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2020 – today
- 2024
[j33]Nassim Ait Ali Braham
, Julien Mairal, Jocelyn Chanussot, Lichao Mou, Xiaoxiang Zhu:
Enhancing Contrastive Learning With Positive Pair Mining for Few-Shot Hyperspectral Image Classification. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 17: 8509-8526 (2024)- [j32]Behnood Rasti, Alexandre Zouaoui, Julien Mairal, Jocelyn Chanussot:
Image Processing and Machine Learning for Hyperspectral Unmixing: An Overview and the HySUPP Python Package. IEEE Trans. Geosci. Remote. Sens. 62: 1-31 (2024) - [j31]Behnood Rasti, Alexandre Zouaoui, Julien Mairal, Jocelyn Chanussot:
Fast Semisupervised Unmixing Using Nonconvex Optimization. IEEE Trans. Geosci. Remote. Sens. 62: 1-13 (2024) - [j30]Juliette Marrie, Michael Arbel, Julien Mairal, Diane Larlus:
On Good Practices for Task-Specific Distillation of Large Pretrained Visual Models. Trans. Mach. Learn. Res. 2024 (2024) - [j29]Maxime Oquab, Timothée Darcet, Théo Moutakanni, Huy V. Vo, Marc Szafraniec, Vasil Khalidov, Pierre Fernandez, Daniel Haziza, Francisco Massa, Alaaeldin El-Nouby, Mido Assran, Nicolas Ballas, Wojciech Galuba, Russell Howes, Po-Yao Huang, Shang-Wen Li, Ishan Misra, Michael Rabbat, Vasu Sharma, Gabriel Synnaeve, Hu Xu, Hervé Jégou, Julien Mairal, Patrick Labatut, Armand Joulin, Piotr Bojanowski:
DINOv2: Learning Robust Visual Features without Supervision. Trans. Mach. Learn. Res. 2024 (2024) - [c64]Timothée Darcet, Maxime Oquab, Julien Mairal, Piotr Bojanowski:
Vision Transformers Need Registers. ICLR 2024 - [i84]Behnood Rasti, Alexandre Zouaoui, Julien Mairal, Jocelyn Chanussot:
Fast Semi-supervised Unmixing using Non-convex Optimization. CoRR abs/2401.12609 (2024) - [i83]Juliette Marrie, Michael Arbel, Julien Mairal, Diane Larlus:
On Good Practices for Task-Specific Distillation of Large Pretrained Models. CoRR abs/2402.11305 (2024) - [i82]Ieva Petrulionyte, Julien Mairal, Michael Arbel:
Functional Bilevel Optimization for Machine Learning. CoRR abs/2403.20233 (2024) - [i81]Nassim Ait Ali Braham, Conrad M. Albrecht, Julien Mairal, Jocelyn Chanussot, Yi Wang, Xiaoxiang Zhu:
SpectralEarth: Training Hyperspectral Foundation Models at Scale. CoRR abs/2408.08447 (2024) - [i80]Théo Bodrito, Olivier Flasseur, Julien Mairal, Jean Ponce, Maud Langlois, Anne-Marie Lagrange:
MODEL&CO: Exoplanet detection in angular differential imaging by learning across multiple observations. CoRR abs/2409.17178 (2024) - 2023
- [j28]Behnood Rasti, Alexandre Zouaoui, Julien Mairal, Jocelyn Chanussot:
SUnAA: Sparse Unmixing Using Archetypal Analysis. IEEE Geosci. Remote. Sens. Lett. 20: 1-5 (2023) - [j27]Alexandre Zouaoui, Gedeon Muhawenayo, Behnood Rasti, Jocelyn Chanussot, Julien Mairal:
Entropic Descent Archetypal Analysis for Blind Hyperspectral Unmixing. IEEE Trans. Image Process. 32: 4649-4663 (2023) - [j26]Romain Menegaux, Emmanuel Jehanno, Margot Selosse, Julien Mairal:
