSN 1998: 47-56 - [c2]David Duvivier, Philippe Preux, Cyril Fonlupt, Denis Robilliard, El-Ghazali Talbi:
The fitness function and its impact on local search methods. SMC 1998: 2478-2483 - 1996
- [c1]
Coauthor Index
last updated on 2019-01-09 01:26 CET by the dblp team
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