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Alexandre Araujo
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2020 – today
- 2024
- [c17]Blaise Delattre, Alexandre Araujo, Quentin Barthélemy, Alexandre Allauzen:
The Lipschitz-Variance-Margin Tradeoff for Enhanced Randomized Smoothing. ICLR 2024 - [c16]Sara Ghazanfari, Alexandre Araujo, Prashanth Krishnamurthy, Farshad Khorrami, Siddharth Garg:
LipSim: A Provably Robust Perceptual Similarity Metric. ICLR 2024 - [c15]Patricia Pauli, Aaron J. Havens, Alexandre Araujo, Siddharth Garg, Farshad Khorrami, Frank Allgöwer, Bin Hu:
Novel Quadratic Constraints for Extending LipSDP beyond Slope-Restricted Activations. ICLR 2024 - [c14]Zi Wang, Bin Hu, Aaron J. Havens, Alexandre Araujo, Yang Zheng, Yudong Chen, Somesh Jha:
On the Scalability and Memory Efficiency of Semidefinite Programs for Lipschitz Constant Estimation of Neural Networks. ICLR 2024 - [c13]Aaron J. Havens, Alexandre Araujo, Huan Zhang, Bin Hu:
Fine-grained Local Sensitivity Analysis of Standard Dot-Product Self-Attention. ICML 2024 - [i21]Patricia Pauli, Aaron J. Havens, Alexandre Araujo, Siddharth Garg, Farshad Khorrami, Frank Allgöwer, Bin Hu:
Novel Quadratic Constraints for Extending LipSDP beyond Slope-Restricted Activations. CoRR abs/2401.14033 (2024) - [i20]Chawin Sitawarin, Norman Mu, David A. Wagner, Alexandre Araujo:
PAL: Proxy-Guided Black-Box Attack on Large Language Models. CoRR abs/2402.09674 (2024) - [i19]Sara Ghazanfari, Alexandre Araujo, Prashanth Krishnamurthy, Siddharth Garg, Farshad Khorrami:
EMMA: Efficient Visual Alignment in Multi-Modal LLMs. CoRR abs/2410.02080 (2024) - 2023
- [c12]Alexandre Araujo, Aaron J. Havens, Blaise Delattre, Alexandre Allauzen, Bin Hu:
A Unified Algebraic Perspective on Lipschitz Neural Networks. ICLR 2023 - [c11]Blaise Delattre, Quentin Barthélemy, Alexandre Araujo, Alexandre Allauzen:
Efficient Bound of Lipschitz Constant for Convolutional Layers by Gram Iteration. ICML 2023: 7513-7532 - [c10]Othmane Laousy, Alexandre Araujo, Guillaume Chassagnon, Nikos Paragios, Marie-Pierre Revel, Maria Vakalopoulou:
Certification of Deep Learning Models for Medical Image Segmentation. MICCAI (4) 2023: 611-621 - [c9]Aaron J. Havens, Alexandre Araujo, Siddharth Garg, Farshad Khorrami, Bin Hu:
Exploiting Connections between Lipschitz Structures for Certifiably Robust Deep Equilibrium Models. NeurIPS 2023 - [c8]Haotian Xue, Alexandre Araujo, Bin Hu, Yongxin Chen:
Diffusion-Based Adversarial Sample Generation for Improved Stealthiness and Controllability. NeurIPS 2023 - [c7]Othmane Laousy, Alexandre Araujo, Guillaume Chassagnon, Marie-Pierre Revel, Siddharth Garg, Farshad Khorrami, Maria Vakalopoulou:
Towards better certified segmentation via diffusion models. UAI 2023: 1185-1195 - [i18]Alexandre Araujo, Aaron J. Havens, Blaise Delattre, Alexandre Allauzen, Bin Hu:
A Unified Algebraic Perspective on Lipschitz Neural Networks. CoRR abs/2303.03169 (2023) - [i17]Blaise Delattre, Quentin Barthélemy, Alexandre Araujo, Alexandre Allauzen:
Efficient Bound of Lipschitz Constant for Convolutional Layers by Gram Iteration. CoRR abs/2305.16173 (2023) - [i16]Haotian Xue, Alexandre Araujo, Bin Hu, Yongxin Chen:
Diffusion-Based Adversarial Sample Generation for Improved Stealthiness and Controllability. CoRR abs/2305.16494 (2023) - [i15]Othmane Laousy, Alexandre Araujo, Guillaume Chassagnon, Marie-Pierre Revel, Siddharth Garg, Farshad Khorrami, Maria Vakalopoulou:
Towards Better Certified Segmentation via Diffusion Models. CoRR abs/2306.09949 (2023) - [i14]Sara Ghazanfari, Siddharth Garg, Prashanth Krishnamurthy, Farshad Khorrami, Alexandre Araujo:
R-LPIPS: An Adversarially Robust Perceptual Similarity Metric. CoRR abs/2307.15157 (2023) - [i13]Blaise Delattre, Alexandre Araujo, Quentin Barthélemy, Alexandre Allauzen:
The Lipschitz-Variance-Margin Tradeoff for Enhanced Randomized Smoothing. CoRR abs/2309.16883 (2023) - [i12]Othmane Laousy, Alexandre Araujo, Guillaume Chassagnon, Nikos Paragios, Marie-Pierre Revel, Maria Vakalopoulou:
Certification of Deep Learning Models for Medical Image Segmentation. CoRR abs/2310.03664 (2023) - [i11]Sara Ghazanfari, Alexandre Araujo, Prashanth Krishnamurthy, Farshad Khorrami, Siddharth Garg:
LipSim: A Provably Robust Perceptual Similarity Metric. CoRR abs/2310.18274 (2023) - [i10]Alexandre Araujo, Jean Ponce, Julien Mairal:
Towards Real-World Focus Stacking with Deep Learning. CoRR abs/2311.17846 (2023) - 2022
- [c6]Laurent Meunier, Blaise Delattre, Alexandre Araujo, Alexandre Allauzen:
A Dynamical System Perspective for Lipschitz Neural Networks. ICML 2022: 15484-15500 - [i9]Raphael Ettedgui, Alexandre Araujo, Rafael Pinot, Yann Chevaleyre, Jamal Atif:
Towards Evading the Limits of Randomized Smoothing: A Theoretical Analysis. CoRR abs/2206.01715 (2022) - 2021
- [b1]Alexandre Araujo:
Building Compact and Robust Deep Neural Networks with Toeplitz Matrices. (Construire des réseaux neuronaux profonds compacts et robustes avec des matrices Toeplitz). PSL University, Paris, France, 2021 - [c5]Alexandre Araujo, Benjamin Négrevergne, Yann Chevaleyre, Jamal Atif:
On Lipschitz Regularization of Convolutional Layers using Toeplitz Matrix Theory. AAAI 2021: 6661-6669 - [i8]Alexandre Araujo:
Building Compact and Robust Deep Neural Networks with Toeplitz Matrices. CoRR abs/2109.00959 (2021) - [i7]Laurent Meunier, Blaise Delattre, Alexandre Araujo, Alexandre Allauzen:
Scalable Lipschitz Residual Networks with Convex Potential Flows. CoRR abs/2110.12690 (2021) - 2020
- [c4]Alexandre Araujo, Benjamin Négrevergne, Yann Chevaleyre, Jamal Atif:
Understanding and Training Deep Diagonal Circulant Neural Networks. ECAI 2020: 945-952 - [c3]Alexandre Araujo, Laurent Meunier, Rafael Pinot, Benjamin Négrevergne:
Advocating for Multiple Defense Strategies Against Adversarial Examples. PKDD/ECML Workshops 2020: 165-177 - [i6]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) - [i5]Alexandre Araujo, Laurent Meunier, Rafael Pinot, Benjamin Négrevergne:
Advocating for Multiple Defense Strategies against Adversarial Examples. CoRR abs/2012.02632 (2020)
2010 – 2019
- 2019
- [c2]Rafael Pinot, Laurent Meunier, Alexandre Araujo, Hisashi Kashima, Florian Yger, Cédric Gouy-Pailler, Jamal Atif:
Theoretical evidence for adversarial robustness through randomization. NeurIPS 2019: 11838-11848 - [i4]Alexandre Araujo, Benjamin Négrevergne, Yann Chevaleyre, Jamal Atif:
On the Expressive Power of Deep Fully Circulant Neural Networks. CoRR abs/1901.10255 (2019) - [i3]Rafael Pinot, Laurent Meunier, Alexandre Araujo, Hisashi Kashima, Florian Yger, Cédric Gouy-Pailler, Jamal Atif:
Theoretical evidence for adversarial robustness through randomization: the case of the Exponential family. CoRR abs/1902.01148 (2019) - [i2]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
- [c1]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 - [i1]Alexandre Araujo, Benjamin Négrevergne, Yann Chevaleyre, Jamal Atif:
Training compact deep learning models for video classification using circulant matrices. CoRR abs/1810.01140 (2018)
Coauthor Index
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last updated on 2024-11-11 21:29 CET by the dblp team
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