Self-Attention in Colors: Another Take on Encoding Graph Structure in Transformers. Trans. Mach. Learn. Res. 2023 (2023) - [c63]Enrico Fini, Pietro Astolfi, Karteek Alahari, Xavier Alameda-Pineda, Julien Mairal, Moin Nabi, Elisa Ricci:
Semi-supervised learning made simple with self-supervised clustering. CVPR 2023: 3187-3197 - [c62]Juliette Marrie, Michael Arbel, Diane Larlus, Julien Mairal:
SLACK: Stable Learning of Augmentations with Cold-Start and KL Regularization. CVPR 2023: 24306-24314 - [c61]Olivier Flasseur, Théo Bodrito, Julien Mairal, Jean Ponce, Maud Langlois, Anne-Marie Lagrange:
Combining Multi-Spectral Data With Statistical and Deep-Learning Models for Improved Exoplanet Detection in Direct Imaging at High Contrast. EUSIPCO 2023: 1723-1727 - [c60]Houssam Zenati, Eustache Diemert, Matthieu Martin, Julien Mairal, Pierre Gaillard:
Sequential Counterfactual Risk Minimization. ICML 2023: 40681-40706 - [c59]Minttu Alakuijala, Gabriel Dulac-Arnold, Julien Mairal, Jean Ponce, Cordelia Schmid:
Learning Reward Functions for Robotic Manipulation by Observing Humans. ICRA 2023: 5006-5012 - [c58]Behnood Rasti, Alexandre Zouaoui, Julien Mairal, Jocelyn Chanussot:
Hysupp: An Open-Source Hyperspectral Unmixing Python Package. IGARSS 2023: 1134-1137 - [c57]Gaspard Beugnot, Julien Mairal, Alessandro Rudi:
GloptiNets: Scalable Non-Convex Optimization with Certificates. NeurIPS 2023 - [i79]Houssam Zenati, Eustache Diemert, Matthieu Martin, Julien Mairal, Pierre Gaillard:
Sequential Counterfactual Risk Minimization. CoRR abs/2302.12120 (2023) - [i78]Maxime Oquab, Timothée Darcet, Théo Moutakanni, Huy V. Vo, Marc Szafraniec, Vasil Khalidov, Pierre Fernandez, Daniel Haziza, Francisco Massa, Alaaeldin El-Nouby, Mahmoud Assran, Nicolas Ballas, Wojciech Galuba, Russell Howes, Po-Yao Huang, Shang-Wen Li, Ishan Misra, Michael G. Rabbat, Vasu Sharma, Gabriel Synnaeve, Hu Xu, Hervé Jégou, Julien Mairal, Patrick Labatut, Armand Joulin, Piotr Bojanowski:
DINOv2: Learning Robust Visual Features without Supervision. CoRR abs/2304.07193 (2023) - [i77]Romain Menegaux, Emmanuel Jehanno, Margot Selosse, Julien Mairal:
Self-Attention in Colors: Another Take on Encoding Graph Structure in Transformers. CoRR abs/2304.10933 (2023) - [i76]Enrico Fini, Pietro Astolfi, Karteek Alahari, Xavier Alameda-Pineda, Julien Mairal, Moin Nabi, Elisa Ricci:
Semi-supervised learning made simple with self-supervised clustering. CoRR abs/2306.07483 (2023) - [i75]Juliette Marrie, Michael Arbel, Diane Larlus, Julien Mairal:
SLACK: Stable Learning of Augmentations with Cold-start and KL regularization. CoRR abs/2306.09998 (2023) - [i74]Olivier Flasseur, Théo Bodrito, Julien Mairal, Jean Ponce, Maud Langlois, Anne-Marie Lagrange:
Combining multi-spectral data with statistical and deep-learning models for improved exoplanet detection in direct imaging at high contrast. CoRR abs/2306.12266 (2023) - [i73]Gaspard Beugnot, Julien Mairal, Alessandro Rudi:
