PGP-mc: Towards a Multicore Parallel Approach for Mining Gradual Patterns. - Anne Laurent; Benjamin Négrevergne; Nicolas Sicard; Alexandre Termier (DASFAA (1), 2010)

PGP-mc : extraction parallèle efficace de motifs graduels. - Anne Laurent; Benjamin Négrevergne; Nicolas Sicard; Alexandre Termier (EGC, 2010)

Efficient Parallel Mining of Gradual Patterns on Multicore Processors. - Anne Laurent; Benjamin Négrevergne; Nicolas Sicard; Alexandre Termier (EGC (best of volume), 2010)

Découverte d'itemsets fréquents fermés sur architecture multicoeurs. - Benjamin Négrevergne; Jean-François Méhaut; Alexandre Termier; Takeaki Uno (EGC, 2010)

Discovering closed frequent itemsets on multicore: Parallelizing computations and optimizing memory accesses. - Benjamin Négrevergne; Alexandre Termier; Jean-François Méhaut; Takeaki Uno (HPCS, 2010)

Un algorithme de fouille de données générique et parallèle pour architecture multi-coeurs. (A generic and parallel pattern mining algorithm for multi-core architectures). - Benjamin Négrevergne (2011)

Dominance Programming for Itemset Mining. - Benjamin Négrevergne; Anton Dries; Tias Guns; Siegfried Nijssen (ICDM, 2013)

Para Miner: a generic pattern mining algorithm for multi-core architectures. - Benjamin Négrevergne; Alexandre Termier; Marie-Christine Rousset; Jean-François Méhaut (Data Min. Knowl. Discov., 2014)

Constraint-Based Sequence Mining Using Constraint Programming. - Benjamin Négrevergne; Tias Guns (CPAIOR, 2015)

PGLCM: efficient parallel mining of closed frequent gradual itemsets. - Trong Dinh Thac Do; Alexandre Termier; Anne Laurent; Benjamin Négrevergne; Behrooz Omidvar-Tehrani; Sihem Amer-Yahia (Knowl. Inf. Syst., 2015)

On Declarative Modeling of Structured Pattern Mining. - Tias Guns; Sergey Paramonov 001; Benjamin Négrevergne (AAAI Workshop: Declarative Learning Based Programming, 2016)

Detecting Strategic Moves in HearthStone Matches. - Boris Doux; Clément Gautrais; Benjamin Négrevergne (MLSA@PKDD/ECML, 2016)

A SAT model to mine flexible sequences in transactional datasets. - Rémi Coletta; Benjamin Négrevergne (CoRR, 2016)

Modeling in MiningZinc. - Anton Dries; Tias Guns; Siegfried Nijssen; Behrouz Babaki; Thanh Le Van; Benjamin Négrevergne; Sergey Paramonov 001; Luc De Raedt (Data Mining and Constraint Programming, 2016)

Recognizing Art Style Automatically in Painting with Deep Learning. - Adrian Lecoutre; Benjamin Négrevergne; Florian Yger (ACML, 2017)

Expert Opinion Extraction from a Biomedical Database. - Ahmed Samet; Thomas Guyet; Benjamin Négrevergne; Tien-Tuan Dao; Tuan Nha Hoang; Marie Christine Ho Ba Tho (ECSQARU, 2017)

Distributed Nested Rollout Policy for SameGame. - Benjamin Négrevergne; Tristan Cazenave (CGW@IJCAI, 2017)

Mining Rare Sequential Patterns with ASP. - Ahmed Samet; Thomas Guyet; Benjamin Négrevergne (ILP (Late Breaking Papers), 2017)

Training Compact Deep Learning Models for Video Classification Using Circulant Matrices. - Alexandre Araujo; Benjamin Négrevergne; Yann Chevaleyre; Jamal Atif (ECCV Workshops (4), 2018)

Fouille de Motifs Graduels Fermés Fréquents Sous Contrainte de la Temporalité. - Jerry Lonlac; Benjamin Négrevergne; Yannick Miras; Aude Beauger; Engelbert Mephu Nguifo (EGC, 2018)

On the Expressive Power of Deep Fully Circulant Neural Networks. - Alexandre Araujo; Benjamin Négrevergne; Yann Chevaleyre; Jamal Atif (CoRR, 2019)

Robust Neural Networks using Randomized Adversarial Training. - Alexandre Araujo; Rafael Pinot; Benjamin Négrevergne; Laurent Meunier; Yann Chevaleyre; Florian Yger; Jamal Atif (CoRR, 2019)

Understanding and Training Deep Diagonal Circulant Neural Networks. - Alexandre Araujo; Benjamin Négrevergne; Yann Chevaleyre; Jamal Atif (ECAI, 2020)

Fréchet Mean Computation in Graph Space through Projected Block Gradient Descent. - Nicolas Boria; Benjamin Négrevergne; Florian Yger (ESANN, 2020)

Monte Carlo Graph Coloring. - Tristan Cazenave; Benjamin Négrevergne; Florian Sikora (MCS@IJCAI, 2020)

Advocating for Multiple Defense Strategies Against Adversarial Examples. - Alexandre Araujo; Laurent Meunier; Rafael Pinot; Benjamin Négrevergne (PKDD/ECML Workshops, 2020)

Fast & Accurate Method for Bounding the Singular Values of Convolutional Layers with Application to Lipschitz Regularization. - Alexandre Araujo; Benjamin Négrevergne; Yann Chevaleyre; Jamal Atif (CoRR, 2020)

On Lipschitz Regularization of Convolutional Layers using Toeplitz Matrix Theory. - Alexandre Araujo; Benjamin Négrevergne; Yann Chevaleyre; Jamal Atif (AAAI, 2021)

Deep Reinforcement Learning for Morpion Solitaire. - Boris Doux; Benjamin Négrevergne; Tristan Cazenave (ACG, 2021)

On the expressivity of bi-Lipschitz normalizing flows. - Alexandre Verine; Benjamin Négrevergne; Yann Chevaleyre; Fabrice Rossi (ACML, 2022)

On the Role of Randomization in Adversarially Robust Classification. - Lucas Gnecco Heredia; Muni Sreenivas Pydi; Laurent Meunier; Benjamin Négrevergne; Yann Chevaleyre (NeurIPS, 2023)

Precision-Recall Divergence Optimization for Generative Modeling with GANs and Normalizing Flows. - Alexandre Verine; Benjamin Négrevergne; Muni Sreenivas Pydi; Yann Chevaleyre (NeurIPS, 2023)

Training Normalizing Flows with the Precision-Recall Divergence. - Alexandre Verine; Benjamin Négrevergne; Muni Sreenivas Pydi; Yann Chevaleyre (CoRR, 2023)

Randomization for adversarial robustness: the Good, the Bad and the Ugly. - Lucas Gnecco Heredia; Yann Chevaleyre; Benjamin Négrevergne; Laurent Meunier (CoRR, 2023)

Adversarial attacks for mixtures of classifiers. - Lucas Gnecco Heredia; Benjamin Négrevergne; Yann Chevaleyre (CoRR, 2023)

Exploring Precision and Recall to assess the quality and diversity of LLMs. - Florian Le Bronnec; Alexandre Verine; Benjamin Négrevergne; Yann Chevaleyre; Alexandre Allauzen (ACL (1), 2024)

Optimal Budgeted Rejection Sampling for Generative Models. - Alexandre Verine; Muni Sreenivas Pydi; Benjamin Négrevergne; Yann Chevaleyre (AISTATS, 2024)

What Makes Large Language Models Reason in (Multi-Turn) Code Generation? - Kunhao Zheng; Juliette Decugis; Jonas Gehring; Taco Cohen; Benjamin Négrevergne; Gabriel Synnaeve (CoRR, 2024)

Unveiling the Role of Randomization in Multiclass Adversarial Classification: Insights from Graph Theory. - Lucas Gnecco Heredia; Matteo Sammut; Muni Sreenivas Pydi; Rafael Pinot; Benjamin Négrevergne; Yann Chevaleyre (AISTATS, 2025)

Improving Discriminator Guidance in Diffusion Models. - Alexandre Verine; Mehdi Inane; Florian Le Bronnec; Benjamin Négrevergne; Yann Chevaleyre (CoRR, 2025)

Lattice Climber Attack: Adversarial attacks for randomized mixtures of classifiers. - Lucas Gnecco Heredia; Benjamin Négrevergne; Yann Chevaleyre (CoRR, 2025)

Improving Diversity in Language Models: When Temperature Fails, Change the Loss. - Alexandre Verine; Florian Le Bronnec; Kunhao Zheng; Alexandre Allauzen; Yann Chevaleyre; Benjamin Négrevergne (CoRR, 2025)