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ORCIDBenjamin Négrevergne
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2020 – today
- 2024
[c25]Florian Le Bronnec, Alexandre Verine, Benjamin Négrevergne, Yann Chevaleyre, Alexandre Allauzen:
Exploring Precision and Recall to assess the quality and diversity of LLMs. ACL (1) 2024: 11418-11441- [c24]Alexandre Verine, Muni Sreenivas Pydi, Benjamin Négrevergne, Yann Chevaleyre:
Optimal Budgeted Rejection Sampling for Generative Models. AISTATS 2024: 3367-3375 - [i16]Florian Le Bronnec, Alexandre Verine, Benjamin Négrevergne, Yann Chevaleyre, Alexandre Allauzen:
Exploring Precision and Recall to assess the quality and diversity of LLMs. CoRR abs/2402.10693 (2024) - [i15]Kunhao Zheng, Juliette Decugis, Jonas Gehring, Taco Cohen, Benjamin Négrevergne, Gabriel Synnaeve:
What Makes Large Language Models Reason in (Multi-Turn) Code Generation? CoRR abs/2410.08105 (2024) - 2023
- [c23]Lucas Gnecco Heredia, Muni Sreenivas Pydi, Laurent Meunier, Benjamin Négrevergne, Yann Chevaleyre:
On the Role of Randomization in Adversarially Robust Classification. NeurIPS 2023 - [c22]Alexandre Verine, Benjamin Négrevergne, Muni Sreenivas Pydi, Yann Chevaleyre:
Precision-Recall Divergence Optimization for Generative Modeling with GANs and Normalizing Flows. NeurIPS 2023 - [i14]Alexandre Verine, Benjamin Négrevergne, Muni Sreenivas Pydi, Yann Chevaleyre:
Training Normalizing Flows with the Precision-Recall Divergence. CoRR abs/2302.00628 (2023) - [i13]Lucas Gnecco Heredia, Yann Chevaleyre, Benjamin Négrevergne, Laurent Meunier:
Randomization for adversarial robustness: the Good, the Bad and the Ugly. CoRR abs/2302.07221 (2023) - [i12]Alexandre Verine, Benjamin Négrevergne, Muni Sreenivas Pydi, Yann Chevaleyre:
Precision-Recall Divergence Optimization for Generative Modeling with GANs and Normalizing Flows. CoRR abs/2305.18910 (2023) - [i11]Lucas Gnecco Heredia, Benjamin Négrevergne, Yann Chevaleyre:
Adversarial attacks for mixtures of classifiers. CoRR abs/2307.10788 (2023) - [i10]Alexandre Verine, Muni Sreenivas Pydi, Benjamin Négrevergne, Yann Chevaleyre:
Optimal Budgeted Rejection Sampling for Generative Models. CoRR abs/2311.00460 (2023) - 2022
- [c21]Alexandre Verine, Benjamin Négrevergne, Yann Chevaleyre, Fabrice Rossi:
On the expressivity of bi-Lipschitz normalizing flows. ACML 2022: 1054-1069 - 2021
- [c20]Alexandre Araujo, Benjamin Négrevergne, Yann Chevaleyre, Jamal Atif:
On Lipschitz Regularization of Convolutional Layers using Toeplitz Matrix Theory. AAAI 2021: 6661-6669 - [c19]Boris Doux, Benjamin Négrevergne, Tristan Cazenave:
Deep Reinforcement Learning for Morpion Solitaire. ACG 2021: 14-26 - [i9]Alexandre Verine, Benjamin Négrevergne, Fabrice Rossi, Yann Chevaleyre:
On the expressivity of bi-Lipschitz normalizing flows. CoRR abs/2107.07232 (2021) - 2020
- [c18]Alexandre Araujo
, Benjamin Négrevergne, Yann Chevaleyre, Jamal Atif:
Understanding and Training Deep Diagonal Circulant Neural Networks. ECAI 2020: 945-952 - [c17]Nicolas Boria, Benjamin Négrevergne, Florian Yger:
Fréchet Mean Computation in Graph Space through Projected Block Gradient Descent. ESANN 2020: 193-198 - [c16]Alexandre Araujo, Laurent Meunier, Rafael Pinot, Benjamin Négrevergne:
Advocating for Multiple Defense Strategies Against Adversarial Examples. PKDD/ECML Workshops 2020: 165-177 - [i8]Alexandre Araujo, Benjamin Négrevergne, Yann Chevaleyre, Jamal Atif:
Fast & Accurate Method for Bounding the Singular Values of Convolutional Layers with Application to Lipschitz Regularization. CoRR abs/2006.08391 (2020) - [i7]Alexandre Araujo, Laurent Meunier, Rafael Pinot, Benjamin Négrevergne:
Advocating for Multiple Defense Strategies against Adversarial Examples. CoRR abs/2012.02632 (2020)
2010 – 2019
- 2019
- [i6]Alexandre Araujo, Benjamin Négrevergne, Yann Chevaleyre, Jamal Atif:
On the Expressive Power of Deep Fully Circulant Neural Networks. CoRR abs/1901.10255 (2019) - [i5]Alexandre Araujo, Rafael Pinot, Benjamin Négrevergne, Laurent Meunier, Yann Chevaleyre, Florian Yger, Jamal Atif:
Robust Neural Networks using Randomized Adversarial Training. CoRR abs/1903.10219 (2019) - 2018
- [c15]Alexandre Araujo, Benjamin Négrevergne, Yann Chevaleyre, Jamal Atif:
Training Compact Deep Learning Models for Video Classification Using Circulant Matrices. ECCV Workshops (4) 2018: 271-286 - [c14]Jerry Lonlac, Benjamin Négrevergne, Yannick Miras, Aude Beauger, Engelbert Mephu Nguifo:
Fouille de Motifs Graduels Fermés Fréquents Sous Contrainte de la Temporalité. EGC 2018: 383-384 - [i4]Alexandre Araujo, Benjamin Négrevergne, Yann Chevaleyre, Jamal Atif:
Training compact deep learning models for video classification using circulant matrices. CoRR abs/1810.01140 (2018) - 2017
- [c13]Adrian Lecoutre, Benjamin Négrevergne, Florian Yger:
Recognizing Art Style Automatically in Painting with Deep Learning. ACML 2017: 327-342 - [c12]Ahmed Samet, Thomas Guyet, Benjamin Négrevergne, Tien-Tuan Dao, Tuan Nha Hoang, Marie Christine Ho Ba Tho:
Expert Opinion Extraction from a Biomedical Database. ECSQARU 2017: 135-145 - [c11]Benjamin Négrevergne, Tristan Cazenave:
Distributed Nested Rollout Policy for SameGame. CGW@IJCAI 2017: 108-120 - [c10]Ahmed Samet, Thomas Guyet, Benjamin Négrevergne:
Mining Rare Sequential Patterns with ASP. ILP (Late Breaking Papers) 2017: 51-60 - [i3]Ahmed Samet, Thomas Guyet, Benjamin Négrevergne, Tien-Tuan Dao, Tuan Nha Hoang, Marie Christine Ho Ba Tho:
Expert Opinion Extraction from a Biomedical Database. CoRR abs/1709.03270 (2017) - 2016
- [c9]Tias Guns, Sergey Paramonov, Benjamin Négrevergne:
On Declarative Modeling of Structured Pattern Mining. AAAI Workshop: Declarative Learning Based Programming 2016 - [c8]Boris Doux, Clément Gautrais, Benjamin Négrevergne:
Detecting Strategic Moves in HearthStone Matches. MLSA@PKDD/ECML 2016 - [p1]Anton Dries, Tias Guns, Siegfried Nijssen, Behrouz Babaki, Thanh Le Van, Benjamin Négrevergne, Sergey Paramonov, Luc De Raedt:
Modeling in MiningZinc. Data Mining and Constraint Programming 2016: 257-281 - [i2]Rémi Coletta, Benjamin Négrevergne:
A SAT model to mine flexible sequences in transactional datasets. CoRR abs/1604.00300 (2016) - 2015
- [j2]Trong Dinh Thac Do, Alexandre Termier, Anne Laurent, Benjamin Négrevergne, Behrooz Omidvar-Tehrani, Sihem Amer-Yahia:
PGLCM: efficient parallel mining of closed frequent gradual itemsets. Knowl. Inf. Syst. 43(3): 497-527 (2015) - [c7]Benjamin Négrevergne, Tias Guns:
Constraint-Based Sequence Mining Using Constraint Programming. CPAIOR 2015: 288-305 - [i1]Benjamin Négrevergne, Tias Guns:
Constraint-based sequence mining using constraint programming. CoRR abs/1501.01178 (2015) - 2014
- [j1]Benjamin Négrevergne, Alexandre Termier, Marie-Christine Rousset, Jean-François Méhaut:
Para Miner: a generic pattern mining algorithm for multi-core architectures. Data Min. Knowl. Discov. 28(3): 593-633 (2014) - 2013
- [c6]Benjamin Négrevergne, Anton Dries, Tias Guns, Siegfried Nijssen:
Dominance Programming for Itemset Mining. ICDM 2013: 557-566 - 2011
- [b1]Benjamin Négrevergne:
Un algorithme de fouille de données générique et parallèle pour architecture multi-coeurs. (A generic and parallel pattern mining algorithm for multi-core architectures). Grenoble Alpes University, France, 2011 - 2010
- [c5]Anne Laurent, Benjamin Négrevergne, Nicolas Sicard, Alexandre Termier:
PGP-mc: Towards a Multicore Parallel Approach for Mining Gradual Patterns. DASFAA (1) 2010: 78-84 - [c4]Anne Laurent, Benjamin Négrevergne, Nicolas Sicard, Alexandre Termier:
Efficient Parallel Mining of Gradual Patterns on Multicore Processors. EGC (best of volume) 2010: 137-151 - [c3]Anne Laurent, Benjamin Négrevergne, Nicolas Sicard, Alexandre Termier:
PGP-mc : extraction parallèle efficace de motifs graduels. EGC 2010: 453-464 - [c2]Benjamin Négrevergne, Jean-François Méhaut, Alexandre Termier, Takeaki Uno:
Découverte d'itemsets fréquents fermés sur architecture multicoeurs. EGC 2010: 465-470 - [c1]Benjamin Négrevergne, Alexandre Termier, Jean-François Méhaut, Takeaki Uno:
Discovering closed frequent itemsets on multicore: Parallelizing computations and optimizing memory accesses. HPCS 2010: 521-528
Coauthor Index
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last updated on 2024-11-19 20:49 CET by the dblp team
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