GloptiNets: Scalable Non-Convex Optimization with Certificates. CoRR abs/2306.14932 (2023) - [i72]Behnood Rasti, Alexandre Zouaoui, Julien Mairal, Jocelyn Chanussot:
SUnAA: Sparse Unmixing using Archetypal Analysis. CoRR abs/2308.04771 (2023) - [i71]Behnood Rasti, Alexandre Zouaoui, Julien Mairal, Jocelyn Chanussot:
Image Processing and Machine Learning for Hyperspectral Unmixing: An Overview and the HySUPP Python Package. CoRR abs/2308.09375 (2023) - [i70]Timothée Darcet, Maxime Oquab, Julien Mairal, Piotr Bojanowski:
Vision Transformers Need Registers. CoRR abs/2309.16588 (2023) - [i69]Alexandre Araujo, Jean Ponce, Julien Mairal:
Towards Real-World Focus Stacking with Deep Learning. CoRR abs/2311.17846 (2023) - [i68]Bruno Lecouat, Yann Dubois de Mont-Marin, Théo Bodrito, Julien Mairal, Jean Ponce:
Fine Dense Alignment of Image Bursts through Camera Pose and Depth Estimation. CoRR abs/2312.05190 (2023) - 2022
- [j25]Bruno Lecouat, Thomas Eboli, Jean Ponce, Julien Mairal:
High dynamic range and super-resolution from raw image bursts. ACM Trans. Graph. 41(4): 38:1-38:21 (2022) - [c56]Houssam Zenati, Alberto Bietti, Eustache Diemert, Julien Mairal, Matthieu Martin, Pierre Gaillard:
Efficient Kernelized UCB for Contextual Bandits. AISTATS 2022: 5689-5720 - [c55]Gaspard Beugnot, Julien Mairal, Alessandro Rudi:
On the Benefits of Large Learning Rates for Kernel Methods. COLT 2022: 254-282 - [c54]Enrico Fini, Victor G. Turrisi da Costa, Xavier Alameda-Pineda, Elisa Ricci, Karteek Alahari, Julien Mairal:
Self-Supervised Models are Continual Learners. CVPR 2022: 9611-9620 - [c53]Michael Arbel, Julien Mairal:
Amortized Implicit Differentiation for Stochastic Bilevel Optimization. ICLR 2022 - [c52]Moulik Choraria, Leello Tadesse Dadi, Grigorios Chrysos, Julien Mairal, Volkan Cevher:
The Spectral Bias of Polynomial Neural Networks. ICLR 2022 - [c51]Nassim Ait Ali Braham, Lichao Mou, Jocelyn Chanussot, Julien Mairal, Xiao Xiang Zhu:
Self Supervised Learning for Few Shot Hyperspectral Image Classification. IGARSS 2022: 267-270 - [c50]Michael Arbel, Julien Mairal:
Non-Convex Bilevel Games with Critical Point Selection Maps. NeurIPS 2022 - [i67]Houssam Zenati, Alberto Bietti, Eustache Diemert, Julien Mairal, Matthieu Martin, Pierre Gaillard:
Efficient Kernel UCB for Contextual Bandits. CoRR abs/2202.05638 (2022) - [i66]Moulik Choraria, Leello Tadesse Dadi, Grigorios Chrysos, Julien Mairal, Volkan Cevher:
The Spectral Bias of Polynomial Neural Networks. CoRR abs/2202.13473 (2022) - [i65]Gaspard Beugnot, Julien Mairal, Alessandro Rudi:
On the Benefits of Large Learning Rates for Kernel Methods. CoRR abs/2202.13733 (2022) - [i64]Nassim Ait Ali Braham, Lichao Mou, Jocelyn Chanussot, Julien Mairal, Xiao Xiang Zhu:
Self Supervised Learning for Few Shot Hyperspectral Image Classification. CoRR abs/2206.12117 (2022) - [i63]Bruno Lecouat, Thomas Eboli, Jean Ponce, Julien Mairal:
High Dynamic Range and Super-Resolution from Raw Image Bursts. CoRR abs/2207.14671 (2022) - [i62]Alexandre Zouaoui, Gedeon Muhawenayo, Behnood Rasti, Jocelyn Chanussot, Julien Mairal:
Entropic Descent Archetypal Analysis for Blind Hyperspectral Unmixing. CoRR abs/2209.11002 (2022) - [i61]Minttu Alakuijala, Gabriel Dulac-Arnold, Julien Mairal, Jean Ponce, Cordelia Schmid:
Learning Reward Functions for Robotic Manipulation by Observing Humans. CoRR abs/2211.09019 (2022) - 2021
- [j24]Nikita Dvornik, Julien Mairal, Cordelia Schmid:
On the Importance of Visual Context for Data Augmentation in Scene Understanding. IEEE Trans. Pattern Anal. Mach. Intell. 43(6): 2014-2028 (2021) - [j23]Arthur Mensch, Julien Mairal, Bertrand Thirion, Gaël Varoquaux:
Extracting representations of cognition across neuroimaging studies improves brain decoding. PLoS Comput. Biol. 17(5) (2021) - [c49]Bruno Lecouat, Jean Ponce, Julien Mairal:
Lucas-Kanade Reloaded: End-to-End Super-Resolution from Raw Image Bursts. ICCV 2021: 2350-2359 - [c48]Mathilde Caron, Hugo Touvron, Ishan Misra, Hervé Jégou, Julien Mairal, Piotr Bojanowski, Armand Joulin:
Emerging Properties in Self-Supervised Vision Transformers. ICCV 2021: 9630-9640 - [c47]Grégoire Mialon, Dexiong Chen, Alexandre d'Aspremont, Julien Mairal:
A Trainable Optimal Transport Embedding for Feature Aggregation and its Relationship to Attention. ICLR 2021 - [c46]Théo Bodrito, Alexandre Zouaoui, Jocelyn Chanussot, Julien Mairal:
A Trainable Spectral-Spatial Sparse Coding Model for Hyperspectral Image Restoration. NeurIPS 2021: 5430-5442 - [c45]Gaspard Beugnot, Julien Mairal, Alessandro Rudi:
Beyond Tikhonov: faster learning with self-concordant losses, via iterative regularization. NeurIPS 2021: 28196-28207 - [i60]Bruno Lecouat, Jean Ponce, Julien Mairal:
Aliasing is your Ally: End-to-End Super-Resolution from Raw Image Bursts. CoRR abs/2104.06191 (2021) - [i59]Mathilde Caron, Hugo Touvron, Ishan Misra, Hervé Jégou, Julien Mairal, Piotr Bojanowski, Armand Joulin:
Emerging Properties in Self-Supervised Vision Transformers. CoRR abs/2104.14294 (2021) - [i58]Goutam Bhat, Martin Danelljan, Radu Timofte, Kazutoshi Akita, Wooyeong Cho, Haoqiang Fan, Lanpeng Jia, Daeshik Kim, Bruno Lecouat, Youwei Li, Shuaicheng Liu, Ziluan Liu, Ziwei Luo, Takahiro Maeda, Julien Mairal, Christian Micheloni, Xuan Mo, Takeru Oba, Pavel Ostyakov, Jean Ponce, Sanghyeok Son, Jian Sun, Norimichi Ukita, Rao Muhammad Umer, Youliang Yan, Lei Yu, Magauiya Zhussip, Xueyi Zou:
NTIRE 2021 Challenge on Burst Super-Resolution: Methods and Results. CoRR abs/2106.03839 (2021) - [i57]Grégoire Mialon, Dexiong Chen, Margot Selosse, Julien Mairal:
GraphiT: Encoding Graph Structure in Transformers. CoRR abs/2106.05667 (2021) - [i56]Minttu Alakuijala, Gabriel Dulac-Arnold, Julien Mairal, Jean Ponce, Cordelia Schmid:
Residual Reinforcement Learning from Demonstrations. CoRR abs/2106.08050 (2021) - [i55]Gaspard Beugnot, Julien Mairal, Alessandro Rudi:
Beyond Tikhonov: Faster Learning with Self-Concordant Losses via Iterative Regularization. CoRR abs/2106.08855 (2021) - [i54]Théo Bodrito, Alexandre Zouaoui, Jocelyn Chanussot, Julien Mairal:
A Trainable Spectral-Spatial Sparse Coding Model for Hyperspectral Image Restoration. CoRR abs/2111.09708 (2021) - [i53]Michael Arbel, Julien Mairal:
Amortized Implicit Differentiation for Stochastic Bilevel Optimization. CoRR abs/2111.14580 (2021) - [i52]Enrico Fini, Victor G. Turrisi da Costa, Xavier Alameda-Pineda, Elisa Ricci, Karteek Alahari, Julien Mairal:
Self-Supervised Models are Continual Learners. CoRR abs/2112.04215 (2021) - 2020
- [j22]Andrei Kulunchakov, Julien Mairal:
Estimate Sequences for Stochastic Composite Optimization: Variance Reduction, Acceleration, and Robustness to Noise. J. Mach. Learn. Res. 21: 155:1-155:52 (2020) - [c44]Grégoire Mialon, Julien Mairal, Alexandre d'Aspremont:
Screening Data Points in Empirical Risk Minimization via Ellipsoidal Regions and Safe Loss Functions. AISTATS 2020: 3610-3620 - [c43]Bruno Lecouat, Jean Ponce, Julien Mairal:
Fully Trainable and Interpretable Non-local Sparse Models for Image Restoration. ECCV (22) 2020: 238-254 - [c42]Nikita Dvornik, Cordelia Schmid, Julien Mairal:
Selecting Relevant Features from a Multi-domain Representation for Few-Shot Classification. ECCV (10) 2020: 769-786 - [c41]Dexiong Chen, Laurent Jacob, Julien Mairal:
Convolutional Kernel Networks for Graph-Structured Data. ICML 2020: 1576-1586 - [c40]Mathilde Caron, Ishan Misra, Julien Mairal, Priya Goyal, Piotr Bojanowski, Armand Joulin:
Unsupervised Learning of Visual Features by Contrasting Cluster Assignments. NeurIPS 2020 - [c39]Bruno Lecouat, Jean Ponce, Julien Mairal:
A Flexible Framework for Designing Trainable Priors with Adaptive Smoothing and Game Encoding. NeurIPS 2020 - [i51]Mathilde Caron, Ari Morcos, Piotr Bojanowski, Julien Mairal, Armand Joulin:
Pruning Convolutional Neural Networks with Self-Supervision. CoRR abs/2001.03554 (2020) - [i50]Dexiong Chen, Laurent Jacob, Julien Mairal:
Convolutional Kernel Networks for Graph-Structured Data. CoRR abs/2003.05189 (2020) - [i49]Nikita Dvornik, Cordelia Schmid, Julien Mairal:
Selecting Relevant Features from a Universal Representation for Few-shot Classification. CoRR abs/2003.09338 (2020) - [i48]Houssam Zenati, Alberto Bietti, Matthieu Martin, Eustache Diemert, Julien Mairal:
Optimization Approaches for Counterfactual Risk Minimization with Continuous Actions. CoRR abs/2004.11722 (2020) - [i47]Mathilde Caron, Ishan Misra, Julien Mairal, Priya Goyal, Piotr Bojanowski, Armand Joulin:
Unsupervised Learning of Visual Features by Contrasting Cluster Assignments. CoRR abs/2006.09882 (2020) - [i46]Grégoire Mialon, Dexiong Chen, Alexandre d'Aspremont, Julien Mairal:
An Optimal Transport Kernel for Feature Aggregation and its Relationship to Attention. CoRR abs/2006.12065 (2020) - [i45]Bruno Lecouat, Jean Ponce, Julien Mairal:
Designing and Learning Trainable Priors with Non-Cooperative Games. CoRR abs/2006.14859 (2020)
2010 – 2019
- 2019
- [j21]Dexiong Chen, Laurent Jacob, Julien Mairal:
Biological sequence modeling with convolutional kernel networks. Bioinform. 35(18): 3294-3302 (2019) - [j20]Alberto Bietti, Julien Mairal:
Group Invariance, Stability to Deformations, and Complexity of Deep Convolutional Representations. J. Mach. Learn. Res. 20: 25:1-25:49 (2019) - [j19]Hongzhou Lin, Julien Mairal, Zaïd Harchaoui:
An Inexact Variable Metric Proximal Point Algorithm for Generic Quasi-Newton Acceleration. SIAM J. Optim. 29(2): 1408-1443 (2019) - [c38]Mathilde Caron, Piotr Bojanowski, Julien Mairal, Armand Joulin:
Unsupervised Pre-Training of Image Features on Non-Curated Data. ICCV 2019: 2959-2968 - [c37]Nikita Dvornik, Julien Mairal, Cordelia Schmid:
Diversity With Cooperation: Ensemble Methods for Few-Shot Classification. ICCV 2019: 3722-3730 - [c36]Alberto Bietti, Grégoire Mialon, Dexiong Chen, Julien Mairal:
A Kernel Perspective for Regularizing Deep Neural Networks. ICML 2019: 664-674 - [c35]Andrei Kulunchakov, Julien Mairal:
Estimate Sequences for Variance-Reduced Stochastic Composite Optimization. ICML 2019: 3541-3550 - [c34]Andrei Kulunchakov, Julien Mairal:
A Generic Acceleration Framework for Stochastic Composite Optimization. NeurIPS 2019: 12556-12567 - [c33]Alberto Bietti, Julien Mairal:
On the Inductive Bias of Neural Tangent Kernels. NeurIPS 2019: 12873-12884 - [c32]Dexiong Chen, Laurent Jacob, Julien Mairal:
Recurrent Kernel Networks. NeurIPS 2019: 13431-13442 - [c31]Dexiong Chen, Laurent Jacob, Julien Mairal:
Biological Sequence Modeling with Convolutional Kernel Networks. RECOMB 2019: 292-293 - [i44]Andrei Kulunchakov, Julien Mairal:
Estimate Sequences for Stochastic Composite Optimization: Variance Reduction, Acceleration, and Robustness to Noise. CoRR abs/1901.08788 (2019) - [i43]Nikita Dvornik, Cordelia Schmid, Julien Mairal:
Diversity with Cooperation: Ensemble Methods for Few-Shot Classification. CoRR abs/1903.11341 (2019) - [i42]Mathilde Caron, Piotr Bojanowski, Julien Mairal, Armand Joulin:
Leveraging Large-Scale Uncurated Data for Unsupervised Pre-training of Visual Features. CoRR abs/1905.01278 (2019) - [i41]Andrei Kulunchakov, Julien Mairal:
Estimate Sequences for Variance-Reduced Stochastic Composite Optimization. CoRR abs/1905.02374 (2019) - [i40]Alberto Bietti, Julien Mairal:
On the Inductive Bias of Neural Tangent Kernels. CoRR abs/1905.12173 (2019) - [i39]Andrei Kulunchakov, Julien Mairal:
A Generic Acceleration Framework for Stochastic Composite Optimization. CoRR abs/1906.01164 (2019) - [i38]Dexiong Chen, Laurent Jacob, Julien Mairal:
Recurrent Kernel Networks. CoRR abs/1906.03200 (2019) - [i37]Bruno Lecouat, Jean Ponce, Julien Mairal:
Revisiting Non Local Sparse Models for Image Restoration. CoRR abs/1912.02456 (2019) - [i36]Grégoire Mialon, Alexandre d'Aspremont, Julien Mairal:
Screening Data Points in Empirical Risk Minimization via Ellipsoidal Regions and Safe Loss Function. CoRR abs/1912.02566 (2019) - [i35]Julien Mairal:
Cyanure: An Open-Source Toolbox for Empirical Risk Minimization for Python, C++, and soon more. CoRR abs/1912.08165 (2019) - 2018
- [j18]Arthur Mensch, Julien Mairal, Bertrand Thirion, Gaël Varoquaux:
Stochastic Subsampling for Factorizing Huge Matrices. IEEE Trans. Signal Process. 66(1): 113-128 (2018) - [c30]Courtney Paquette, Hongzhou Lin, Dmitriy Drusvyatskiy, Julien Mairal, Zaïd Harchaoui:
Catalyst for Gradient-based Nonconvex Optimization. AISTATS 2018: 613-622 - [c29]Nikita Dvornik, Julien Mairal, Cordelia Schmid:
Modeling Visual Context Is Key to Augmenting Object Detection Datasets. ECCV (12) 2018: 375-391 - [c28]Daan Wynen, Cordelia Schmid, Julien Mairal:
Unsupervised Learning of Artistic Styles with Archetypal Style Analysis. NeurIPS 2018: 6584-6593 - [i34]Daan Wynen, Cordelia Schmid, Julien Mairal:
Unsupervised Learning of Artistic Styles with Archetypal Style Analysis. CoRR abs/1805.11155 (2018) - [i33]Nikita Dvornik, Julien Mairal, Cordelia Schmid:
Modeling Visual Context is Key to Augmenting Object Detection Datasets. CoRR abs/1807.07428 (2018) - [i32]Nikita Dvornik, Julien Mairal, Cordelia Schmid:
On the Importance of Visual Context for Data Augmentation in Scene Understanding. CoRR abs/1809.02492 (2018) - [i31]Arthur Mensch, Julien Mairal, Bertrand Thirion, Gaël Varoquaux:
Extracting Universal Representations of Cognition across Brain-Imaging Studies. CoRR abs/1809.06035 (2018) - [i30]Alberto Bietti, Grégoire Mialon, Julien Mairal:
On Regularization and Robustness of Deep Neural Networks. CoRR abs/1810.00363 (2018) - 2017
- [b1]Julien Mairal:
Large-Scale Machine Learning and Applications. (Apprentissage à grande échelle et applications). Grenoble Alpes University, France, 2017 - [j17]Mattis Paulin, Julien Mairal, Matthijs Douze, Zaïd Harchaoui, Florent Perronnin, Cordelia Schmid:
Convolutional Patch Representations for Image Retrieval: An Unsupervised Approach. Int. J. Comput. Vis. 121(1): 149-168 (2017) - [j16]Hongzhou Lin, Julien Mairal, Zaïd Harchaoui:
Catalyst Acceleration for First-order Convex Optimization: from Theory to Practice. J. Mach. Learn. Res. 18: 212:1-212:54 (2017) - [c27]Nikita Dvornik, Konstantin Shmelkov, Julien Mairal, Cordelia Schmid:
BlitzNet: A Real-Time Deep Network for Scene Understanding. ICCV 2017: 4174-4182 - [c26]Alberto Bietti, Julien Mairal:
Stochastic Optimization with Variance Reduction for Infinite Datasets with Finite Sum Structure. NIPS 2017: 1623-1633 - [c25]Arthur Mensch, Julien Mairal, Danilo Bzdok, Bertrand Thirion, Gaël Varoquaux:
Learning Neural Representations of Human Cognition across Many fMRI Studies. NIPS 2017: 5883-5893 - [c24]Alberto Bietti, Julien Mairal:
Invariance and Stability of Deep Convolutional Representations. NIPS 2017: 6210-6220 - [i29]Arthur Mensch, Julien Mairal, Bertrand Thirion, Gaël Varoquaux:
Stochastic Subsampling for Factorizing Huge Matrices. CoRR abs/1701.05363 (2017) - [i28]Alberto Bietti, Julien Mairal:
Group Invariance and Stability to Deformations of Deep Convolutional Representations. CoRR abs/1706.03078 (2017) - [i27]Nikita Dvornik, Konstantin Shmelkov, Julien Mairal, Cordelia Schmid:
BlitzNet: A Real-Time Deep Network for Scene Understanding. CoRR abs/1708.02813 (2017) - [i26]Arthur Mensch, Julien Mairal, Danilo Bzdok, Bertrand Thirion, Gaël Varoquaux:
Learning Neural Representations of Human Cognition across Many fMRI Studies. CoRR abs/1710.11438 (2017) - [i25]Arthur Mensch, Julien Mairal, Bertrand Thirion, Gaël Varoquaux:
Subsampling Enables Fast Factorisation of Huge Matrices into Sparse Signals. ERCIM News 2017(108) (2017) - 2016
- [j15]Andreas M. Tillmann, Yonina C. Eldar, Julien Mairal:
DOLPHIn - Dictionary Learning for Phase Retrieval. IEEE Trans. Signal Process. 64(24): 6485-6500 (2016) - [c23]Andreas M. Tillmann, Yonina C. Eldar, Julien Mairal:
Dictionary learning from phaseless measurements. ICASSP 2016: 4702-4706 - [c22]Arthur Mensch, Julien Mairal, Bertrand Thirion, Gaël Varoquaux:
Dictionary Learning for Massive Matrix Factorization. ICML 2016: 1737-1746 - [c21]Julien Mairal:
End-to-End Kernel Learning with Supervised Convolutional Kernel Networks. NIPS 2016: 1399-1407 - [i24]Andreas M. Tillmann, Yonina C. Eldar, Julien Mairal:
DOLPHIn - Dictionary Learning for Phase Retrieval. CoRR abs/1602.02263 (2016) - [i23]Mattis Paulin, Julien Mairal, Matthijs Douze, Zaïd Harchaoui, Florent Perronnin, Cordelia Schmid:
Convolutional Patch Representations for Image Retrieval: an Unsupervised Approach. CoRR abs/1603.00438 (2016) - [i22]Arthur Mensch, Julien Mairal, Bertrand Thirion, Gaël Varoquaux:
Dictionary Learning for Massive Matrix Factorization. CoRR abs/1605.00937 (2016) - [i21]Julien Mairal:
End-to-End Kernel Learning with Supervised Convolutional Kernel Networks. CoRR abs/1605.06265 (2016) - [i20]Alberto Bietti, Julien Mairal:
Stochastic Optimization with Variance Reduction for Infinite Datasets with Finite-Sum Structure. CoRR abs/1610.00970 (2016) - 2015
- [j14]Elsa Bernard, Laurent Jacob, Julien Mairal, Eric Viara, Jean-Philippe Vert:
A convex formulation for joint RNA isoform detection and quantification from multiple RNA-seq samples. BMC Bioinform. 16: 262:1-262:10 (2015) - [j13]Julien Mairal, Michael Elad, Francis R. Bach:
Guest Editorial: Sparse Coding. Int. J. Comput. Vis. 114(2-3): 89-90 (2015) - [j12]Julien Mairal:
Incremental Majorization-Minimization Optimization with Application to Large-Scale Machine Learning. SIAM J. Optim. 25(2): 829-855 (2015) - [c20]Mattis Paulin, Matthijs Douze, Zaïd Harchaoui, Julien Mairal, Florent Perronnin, Cordelia Schmid:
Local Convolutional Features with Unsupervised Training for Image Retrieval. ICCV 2015: 91-99 - [c19]Hongzhou Lin, Julien Mairal, Zaïd Harchaoui:
A Universal Catalyst for First-Order Optimization. NIPS 2015: 3384-3392 - 2014
- [j11]Elsa Bernard, Laurent Jacob, Julien Mairal, