reinforcement learning,
including modeling of the dynamics of behavior in living beings (ongoing
since 1996 or so)
machine learning
application of machine learning
virtual laboratories (from 1996 to 2004)
genetic algorithms, combinatorial optimization, fitness landscapes,
local search algorithms (from 1994 to 1999)
old
stuffs on supercompilers done during my PhD (before 1993)
other topics
Notes de cours d'apprentissage par renforcement, Sep. 2021 (in French)
Machines à noyau : une courte introduction (ou « SVM décryptées », ou « SVMs pour les nuls ») (in French)
Data Data Data Data, École Centrale de Lille, Déc. 2012 (in French)
Tout ce que vous avez toujours voulu
savoir sur les systèmes dynamiques non-linéaires sans oser
le demander, (only available in French) Seconde édition (avr. 95)
(pdf) (in French)
More French material on my teaching page on reinforcement learning, data mining, ... (in French only).
Direct access to a year: 2024, 2023, 2022, 2021, 2020, 2019, 2018, 2017, 2016, 2015, 2014, 2013, 2012, 2011, 2010, 2009, 2008, 2007, 2006, 2005, 2004, 2003, 2002, 2001, 2000, 1999, 1998, 1997, 1996, 1995, 1994, 1992, 1991, 1990, 1989
T. Mathieu, M. Centa de Medeiros, R. Della Vecchia, H. Kohler, A. Shilova, O-A. Maillard, Ph. Preux, AdaStop: adaptive statistical testing for sound comparisons of Deep RL agents, Transactions on Machine Learning Research, Aug. 2024. on hal
P. Erbacher, J-Y. Nie, Ph. Preux, L. Soulier, Augmenting Ad-Hoc IR Dataset for Interactive Conversational Search, Transactions on Machine Learning Research, June 2024.
M. Basson, Ph. Preux, IDEQ: an improved diffusion model for the TSP, Inria research report 9558, July 2024.
A. Shilova, Th. Delliaux, B. Raffin, Ph. Preux,
Learning HJB Viscosity Solutions with PINNs for Continuous-Time Reinforcement Learning,
presented at the Foundations of Reinforcement Learning and Control -- Connections and Perspectives (FoRLaC) workshop at ICML, Vienna, Austria, July 2024. Also available on hal.
T. Mathieu, Ph. Preux,
Statistical comparison in empirical computer science with minimal computation usage,
short paper at ACM Conference on Reproducibility and Replicability (REP), Rennes, June 2024
A. Shilova, Th. Delliaux, B. Raffin, Ph. Preux,
Learning HJB Viscosity Solutions with PINNs for Continuous-Time Reinforcement Learning, Inria Research Report 9541, on hal, Jan 2024.
P. Saux, P. Bauvin, V. Raverdy, J. Teigny, H. Verkindt, T. Soumphonphakdy, M. Debert, A. Jacobs, D. Jacobs, V. Monpellier, P. Ching Lee, C. Hong Lim, J. Andersson-Assarsson, L. Carlsson, P-A. Svensson, F. Galtier, G. Dezfoulian, M. Moldovanu, S. Andrieux, J. Couster, M. Lepage, E. Lembo, O. Verrastro, M. Robert, P. Salminen, G. Mingrone, R. Peterli, R. Cohen, C. Zerrweck, D. Nocca, C. Le Roux, R. Caiazzo, Ph. Preux, F. Pattou,
Development and validation of an interpretable machine learning-based calculator for predicting 5-year weight trajectories after bariatric surgery: a multinational retrospective cohort SOPHIA study,
The Lancet Digital Health, 5(10), Oct. 2023. pdf on hal.
T. Mathieu, R. Della Vecchia, A. Shilova, M. Centa de Medeiros, H. Kohler, O-A. Maillard, Ph. Preux,
AdaStop: sequential testing for efficient and reliable comparisons of Deep RL Agents.
This paper is the Inria Research report RR-9513, first version in June 2023. Since then, the paper has evolved a lot. The current version of the research report is available
on hal,
and on arxiv,
An earlier version was presented at the European Worskhop on Reinforcement Learning (EWRL), 2023.
E. Vasconcellos, R. Sampaio, A. P. Araujo, E. Clua, Ph. Preux, R. Guerra, L. Gonçalves, L. Martí, H. Lira, N.S. Pi,
Reinforcement-learning robotic sailboats: simulator and preliminary results,
6th Robot Learning Workshop NeurIPS 2023: Pretraining, Fine-Tuning, and Generalization with Large Scale Models, Dec. 2023. on hal.
A.P.D. Araújo, D.H.J. Daniel, R. Guerra, D.N. Brandão, E.C. Vasconcellos, E.W.G. Clua, L.M.G. Goncalves, Ph. Preux,
General system architecture and COTS prototyping of an AIoT-enabled sailboat for autonomous aquatic ecosystem monitoring,
IEEE Trans on IoT, Online Oct. 2023, on hal.
P. Schegg, É. Ménager, E. Khairallah, D. Marchal, J. Dequidt, Ph. Preux, Ch. Duriez,
SofaGym: An open platform for Machine Learning based on Soft Robot simulations,
Soft Robotics, 10(2), pp. 410-430, Apr. 2023. Unpolished version on hal.
A. Shilova, Th. Delliaux, Ph. Preux, B. Raffin,
Revisiting Continuous-Time Reinforcement Learning. A Study of HJB Solvers Based on PINNs and FEMs,
presented at the European Worskhop on Reinforcement Learning (EWRL), 2023. Also available on hal.
C. Rozwag, F. Valentini, A. Cotten, X. Demondion, Ph. Preux, Th. Jacques,
Elbow trauma in children: development and evaluation of radiological artificial intelligence models},
Research in Diagnostic and Interventional Imaging, 6,
available on
on sciencedirect web site since April 29, 2023. sur hal.
A.P.D. Araújo, G.P. Chandrasekharan, E.W.G. Clua, Ph. Preux, E.Ch. Vasconcellos, L.M.G. Gonçalves,
Vision of the Seas: Open Visual Perception Framework for Autonomous Sailing Vessels,
Proc. International Conference on Systems, Signals and Image Processing (IWSSIP),
June, 2023. on hal.
H. Kohler, R. Akrour, Ph. Preux,
Optimal Interpretability-Performance Trade-off of Classification Trees with black-box Reinforcement Learning,
Inria research report RR-9503,
on hal.
M. Centa, Ph. Preux,
Soft Action Priors in Reinforcement Learning,
Proc. AAAI, 2023.
accepted version, on hal.
R. Gautron, E. J. Padrón González, Ph. Preux, J. Bigot, O-A. Maillard, G. Hoogenboom, J. Teigny,
Learning Crop Management by Reinforcement: gym-DSSAT,
accepted and presented at the AI for Agriculture and Food Systems (AIAFS) workshop at AAAI, Feb. 2023.
N. Grinsztajn, T. Johnstone, J. Ferret, Ph. Preux,
Better state exploration using action sequence equivalence,
Deep Reinforcement Learning workshop, NeurIPS 2022.
R. Gautron, O-A. Maillard, Ph. Preux, M. Corbeels, R. Sabbadin,
Reinforcement Learning for crop management support: review, prospects and challenges, Computers and Electronics in Agriculture, Sep. 2022. on hal.
R. Della Vecchia, A. Shilova, R. Akrour, Ph. Preux,
Entropy Regularized Reinforcement Learning with Cascading Networks,
European Workshop on Reinforcement Learning (EWRL), Sep. 2022. Inria research report 7003, on hal.
R. Gautron, E. J. Padrón, Ph. Preux, J. Bigot, D. Emukpere,
gym-DSSAT: a crop model turned into a Reinforcement Learning environment,
Inria Research Report number 9460, June 2022, on hal, on arxiv.
N. Mitton, L. Brossard, T. Bouadi, F. Garcia, R. Gautron, N. Hilgert, D. Ienco, Ch. Largouët, E. Lutton, V. Masson, R. Martin-Clouaire, M-L. Mugnier, P. Neveu, Ph. Preux, H. Raynal, C. Roussey, A. Termier, V. Bellon Maurel,
Foundations and state of the art,
in Agriculture and Digital Technology: Getting the most out of digital technology to contribute to the transition to sustainable agriculture and food systems,
Inria white book, pp. 30-75, 2022, on hal
P. Saux, P. Bauvin,
J. Teigny,
V. Raverdy,
H. Verkindt,
G. Dezfoulian,
M. Moldovanu,
S. Andrieux,
J. Couster,
M. Lepage,
A. Jacobs,
D. Jacobs,
V.M. Monpellier,
F. Galtier,
D. Nocca,
R. Caiazzo, Ph. Preux, F. Pattou,
Easy to use and interpretable model based on artificial intelligence for predicting 5-year weight trajectories after bariatric surgery,
Oral presentation at Zoom Forward 22, the joint congress on obesity of the European Association of the Study of Obesity and the International Federation for the Surgery of Obesity and metabolic disorders-European Chapter, May 2022
P. Schegg, J. Dequidt, E. Coevoet, É. Leurent, R. Sabatier, Ph. Preux, Ch. Duriez,
Automated planning for robotic guidewire navigation in the coronary arteries,
Proc. IEEE 5th International Conference on Soft Robotics (RoboSoft), pp. 239-246, Edinburgh, Scotland, UK, April 2022. on hal.
N. Grinsztajn, T. Johnstone, J. Ferret, Ph. Preux,
Better state exploration using action sequence equivalence,
arxiv preprint, Oct 2021
J. Ferret, N. Grinsztajn, Ph. Preux, M. Geist, O. Pietquin,
There Is No Turning Back: A Self-Supervised Approach for Reversibility-Aware Reinforcement Learning, Proc. NeurIPS, Dec. 2021. Preprint: arxiv preprint, on hal.
N. Grinsztajn, L. Leconte, Ph. Preux, É. Oyallon,
Interferometric Graph Transform for Community Labeling,
arxiv preprint, May 2021
N. Grinsztajn and O. Beaumont and E. Jeannot and Ph. Preux,
READYS: A Reinforcement Learning Based Strategy for Heterogeneous Dynamic Scheduling,
Proc. IEEE Cluster, 2021, on hal.
M. Seurin, F. Strub, Ph. Preux, O. Pietquin,
Don't do what doesn't matter: Intrinsic Motivation with Action Usefulness,
in Proc. IJCAI, 2021, on arxiv, and hal.
Y. Flet-Berliac, J. Ferret, O. Pietquin, Ph. Preux, M. Geist,
Adversarially Guided Actor-Critic,
in Proc. ICLR, 2021, on hal on arxiv.
Y. Flet-Berliac, R. Ouhamma, Ph. Preux, O-A. Maillard,
Learning Value Functions in Deep Policy Gradients using Residual Variance,
in Proc. ICLR 2021, on hal, on arxiv.
N. Grinsztajn, Ph. Preux, É. Oyallon,
Low-rank projections of GCNs Laplacian,
poster at the ICLR Workshop on Geometrical and Topological Representation Learning (GTRL), 2021, on hal, on arxiv.
M. Seurin, F. Strub, Ph. Preux, O. Pietquin,
Relevant Actions Matter: Motivating Agents with Action Usefulness,
poster at the ICLR Workshop on Self-Supervision for Reinforcement Learning Workshop, 2021
N. Grinsztajn and O. Beaumont and E. Jeannot and Ph. Preux,
Geometric deep reinforcement learning for dynamic DAG scheduling,
Proc. ADPRL 2020, on hal,
on arxiv
T. Levent, Ph. Preux, G. Henri, R. Alami, Y. Bonnassieux,
The challenge of controlling microgrids in the presence of rare events with Deep Reinforcement Learning, IET Smartgrid, (featured paper), on hal.
M. Seurin, F. Strub, Ph. Preux, O. Pietquin,
A Machine of Few Words: Interactive Speaker Recognition with Reinforcement Learning, Proc. Interspeech, 2020, on hal, on arxiv.
Y. Flet-Berliac, R. Ouhamma, O-A. Maillard, Ph. Preux,
Is Standard Deviation the New Standard? Revisiting the Critic in Deep Policy Gradients, preprint on hal, and on arxiv.
Y. Flet-Berliac, Ph. Preux,
Only Relevant Information Matters: Filtering Out Noisy Samples to Boost RL,
Proc. IJCAI 2020, on hal, on arxiv.
M. Seurin, Ph. Preux, O. Pietquin,
I'm sorry Dave, I'm afraid I can't do that: Deep-Q Learning From Forbidden Actions, Proc. IJCNN 2020, on arxiv.
Y. Flet-Berliac, Ph. Preux,
MERL: Multi-Head Reinforcement Learning,
NeurIPS 2019 DRL workshop, Vancouver, Canada,
Dec 2019. on hal, on arxiv.
M. Seurin, Ph. Preux, O. Pietquin,
I'm sorry Dave, I'm afraid I can't do that: Deep-Q Learning From Forbidden Actions.
NeurIPS 2019 workshop on Safety and Robustness in Decision Making, Vancouver, Canada, Dec 2019. on arxiv.
T. Levent, Ph. Preux, E. Le Pennec, J. Badosa, G. Henri, Y. Bonnassieux,
Energy Management for Microgrids: a Reinforcement Learning Approach,
ISGT Europe 2019, Bucharest, Romania, Sep 2019. on hal.
K. Villatel, E. Smirnova, J. Mary, Ph. Preux,
Recurrent Neural Networks for Long and Short-Term Sequential Recommendation, July 2018. Unpublished. on hal, arxiv:1807.09142.
F. Strub, M. Seurin, E. Perez, H. de Vries, J. Mary, Ph. Preux,
A. Courville, O. Pietquin,
Visual Reasoning with a Multi-hop FiLM Generator,
Proc. European Conference on Computer Vision (ECCV), Munchen, Germany, Sep 2018, LNCS 11209, Springer arxiv:1808.04446, hal-01927811..
B. Danglot, Ph. Preux, B. Baudry, M. Monperrus,
Correctness Attraction: A Study of Stability of Software Behavior Under Runtime Perturbation, accepted in the journal first program of the 40th International Conference on Software Engineering (ICSE), Gothenburg, Sweden, May 27 – June 3, 2018. (This is a 1 page summary of the journal paper.) Also highlihted on IEEE Software blog
B. Danglot, Ph. Preux, B. Baudry, M. Monperrus,
Correctness Attraction: A Study of Stability of Software Behavior Under Runtime Perturbation, Empirical Software Engineering, Aug. 2018, 23(4):2086-2119, The final
publication is available at link.springer.com. on hal. on arxiv
G. Papoudakis and Ph. Preux and M. Monperrus,
A generative model for sparse, evolving digraphs,
Proc. 6th International Conference on Complex Networks and their applications, Lyon,
Studies in Computational Intelligence, vol. 689, Springer-Verlag, 2017.
draft version, on arxiv, on hal.
V. Musco, M. Monperrus, Ph. Preux,
A Large Scale Study of Call Graph-based Impact Prediction using Mutation Testing, Software Quality Journal, 25(3), 921:950, Sep. 2017 (on hal)
C. Z. Felício and K.V.R. Paixão and C. A. Z. Barcelo and Ph. Preux,
A Multi-Armed Bandit Model Selection for Cold-Start User Recommendation,
Proc. 25th ACM Conference on User Modelling, Adaptation and Personalization (UMAP), Bratislava, Slovekia, July 2017. on hal.
B. Danglot, Ph. Preux, B. Baudry, M. Monperrus,
Correctness Attraction: A Study of Stability of Software Behavior Under Runtime Perturbation, on arxiv, this link for the official paper.
H. Kadri, E. Duflos, Ph. Preux, S. Canu, A. Rakotomamonjy, J. Audiffren,
Operator-valued Kernels for Learning from Functional Response Data,
Journal of Machine Learning Research,
17(20),1:54, 2016.
A. Khaleghi, D. Ryabko, J. Mary, Ph. Preux,
Consistent algorithms for clustering time series, Journal of Machine Learning Research, 17(3), 1:32.
C. Z. Felício, K.V.R. Paixão, G. Alves, S. de Amo, Ph. Preux,
Exploiting social information in pairwise preference recommender system,
Journal of Information and Data Management, 7(2), pp. 99:115, Aug. 2016
C. Z. Felício, K.V.R. Paixão, C. A. Z. Barcelo, Ph. Preux,
Preference-like Networks to Cope with User Cold Start in Recommender Systems,
in Proc. 28th IEEE International Conference on Tools with Artificial Intelligence (ICTAI), IEEE Computer Society, San Jose, Nov. 2016 (on hal)
F. Guillou, R. Gaudel, Ph. Preux, Sequential Collaborative Ranking Using (No-)Click Implicit Feedback, Proc. 23rd International Conference on Neural Information Processing (ICONIP), Springer, LNCS, Kyoto, Oct. 2016
V. Musco, M. Monperrus, Ph. Preux,
Mutation-Based Graph Inference for Fault Localization,
Proc. 16th IEEE International Working Conference on Source Code Analysis and Manipulation (SCAM), Oct. 2016 (on hal)
C. Z. Felício, K.V.R. Paixão, C. A. Z. Barcelo, Ph. Preux,
Multi-Armed Bandits to Recommend for Cold Start User,
Proc. Symposium on Knowledge Discovery, Mining and Learning (KDMILE), Recife, Brazil, Oct. 2016
F. Guillou, R. Gaudel, Ph. Preux, Large-scale bandit recommender systems, Proc. of the Second International Workshop on Machine Learning, Optimization and Big Data (MOD), Springer, LNCS, Aug. 2016.
F. Guillou, R. Gaudel, Ph. Preux, Scalable Explore-Exploit Collaborative Filtering, Proc. 20th Pacific Asia Conference on Information Systems (PACIS), Taiwan, June 2016
V. Musco, A. Carette, M. Monperrus, Ph. Preux,
A Learning Algorithm for
Change Impact Prediction: Experimentation on 7 Java Applications,
workshop ACM ICSE/RAISE, May 2016. on the ACM website (on hal).
F. Strub, R. Mary, Ph. Preux, Collaborative Filtering with stacked denoising autoencoders and sparse inputs, NIPS workshop Machine Learning for (e-)Commerce, 2015 (on hal)
F. Guillou, R. Gaudel, Ph. Preux, Collaborative Filtering as a Multi-Armed Bandit, NIPS workshop Machine Learning for (e-)Commerce, 2015 (on hal)
V. Musco, A. Carette, M. Monperrus, Ph. Preux,
A Learning Algorithm for
Change Impact Prediction: Experimentation on 7 Java Applications,
aug. 2015, later published at ACM ICSE/RAISE workshop in May 2016
J. Mary, R. Gaudel, Ph. Preux,
Bandits and Recommender Systems, Proc. 1st Int'l Workshop on Machine Learning, Optimization and big data (MOD), Springer/LNCS 9432, pp. 325:336, 2015. (on hal)
B. Derbel and Ph. Preux,
Simultaneous Optimistic Optimization on the Noiseless BBOB Testbed, Proc. IEEE Congress on Evolutionary Computation (CEC), pp. 2010--2017 , 2015 (accepted version; differs a little from the published version.)
V. Musco and M. Monperrus and Ph. Preux,
An Experimental Protocol for Analyzing the Accuracy of Software Error Impact Analysis, Proc. 10th IEEE/ACM International Workshop on Automation of Software Test (AST), associated with ICSE 2015, Florence, May 2015. on hal.
F. Guillou, R. Gaudel, J. Mary, Ph. Preux,
User engagement as evaluation: a ranking or a regression problem?,
ACM RecSYS challenge 2014 ``User Engagement as Evaluation'' workshop, winner of the challenge (see some pictures here, the official page).
J. Mary, R. Gaudel, Ph. Preux,
Bandits Warm-up Cold Recommender Systems, INRIA Research Report 8563, 2014, on hal, on arxiv.
V. Musco and M. Monperrus and Ph. Preux,
A Generative Model of Software Dependency Graphs to Better Understand Software Evolution, on arxiv, and on hal.
Ph. Preux, R. Munos, M. Valko, Bandits attack function optimization, Proc. IEEE Congress on Evolutionary Computation (CEC), July 2014. This paper is copyrighted by IEEE. (on hal) (on ieeeXplore.)
O. Nicol, J. Mary, Ph. Preux,
Improving offline evaluation of contextual bandit algorithms via bootstrapping techniques,
Proc. ICML, JMLR W&CP, 32Beijing, China, Jun 2014. (supplementary material)
B. Baldassari and Ph. Preux,
Understanding software evolution: the Maisqual Ant data set, in Proc.
11th Working Conference on Mining Software Repositories (MSR), 424-427, ACM Press, 2014
B. Baldassari, F. Huynh, Ph. Preux,
De l'ombre à la lumière : plus de visibilité sur l'Éclipse,
Proc. EGC, Rennes, Jan. 2014 (in French)
H. Kadri, M. Ghavamzadeh, Ph. Preux,
A Generalized Kernel Approach to Structured Output Learning,
Proc. ICML, JMLR W&CP 28(1):471-479, Atlanta, Jun. 2013 (available on Arxiv, also known as INRIA Research Report 7956 at this entry).
H. Kadri, A. Rakotomamonjy, F. Bach, Ph. Preux,
Multiple Operator-valued Kernel Learning, Proc. NIPS, pp. 2429-2438, 2012, also known as INRIA Research Report 7900, available on Arxiv (25 % acceptance rate)
G. Dulac-Arnold, L. Denoyer, Ph. Preux, P. Gallinari,
Sequential Approaches for Learning Datum-Wise Sparse Representations,
in Machine Learning, 89(1-2), 87-122, 2012.
G. Dulac-Arnold, L. Denoyer, Ph. Preux, P. Gallinari,
Fast Reinforcement Learning with Large Action Sets using Error-Correcting Output Codes for MDP Factorization, proceedings of the ECML-PKDD 2012, Springer, LNCS, 7524, 180:194, Sep. 2012, early draft (Feb. 2012) on Arxiv, also presented at the 10thEuropean Workshop on Reinforcement Learning
H. Kadri, M. Ghavamzadeh, Ph. Preux,
A Generalized Kernel Approach to Structured Output Learning, Feb. 2012, available on Arxiv, also known as INRIA Research Report 7956 (accpted at ICML'2013).
G. Dulac-Arnold, L. Denoyer, Ph. Preux, P. Gallinari,
Apprentissage par renforcement rapide pour des grands ensembles d'actions en utilisant des codes correcteurs d'erreur, JFPDA et CAP, Nancy, Mai 2012
S. Girgin and J. Mary and Ph. Preux and O. Nicol,
Managing Advertising Campaigns - an Approximate Planning approach,
in Frontiers of Computer Science, 6(2), 209:229, 2012.
O. Nicol and J. Mary and Ph. Preux,
ICML Exploration & Exploitation challenge: Keep it simple!,
in Journal of Machine Learning Research W&CP, 26, 62:85, 2012.
A. Khaleghi, D. Ryabko, J. Mary, Ph. Preux,
Online clustering of processes,
in Proc. 15th Conf. on Ai & Stats, Journal of Machine Learning Research W&CP, 22, 601-609, 2012
G. Dulac-Arnold, L. Denoyer, Ph. Preux, P. Gallinari,
Datum-wise classification. A sequential Approach to sparsity
in Machine Learning and Knowledge Discovery in Databases (aka, Proc. European Conference
on Machine Learning and Principles and Practice of Knowledge
Discovery in Databases (ECML PKDD)),
Springer, LNAI, vol. 6911, 375-390, Athens, Greece, Sep. 2011 (20 % acceptance rate), on arxiv, on Springer website.
H. Kadri, A. Rabaoui, Ph. Preux, E. Duflos, A. Rakotomamonjy,
Functional Regularized
Least Squares Classification with Operator-Valued Kernels,
in Proc. 28th International Conference on Machine Learning (ICML), Seattle, ACM Press, 2011 (26 % acceptance rate)
H. Kadri, Ph. Preux, E. Duflos, S. Canu,
Multiple functional regression with both discrete and continuous covariates,
in F. Ferraty (ed), Recent Advances in Functional Data Analysis and Related Topics, Physica-Verlag/Springer, Contributions to Statistics series, 189:195, 2011, Proc. 2nd International Workshop on Functional and Operatorial Statistics (IWFOS), Santander, June 2011
(paper available on the Springer website).
H. Kadri, Ph. Preux, E. Duflos,
Régression ridge à noyau pour des variables explicatives et
d'intérêts fonctionnelles (draft),
in Proc. 43e Journées de
statistiques (JDS), Mai 2011
H. Kadri, E. Duflos, Ph. Preux,
Learning vocal tract variables with multi-task kernels,
in Proc. 36th International
Conference on Acoustics, Speech and Signal
Processing (ICASSP), pp. 821-826, Prague, Czech Republic, May 2011
H. Kadri, Ph. Preux, E. Duflos, S. Canu,
Operator-Valued
Kernels for Nonparametric Operator Estimation,
INRIA research report RR-7607, April 2011
S. Girgin, J. Mary, Ph. Preux, O. Nicol,
Advertising Campaigns Management: Should We Be Greedy?,
in Proc. 10th IEEE International Conference on Data Mining (ICDM), pp. 821-826, Sydney, Australia, Dec. 2010
(pdf)
(short (6 pages) paper: acceptance rate < 20 % for long + short papers),
extended version available as the
INRIA research
report 7388
(Abstract here.)
S. Girgin, J. Mary, Ph. Preux, O. Nicol,
Planning-based Approach for Optimizing the Display of Online
Advertising Campaigns, poster at the
NIPS workshop on Machine Learning in Online ADvertising (MLOAD 2010)
Hachem Kadri, Philippe Preux, Emmanuel Duflos, Stéphane Canu, Manual Davy,
Function-Valued Reproducting Kernel Hilbert Spaces and Applications,
poster at the NIPS workshop on Tensors, Kernels, and Machine Learning (TKML 2010)
M. Loth, Ph. Preux,
The Iso-lambda Descent Algorithm for the LASSO,
in Proc. of ICONIP, Neural Information Processing. Theory and Algorithms, Springer LNCS 6443, pp. 454-461, Sydney, Nov. 2010 (31 % acceptance rate, 146 out of 470)
(Abstract here.)
S. Delepoulle, F. Rousselle, Ch. Renaud, Ph. Preux,
A comparison of two machine learning approaches for Photometric Solids
Compression, in Proc. of the 13th Int'l
Conf. on Computer Graphics and Artificial Intelligence
(3IA), 132:142, Athens, Greece, May 2010.
