Philippe Preux

Orcid: 0000-0002-2067-2838

According to our database1, Philippe Preux authored at least 97 papers between 1990 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
General System Architecture and COTS Prototyping of an AIoT-Enabled Sailboat for Autonomous Aquatic Ecosystem Monitoring.
IEEE Internet Things J., February, 2024

Augmenting Ad-Hoc IR Dataset for Interactive Conversational Search.
Trans. Mach. Learn. Res., 2024

Interpretable and Editable Programmatic Tree Policies for Reinforcement Learning.
CoRR, 2024

Towards a Research Community in Interpretable Reinforcement Learning: the InterpPol Workshop.
CoRR, 2024

PAQA: Toward ProActive Open-Retrieval Question Answering.
CoRR, 2024

Reinforcement-learning robotic sailboats: simulator and preliminary results.
CoRR, 2024

PAQA: Vers des systèmes ProActifs face aux Questions Ambiguës.
Proceedings of the COnférence en Recherche d'Informations et Applications, 2024

Statistical comparison in empirical computer science with minimal computation usage.
Proceedings of the 2nd ACM Conference on Reproducibility and Replicability, 2024

2023
Discovering the Interpretability-Performance Pareto Front of Decision Trees with Dynamic Programming.
CoRR, 2023

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.
CoRR, 2023

AdaStop: sequential testing for efficient and reliable comparisons of Deep RL Agents.
CoRR, 2023

Optimal Interpretability-Performance Trade-off of Classification Trees with Black-Box Reinforcement Learning.
CoRR, 2023

Augmentation de jeux de données RI pour la recherche conversationnelle à initiative mixte.
Proceedings of the Actes de CORIA-TALN 2023. Actes de la 18e Conférence en Recherche d'Information et Applications, 2023

Soft Action Priors: Towards Robust Policy Transfer.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Entropy Regularized Reinforcement Learning with Cascading Networks.
CoRR, 2022

gym-DSSAT: a crop model turned into a Reinforcement Learning environment.
CoRR, 2022

Reinforcement learning for crop management support: Review, prospects and challenges.
Comput. Electron. Agric., 2022

Automated Planning for Robotic Guidewire Navigation in the Coronary Arteries.
Proceedings of the 5th IEEE International Conference on Soft Robotics, 2022

2021
More Efficient Exploration with Symbolic Priors on Action Sequence Equivalences.
CoRR, 2021

Low-Rank Projections of GCNs Laplacian.
CoRR, 2021

Interferometric Graph Transform for Community Labeling.
CoRR, 2021

There Is No Turning Back: A Self-Supervised Approach for Reversibility-Aware Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Don't Do What Doesn't Matter: Intrinsic Motivation with Action Usefulness.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Learning Value Functions in Deep Policy Gradients using Residual Variance.
Proceedings of the 9th International Conference on Learning Representations, 2021

Adversarially Guided Actor-Critic.
Proceedings of the 9th International Conference on Learning Representations, 2021

READYS: A Reinforcement Learning Based Strategy for Heterogeneous Dynamic Scheduling.
Proceedings of the IEEE International Conference on Cluster Computing, 2021

2020
Is Standard Deviation the New Standard? Revisiting the Critic in Deep Policy Gradients.
CoRR, 2020

Geometric deep reinforcement learning for dynamic DAG scheduling.
Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

A Machine of Few Words: Interactive Speaker Recognition with Reinforcement Learning.
Proceedings of the 21st Annual Conference of the International Speech Communication Association, 2020

"I'm Sorry Dave, I'm Afraid I Can't Do That" Deep Q-Learning from Forbidden Actions.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Only Relevant Information Matters: Filtering Out Noisy Samples To Boost RL.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

2019
"I'm sorry Dave, I'm afraid I can't do that" Deep Q-learning from forbidden action.
CoRR, 2019

High-Dimensional Control Using Generalized Auxiliary Tasks.
CoRR, 2019

Samples are not all useful: Denoising policy gradient updates using variance.
CoRR, 2019

Energy Management for Microgrids: a Reinforcement Learning Approach.
Proceedings of the 2019 IEEE PES Innovative Smart Grid Technologies Europe, 2019

2018
Correctness attraction: a study of stability of software behavior under runtime perturbation.
Empir. Softw. Eng., 2018

Recurrent Neural Networks for Long and Short-Term Sequential Recommendation.
CoRR, 2018

Visual Reasoning with Multi-hop Feature Modulation.
Proceedings of the Computer Vision - ECCV 2018, 2018

2017
A large-scale study of call graph-based impact prediction using mutation testing.
Softw. Qual. J., 2017

A Multi-Armed Bandit Model Selection for Cold-Start User Recommendation.
Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization, 2017

A Generative Model for Sparse, Evolving Digraphs.
Proceedings of the Complex Networks & Their Applications VI, 2017

2016
Consistent Algorithms for Clustering Time Series.
J. Mach. Learn. Res., 2016

Operator-valued Kernels for Learning from Functional Response Data.
J. Mach. Learn. Res., 2016

Exploiting Social Information in Pairwise Preference Recommender System.
J. Inf. Data Manag., 2016

Mutation-Based Graph Inference for Fault Localization.
Proceedings of the 16th IEEE International Working Conference on Source Code Analysis and Manipulation, 2016

Scalable Explore-Exploit Collaborative filtering.
Proceedings of the 20th Pacific Asia Conference on Information Systems, 2016

Large-Scale Bandit Recommender System.
Proceedings of the Machine Learning, Optimization, and Big Data, 2016

Preference-Like Score to Cope with Cold-Start User in Recommender Systems.
Proceedings of the 28th IEEE International Conference on Tools with Artificial Intelligence, 2016

A learning algorithm for change impact prediction.
Proceedings of the 5th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering, 2016

Sequential Collaborative Ranking Using (No-)Click Implicit Feedback.
Proceedings of the Neural Information Processing - 23rd International Conference, 2016

2015
A Learning Algorithm for Change Impact Prediction: Experimentation on 7 Java Applications.
CoRR, 2015

Bandits and Recommender Systems.
Proceedings of the Machine Learning, Optimization, and Big Data, 2015

An Experimental Protocol for Analyzing the Accuracy of Software Error Impact Analysis.
Proceedings of the 10th IEEE/ACM International Workshop on Automation of Software Test, 2015

Simultaneous optimistic optimization on the noiseless BBOB testbed.
Proceedings of the IEEE Congress on Evolutionary Computation, 2015

2014
Cold-start Problems in Recommendation Systems via Contextual-bandit Algorithms.
CoRR, 2014

A Generative Model of Software Dependency Graphs to Better Understand Software Evolution.
CoRR, 2014

Bandits Warm-up Cold Recommender Systems.
CoRR, 2014

Understanding software evolution: the maisqual ant data set.
Proceedings of the 11th Working Conference on Mining Software Repositories, 2014

Improving offline evaluation of contextual bandit algorithms via bootstrapping techniques.
Proceedings of the 31th International Conference on Machine Learning, 2014

De l'ombre à la lumière : plus de visibilité sur l'Eclipse.
Proceedings of the 14èmes Journées Francophones Extraction et Gestion des Connaissances, 2014

Bandits attack function optimization.
Proceedings of the IEEE Congress on Evolutionary Computation, 2014

2013
Multiple functional regression with both discrete and continuous covariates
CoRR, 2013

Functional Regularized Least Squares Classi cation with Operator-valued Kernels
CoRR, 2013

A Generalized Kernel Approach to Structured Output Learning.
Proceedings of the 30th International Conference on Machine Learning, 2013

2012
Sequential approaches for learning datum-wise sparse representations.
Mach. Learn., 2012

ICML Exploration & Exploitation Challenge: Keep it simple!
Proceedings of the Workshop on On-line Trading of Exploration and Exploitation 2, 2012

Online Clustering of Processes.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Managing advertising campaigns - an approximate planning approach.
Frontiers Comput. Sci., 2012

Fast Reinforcement Learning with Large Action Sets Using Error-Correcting Output Codes for MDP Factorization.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

Multiple Operator-valued Kernel Learning.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

2011
Datum-Wise Classification: A Sequential Approach to Sparsity.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

Functional Regularized Least Squares Classication with Operator-valued Kernels.
Proceedings of the 28th International Conference on Machine Learning, 2011

Learning vocal tract variables with multi-task kernels.
Proceedings of the IEEE International Conference on Acoustics, 2011

2010
Nonlinear functional regression: a functional RKHS approach.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

The Iso-regularization Descent Algorithm for the LASSO.
Proceedings of the Neural Information Processing. Theory and Algorithms, 2010

Advertising Campaigns Management: Should We Be Greedy?
Proceedings of the ICDM 2010, 2010

Affichage de publicités sur des portails web.
Proceedings of the Extraction et gestion des connaissances (EGC'2010), 2010

2009
ECON: A Kernel Basis Pursuit Algorithm with Automatic Feature Parameter Tuning, and its Application to Photometric Solids Approximation.
Proceedings of the International Conference on Machine Learning and Applications, 2009

Feature discovery in approximate dynamic programming.
Proceedings of the IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, 2009

2008
Basis Function Construction in Reinforcement Learning Using Cascade-Correlation Learning Architecture.
Proceedings of the Seventh International Conference on Machine Learning and Applications, 2008

Basis Expansion in Natural Actor Critic Methods.
Proceedings of the Recent Advances in Reinforcement Learning, 8th European Workshop, 2008

Feature Discovery in Reinforcement Learning Using Genetic Programming.
Proceedings of the Genetic Programming, 11th European Conference, 2008

2007
A unified view of TD algorithms, introducing Full-gradient TD and Equi-gradient descent TD.
Proceedings of the 15th European Symposium on Artificial Neural Networks, 2007

2006
A Unified View of TD Algorithms; Introducing Full-Gradient TD and Equi-Gradient Descent TD
CoRR, 2006

2004
A generic architecture for adaptive agents based on reinforcement learning.
Inf. Sci., 2004

2003
"Virtual laboratory environment" (VLE): a software environment oriented agent and object for modeling and simulation of complex systems.
Simul. Model. Pract. Theory, 2003

2002
Propagation of Q-values in Tabular TD(lambda).
Proceedings of the Machine Learning: ECML 2002, 2002

2001
Selection of Behavior in Social Situations.
Proceedings of the Applications of Evolutionary Computing, 2001

Learning as a Consequence of Selection.
Proceedings of the Artificial Evolution, 2001

2000
Virtual Laboratory Environment (VLE) : un environnement multi-agents pour la modélisation et la simulation d'écosystèmes (démonstration).
Proceedings of the Systèmes multi-agents : Méthodologie, technologie et expériences - JFIADSMA 00, 2000

1999
Evolution of Cooperation within a Behavior-Based Perspective: Confronting Nature and Animats.
Proceedings of the Artificial Evolution, 4th European Conference, 1999

1998
The fitness function and its impact on local search methods.
Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, 1998

A Bit-Wise Epistasis Measure for Binary Search Spaces.
Proceedings of the Parallel Problem Solving from Nature, 1998

1996
Climbing Up NP-Hard Hills.
Proceedings of the Parallel Problem Solving from Nature, 1996

1992
Performance improvement for vector pipeline multiprocessor systems using a disordered execution model.
Proceedings of the 19th Annual International Symposium on Computer Architecture. Gold Coast, 1992

1990
EVA: an explicit vector language.
ACM SIGPLAN Notices, 1990

Vector addressing processor for direct and indirect accesses.
Microprocessing and Microprogramming, 1990


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