Also selected for publication in
D. Plemenos, G. Miaoulis (Eds),
Intelligent Computer Graphics 2010,
Springer, Studies in Computational Intelligence, Vol. 321, 145:164
(pdf of the 3IA conf. version)
H. Kadri, E. Duflos, Ph. Preux, S. Canu, M. Davy,
Nonlinear functional
regression: a functional RKHS approach, (also available here)
in Proc. of the 13th Int'l Conf. on
Artificial Intelligence and Statistics (AI & Stats), JMLR:
W&CP 9, pp. 374:380, Chia Laguna, Italy, May 13-15, 2010.
(orally presented paper: acceptance rate is 24 out of 308 submissions, less than 8 % thus.)
V. Gabillon, J. Mary, Ph. Preux,
Affichage de publicités sur des portails web,
in Proc. 10e Extraction,
Gestion des Connaissances (EGC), Tunisie, 2010
(pdf)
This paper received a best paper award.
(long paper: acceptance rate < 25 % for long papers)
(More details here.)
M. Loth, Ph. Preux, S. Delepoulle, Ch. Renaud,
ECON: a Kernel Basis Pursuit Algorithm with Automatic Feature
Parameter Tuning, and its Application to Photometric Solids Approximation,
in Proc. Int'l Conf.
on Machine Learning and Applications (ICML-A), Miami, USA, 2009
(a draft is available here)
An implementation of the algorithm (ECON) is available by clicking on this link.
(More details here.)
H. Kadri, E. Duflos, M. Davy, Ph. Preux, S. Canu,
A General Framework for Nonlinear Functional Regression with
Reproducing Kernel Hilbert Spaces,
INRIA Research Report 6809,
2009. This paper was improved, and published
in the proc. of the AI & Stats'2010 conf.
S. Delepoulle, Ch. Renaud, Ph. Preux,
Light Source Storage and Interpolation for Global Illumination:
a neural solution, in
Intelligent Computer Graphics,
D. Plemenos and G. Miaoulis eds, Springer 2009,
Studies in Computational Intelligence series, Vol. 240, 87-104
S. Delepoulle, Ch. Renaud, Ph. Preux,
Photometric compression and interpolation for light source repreentation, in
Proc. 12th Int'l
Conf. on Computer Graphics and Artificial Intelligence
(3IA),
Athens, Greece, May 2009 (pdf available here)
M. Loth, Ph. Preux,
Automatic synthesis
of sparse neural networks using l1 regularization.
This paper was rejected at
ICANN 2009.
I found interesting though to put it on my webpage. I found particularly
interesting the reviews we got; so
I
publish them completely on the web, and I allow myself to review
the reviews. An updated, and published, version of this paper
(in particular, the experimental results have been much improved)
is available here, in the ICMLA'2009
Proceedings.
M. Loth, Ph. Preux, l1 regularization path for functional
features, poster at the
Pascal
Workshop ``Sparsity in Machine Learning and Statistics'',
Cumberland Lodge, UK, Apr. 2009
(1 page abstract, and
the poster)
Ph. Preux, S. Girgin, Sparsity in Adaptive Control,
poster at the Pascal Workshop ``Sparsity in Machine Learning and Statistics'',
Cumberland Lodge, UK, Apr. 2009
(1 page abstract, and
the poster)
Ph. Preux, S. Girgin, M. Loth,
Feature Discovery in Approximate Dynamic Programming, in
Proc. Approximate Dynamic Programming and Reinforcement Learning
(ADPRL),
IEEE Press, 109:116, Nashville, Mar-Apr. 2009 (draft available here,
final version on IEEExplore)
(More details here.)
M. loth, Ph. Preux,
The Equi-Correlation Network: a New Kernelized-LARS with
Automatic Kernel Parameters Tuning,
INRIA Research Report 6794,
2008 (pdf available here, which
is a little more up-to-date than the version available on HAL; the
ICML-A paper provides more recent results).
S. Girgin, M. Loth, R. Munos Ph. Preux, D. Ryabko, (eds)
Recent Advances in Reinforcement Learning,
Springer, Lecture Notes in Artificial Intelligence, vol. 5323,
Feb. 2009
S. Girgin, Ph. Preux,
Basis Function Construction in Reinforcement Learning using
Cascade-Correlation Learning Architecture, in Proc. of the
International Conference
on Machine Learning and Applications (ICML-A), 75--82, IEEE Press,
La Jolla, USA, Dec. 2008
(the paper is copyrighted by IEEE Press,
available on IEEExplore,
an early draft is available.
Despite having the same title as the following paper, these two
papers are not the same; the ICML-A paper is more thorough.)
S. Girgin, Ph. Preux,
Incremental basis function expansion in reinforcement learning
using cascade-correlation networks, in Proc. of the ECAI
ERLARS workshop, Patras, Greece,
Jul 2008 (see the January 2008 INRIA research report
INRIA
research report RR-6505)
S. Girgin, Ph. Preux,
Basis Expansion In Natural Actor
Critic Methods,
in Girgin et al., Recent
Advances in Reinforcement Learning, Springer, Lecture Notes
in Artificial Intelligence, vol. 5323, pp. 110-123, 2009.
(More details here.)
S. Girgin, Ph. Preux,
Feature discovery in reinforcement learning using genetic
programming, in
Proc. 11th European Conference on Genetic Programming
(EUROGP), Mar 2008
See the associate
INRIA research report. Best paper award nominee,
see here
M. Loth, Ph. Preux, M. Davy,
A unified view of TD algorithms - Introducing full-gradient TD and
Equi-gradient descent TD, in Proc. European Symposium on
Artificial Neural Networks (ESANN), Apr. 2007.
on arxiv.
M. Loth, M. Davy, Ph. Preux,
Sparse temporal difference learning using LASSO,
Oct 2006 draft on-line, final version in the proc. of the IEEE International
Symposium on Approximate Dynamic Programming and Reinforcement
Learning, pp. 352:359, available on IEEExplore,
Hawaii,
2007
(More details here.)
Ph. Preux, S. Delepoulle, R. Coulom (eds),
Prise de décision séquentielle,
numéro spécial de la revue d'intelligence artificielle (RIA),
volume 21, numéro 1, jan. 2007
F. Montagne, Ph. Preux, S. Delepoulle,
Introducing interactive help for reinforcement learners,
Workshop on planning, learning and monitoring with
uncertainty and dynamic worlds, ECAI Workshop, Aug 2006
M. Loth, M. Davy, R. Coulom, Ph. Preux,
Equi-gradient Temporal Difference Learning,
Kernel methods for reinforcement learning, ICML Workshop, June 2006
(More details here.)
M. Loth, R. Coulom, M. Davy, Ph. Preux,
Least
Angle Temporal Difference Learning: LATD(λ),
Journées
Francophones Planification, Décision, Apprentissage,
Toulouse, France, May 2006 (In French)
O. Ambrym-Maillard, R. Coulom, Ph. Preux,
Parallelization of the TD(λ) learning algorithm,
European Workshop on reinforcement Learning, Naples, Oct 2005
N. Langlois, R. Coulom, Ph. Preux,
Decomposing a value function into a sum of neural networks,
European Workshop on reinforcement Learning, Naples, Oct 2005
Ph. Preux, S. Delepoulle, J-Cl. Darcheville,
A
Generic architecture for Adaptive Agents Based on
Reinforcement Learning,
Information Sciences Journal, 161, 37--55, Elsevier, 2004. The
on-line version is a draft.
F. Montagne, S. Delepoulle, Ph. Preux,
A
critic-critic architecture to combine reinforcement and supervised
learnings,
European Workshop on reinforcement Learning, Nancy, Sep 2003
R. Duboz, É. Ramat, Ph. Preux,
Scale transfer modeling: using emergent computation for
coupling an ordinary differential equation system
with a reactive agent model,
Systems Analysis Modeling and Simulation, 43(6),
pp. 793:814, Jun 2003
R. Duboz, F. Amblard, É. Ramat, G. Deffuant, Ph. Preux,
Individual-based model to enrich an aggregate model,
Model to model workshop ,
Mar-Apr 2003, Marseille, France
R. Duboz, F. Amblard, É. Ramat, G. Deffuant, Ph. Preux,
Utiliser les modèles indidividus-centrés comme laboratoires virtuels
pour identifier les paramètres d'un modèle agrégé,
Proc. MOSIM 2003
É. Ramat, Ph. Preux,
"Virtual Laboratory Environment" (VLE): a software environment agent
and object oriented for modeling and simulation of complex systems,
Simulation, Practice and Theory , 2002
Ph. Preux,
Propagation of Q-values in Tabular TD(λ),
European Conf.
on machine Learning (ECML),
Springer-Verlag, LNAI 2430, Aug. 2002
(
S. Delepoulle, Ph. Preux, J-C. Darcheville,
Multi-segmented models to simulate vertebrate organisms,
Société de biomécanique, Archives of physiology and
biochemistry, vol 110, Valenciennes, 2002.
J. Jozéfowiec, J-Cl. Darcheville, Ph. Preux,
Using Markovian Decision Problems to Analyze Animal
Performance in Random and Variable Ratio Schedules of Reinforcement,
SAB 7, From Animals to Animats,
Edinburgh, Scotland, Aug 2002
J. Jozéfowiec, J-Cl. Darcheville, Ph. Preux,
Operant conditioning as a Markovian decision
problem: application to variable and random ratio
schedules of reinforcement,
poster at the Symposium
for the Quantitative Analyses of Behavior, Toronto, Canada, May 2002
Ph. Preux, S. Delepoulle, J-Cl. Darcheville, Modélisation
du comportement animal et apprentissage par renforcement, rapport interne
LIL-01-02, Oct. 2001
(pdf)
S. Delepoulle, Ph. Preux, J-C. Darcheville,
L'apprentissage par renforcement comme résultat de la sélection,
Extraction des connaissances et apprentissage, 1(3), 9:30, 2001
(pdf)
S. Delepoulle, Ph. Preux, J-C. Darcheville,
Learning as a consequence of selection,
Artificial Evolution, Oct 2001, Le Creusot, France,
Springer-Verlag, LNCS
(pdf)
Ph. Preux, Ch. Cassagnabère, S. Delepoulle, J-C. Darcheville,
A non supervised multi-reinforcement agents architecture
to model the development of behavior of living organisms European Workshop
on Reinforcement Learning (EWRL-5), Sep 2001, Utrecht, Pays-Bas
(pdf)
R. Duboz, É. Ramat, Ph. Preux, Towards a coupling
of continuous and discrete formalisms in ecological modelling - Influences
of the choice of algorithms and result, European Simulation Symposium, Oct
2001, Marseille, France
(doc)
S. Delepoulle, Ph. Preux, J-C. Darcheville, Dynamique
de l'interaction, Modèles Formels de l'Interaction, Mai 2001, Toulouse
(pdf)
S. Delepoulle, Ph. Preux, J-C. Darcheville, Selection
of Behavior in Social Situations - Application to the development of coordinated
movements, First European Workshop on Evolutionary Learning, EuroGP 2001,
Springer-Verlag, LNCS Avr 2001, Como, Italie
(pdf)
É. Ramat, Ph. Preux, Virtual Laboratory Environment
(VLE) : un environnement multi-agents et objets pour la modélisation
et la simulation de systèmes complexes, MOSIM
Avr 2001, Troyes, France
(doc)
Ph. Preux, S. Delepoulle, J-C. Darcheville, Selection
of behaviors by their consequences in the human baby, software agents,
and robots, Computational Biology, Genome Information Systems and Technology
Mar 2001, Durham, USA (pdf)
S. Delepoulle, Ph. Preux, J-C. Darcheville, Simulation
of social behaviors: why and how?, M. J'al. of Behavior Analysis, 26(2),
191:209, Sep 2000
J. Josefowiecz, J-Cl. Darcheville, Ph. Preux, An
operant approach to the prisoners' dilemma: indirect reinforcement of controlling
behaviors in simple reinforcement learning agents allows the emergence
of stable cooperation, M. J'al. of Behavior Analysis, 26(2), 211:227, Sep
2000
E. Ramat, Ph. Preux, Virtual Laboratory Environment
(VLE): un environnement multi-agents pour la modélisation et la
simulation d'écosystèmes, Systèmes Multi-agents -
Méthodologie, technologie et expériences (JFIADSMA 2000),
Hermès, pp. 252:258, Septembre 2000
S. Delepoulle, Ph. Preux, J-Cl. Darcheville, Un système
coopératif pour la simulation comportementale. Application au contrôle
d'un bras mobile, Neurosciences
et sciences de l'ingénieur, Rennes, France, Septembre 2000
(pdf)
S. Delepoulle, J-Cl. Darcheville, Ph. Preux, Cooperation
in dependent situation: experiment on dyads,
European
Meeting on the Experimental Analysis of Behabior, Amiens, France, Juillet
2000
L. Seuront, E. Ramat, Ph. Preux, Y. Lagadeuc, An
Individual-Based Approach of Zooplankton Behavior in Microscale Phytoplankton
Patches, American Society for Limnology and Oceanography Annual Meeting,
Juin 2000, Copenhague, Danemark
Y. Lagadeuc, V. Gentilhomme, F. Lizon, L. Seuront,
Ph. Preux, E. Ramat, J-C. Poggiale, Vers une étude des transferts
d'échelles en écologie planctonique, workshop ressources
aquatiques : modélisation, contrôle, effets physiques et océanographie,
Mai 2000, Marrakech
Ph. Preux, E-G. Talbi, Towards Hybrid Evolutionary
Algorithms, International Transactions in Operational Research, vol. 6,
557:570, 1999 (© Elsevier) pdf draft version
S. Delepoulle, Ph. Preux, J-Cl. Darcheville,
Evolution of cooperation within a behavior-based perspective,
Evolution Artificial,
Springer-Verlag, Lecture Notes in Computer Science 1829,
2000, pdf
L. Seuront, F. Schmitt, Y. Lagadeuc, E. Ramat, Ph.
Preux, Turbulence intermittency and small-scale phytoplankton patchiness:
effects on plankton trophodynamics, XXIV General Assembly of the European
Geophysical Society, Den Haag, The Netherlands, Avril 1999
Ph. Preux, D. Robilliard, C. Fonlupt, E-G. Talbi,
V. Bachelet, Reaching summits is not wandering, or, Getting insight into
problem landscapes to go higher, faster, Technical Report LIL-99-5, Jan
1999
(pdf)
Yvan Lagadeuc, Laurent Seuront, Eric Ramat, Philippe
Preux, Pascal Pitiot, Vanessa Denis, Laurent Falk, Hervé Vivier,
Microscale turbulence intermittency and zooplankton dynamics: how to include
behavioral components? Technical Report LIL-99-4, Fév 1999
Eric Ramat, Philippe Preux, Laurent Seuront, Yvan
Lagadeuc, Multi-agent modeling of the physical/biological coupling - A
case study in marine biology, Technical Report LIL-99-3, Fév 1999
(pdf)
Ph. Preux, D. Robilliard, C. Fonlupt,
Simplicity can meet efficiency - The case of the TSP, (1 page abstract)
Twelfth
Meeting of the European Chapter on Combinatorial Optimization, Bendor,
Mai 1999
(pdf)
Ph. Preux, D. Duvivier,
Creating gradient to help local search algorithm - Application to tabu search for the simple
Job-Shop-Scheduling Problem,
(1 page abstract)
Twelfth
Meeting of the European Chapter on Combinatorial Optimization, Bendor,
Mai 1999
(pdf)
C. Fonlupt, D. Robilliard, Ph. Preux, E-G. Talbi,
"Fitness Landscape and Performance of Meta-Heuristics", in Meta-Heuristics
- Advances and Trends in Local Search Paradigms for Optimization, Stefan
Voss, Silvano Martello, Ibrahim Osman, Catherine Roucairol (eds), chap.
18, Kluwer Academic Press, 255-266, 1999
(pdf)
S. Delepoulle, Ph. Preux, J-Cl. Darcheville, Coopération
en situation d'interaction minimale : quelle simulation ? Colloque ACCION
"L'interdisciplinarité en sciences de la cognition", Marseille,
Jan 1999
Ph. Preux, Réflexions sur quelques systèmes complexes et leur
dynamique, mémoire d'habilitation à diriger les recherches,
ULCO, Calais, Jan 1999
D. Duvivier, Ph. Preux, C. Fonlupt, D. Robilliard,
E-G. Talbi, The fitness function and its impact on Local Search Methods,
IEEE
Systems, Man, and Cybernetics, La Jolla, USA, Oct. 1998
(pdf)
C. Fonlupt, D. Robilliard, Ph. Preux, A Bit-Wise
Epistasis Measure for Binary Search Spaces PPSN 98, Amsterdam,
Springer-Verlag,
LNCS, Oct 1998 (pdf)
(© Springer-Verlag)
E. Ramat, Ph. Preux, L. Seuront, Y. Lagadeuc, Modélisation
et simulation multi-agents en biologie marine - Étude du comportement
du copépode,
Modèles
et Systèmes Multi-Agents pour la Gestion de l'Environnement et des
Territoires (SMAGET'98), Clermont-Ferrand, Oct 1998
(pdf)
J. Joséfowicz, J-C. Darcheville, Ph. Preux,
L'émergence de comportements de contrôle chez des agents sélectionnistes
leur permet de résoudre le dilemme du prisonnier, Journées
Francophones d'Apprentissage, 174-185, Arras, Mai 1998
S. Delepoulle, Ph. Preux, J-C. Darcheville, Répartition
des tâches : coopération et apprentissage par renforcement,
Journées Francophones d'Apprentissage, 201-204, Arras, Mai 1998
V. Bachelet, E-G. Talbi, Ph. Preux,
Diversifying Tabu Search by Genetic Algorithms,
1998, INFORMS/CORS 1998, Montreal, Canada
C. Fonlupt, P. Preux, D. Robillard, E-G. Talbi, Paysages
des problèmes NP-durs et métaheuristiques, 1er congrès
"Recherche Opérationnelle et Aide à la décision" (ROAD-F),
Paris, Jan 1998
D. Duvivier, Ph. Preux, Impact de la fonction objectif
sur les performances des algorithmes itératifs de recherche locale,
1er congrès "Recherche Opérationnelle et Aide à la
décision" (ROAD-F), Paris, Jan 1998
V. Bachelet, Z. Hafidi, Ph. Preux, E-G. Talbi, Vers
la coopération de métaheuristiques parallèles, Calculateurs
Parallèles, Réseaux et Systèmes Répartis, 10(2),
211-223, Avril 1998
(pdf)
Ph. Preux, D. Robilliard, C. Fonlupt, "Fitness Landscape
Of Combinatorial Problems And The Performance Of Local Search Algorithms",
Rapport interne LIL-97-13, Nov 1997
(pdf)
C. Fonlupt, D. Robilliard, Ph. Preux, "Fitness Landscape
and the Behavior of Heuristics", Proc. Evolution Artificielle'97
(pdf)
B. Cuvelier, C. Cambier, Ph. Preux,
Studying adaptation with Echo,
European
Conference on Artificial Life (ECAL'97), Aug. 97
(pdf)
C. Fonlupt, D. Robilliard, Ph. Preux "Preventing
Premature Convergence via Cooperating Genetic Algorithms" Proc. Mandel'97,
Brno, Czeck Republic, June 1997
(pdf)
V. Bachelet, Ph. Preux, E-G. Talbi, "The Landscape
of the Quadratic Assignment Problem and Local Search Methods", (1 page)
Tenth Meeting of the European Chapter on Combinatorial Optimization, Teneriffe,
Canary Islands, May 1997
(pdf)
Ph. Preux, D. Robilliard, C. Fonlupt "Fitness Landscape
And The Performance Of Local Search Algorithms", (1 page) Tenth Meeting
of the European Chapter on Combinatorial Optimization, Teneriffe, Canary
Islands, May 1997
(pdf)
C. Cambier, E. Perrier, J-P. Treuil, Ph. Preux, "Action
Physique et géométrique. Contribution a une reflexion sur
l'utilisation des processus physiques. Application RIVAGE", Poster aux
Journées Francaise IAD et SMA, Sophia-Antipolis, France, Avril 1997
C. Fonlupt, Ph. Preux, E-G. Talbi, "Paysages adaptatifs
des problemes NP-durs et performance des meta-heuristiques", (in French)
Feb. 97
D. Duvivier, Ph. Preux, C. Fonlupt, D. Robiliard,
E-G. Talbi, "The fitness function and its impact on Local Search Methods",
Rapport interne LIL-97-4, Fév. 97, mis à jour Sep. 97
(pdf)
C. Fonlupt, D. Robilliard, Ph. Preux, "Some Results
on the structure of the TSP and its Search Space", Technical report LIL-97-3,
Jan 97
C. Fonlupt, D. Robilliard, Ph. Preux, "A comparison
of the 2-opt-move and the city-swap operators for the TSP", Technical report
LIL-97-2, Jan. 1997
D. Duvivier, Ph. Preux, E-G. Talbi, "Climbing-Up
NP-Hard Hills", Proc. Parallel Problem Solving from Nature'96,
Springer-Verlag, Lecture Notes in Computer Science, Berlin, Sep. 1996
(pdf)
(© Springer-Verlag)
V. Bachelet, Ph. Preux, E-G. Talbi, "Parallel Hybrid
Meta-Heuristics: Application to the Quadratic Assignment Problem", Proc.
Parallel Optimization Colloquium, Versailles, Mar. 1996
(pdf)
D. Duvivier, Ph. Preux, E-G. Talbi, "Genetic Algorithms
Applied to the Job-shop Scheduling Problem", Proc. FUCAM'96, Mons, Belgique,
Sep. 1996 (pdf)
D. Duvivier, Ph. Preux, E-G. Talbi, "Algorithmes
génétiques parallèles pour l'optimisation : application aux problèmes de
job-shop et d'affectation quadratique", Proc. Francoro'95, Mons, Belgique,
Jun. 1995
D. Duvivier, Ph. Preux, E-G. Talbi, "Parallel
Genetic Algorithms for Optimization and Application to NP-Complete Problem
Solving", Proc. CCS'95, Brest, France, Jui. 1995
Ph. Preux, E-G. Talbi, "Assessing the Evolutionary
Algorithm Paradigm to Solve Hard Problems", Technical Report LIL-95-4,
(pdf)
Ph. Preux, E-G. Talbi, "Assessing the Evolutionary
Algorithm Paradigm to Solve Hard Problems", Proc. Workshop on Studying
and Solving Really Hard Problems, Constraint Processing'95, Marseille,
(Sep. 1995) This is a summary of pub. LIL-95-4
(pdf)
D. Duvivier, Ph. Preux, E-G. Talbi, "Stochastic Algorithms
for Optimization and Application to Job-Shop-Scheduling", Technical Report
LIL-96-5, Sep 1995
(pdf)
Ph. Preux, "Etude de l'uniformisation de la population
des algorithmes génétiques", (in French) Proc. Evolution Artificielle'94,
Toulouse (in French), (Sep. 94)
(pdf)
Ph. Preux, "A study of population uniformization
in GAs" Proc. of the workshop on applied genetic and other evolutionary
techniques, ECAI'94, Amsterdam, The Netherlands (Aug 1994)
(pdf)
Ph. Preux, "Les algorithmes évolutifs", (in French)
Technical report LIL-94-1, Second edition (oct. 95)
(pdf)
While working on my PhD and a bit later, I was with the Laboratoire d'Informatique Fondamentale de Lille, at the Université de Lille 1. There, I studied vector supercomputers, their architecture, and supercompilers (compilers for supercomputers). Below, there is the list of publications related to this phase of my life. I've stopped working on these things for a very long time... These are not available on this page.
J-L. Dekeyser, Ph. Marquet, Ph. Preux, "Load-Store
Dependence and Data-Parallel Code Generation", CONPAR 92/VAPP V,
pp. 805--806 L. Bouge, M. Cosnard, Y. Robert, D. Trystram (eds), 1992,
Lyon, France, Springer-Verlag, Lecture Notes in Computer Science, vol 634
J-L. Dekeyser, Ph. Marquet, Ph. Preux, "A Multi-Level
Environment for Data-Parallel Code Generation", Proc. European Workshops
on Parallel Computing, 1992, Wouter Joosen, Elie Milgrom (eds), pp. 252--255,
IOS Publisher, Barcelona, Spain
M.T. Kechadi, -L. Dekeyser, Ph. Marquet, Ph. Preux, "Performance improvement for vector pipeline multiprocessor systems using a disordered execution model", poster at the ISCA, 1992, Australia, ACM SIGARCH News, 20(2), pp. 433
J-L. Dekeyser, M. Tahar Kechadi, Ph. Marquet, Ph.
Preux, "Disordered Vector Pipelined Processor", Proc. ISMM Workshop on
Parallel Computing, pp. 36--39, 1991 Trani, Italie
J-L. Dekeyser, Ph. Marquet, Ph. Preux, "PARTNER:
An Environment for Parallel Scientific Computing", Proc. ISMM Workshop
on Parallel Computing, pp. 288--291, Trani, Italie, 1991
J-L. Dekeyser, Ph. Marquet, Ph. Preux, "LSD2: An
Embedded Language for Massively Parallel and Vector Pipeline Programming",
Proc. Parallel Computing'91, London
Ph. Preux, MAD : une machine virtuelle vectorielle - Conséquences sur les architectures vectorielles, PhD dissertation, Lille, Jan 1991
J-L. Dekeyser, Ph. Marquet, Ph. Preux, "DEVIL: An
Intermediate Vector Language - Definition and Implementation", Proc.
Int'l Workshop on Compilers for Parallel Computers, 1990, pp. 273--284,
Paris
J-L. Dekeyser, Ph. Marquet, Ph. Preux, Vector Addressing Processor for Direct and Indirect Accesses, Microprocessing and Microprogramming,
29(1), 657:664, 1990
J-L. Dekeyser, Ph. Marquet, Ph. Preux, EVA: an Explicit Vector lAnguage. An Alternative Language to Fortran 90 (former 8x), ACM SIGPLAN Notices, 25(8)52:71, Aug. 1990
Paris
J-L. Dekeyser, Ph. Marquet, Ph. Preux, "EVA: An Explicit
Vector Language", Proc. 10 SCCC Int'l Conf. on Computer Science, 1990,
Santiago, Chili, pp. 233--244
J-L. Dekeyser, Ph. Preux, "Indirect Memory Decoding
for Vector Accesses", Proc. of the 1989 Int'l Symp. on Computer Architecture
and Digital Signal Processing, 1989, pp. 293--298, Hong-Kong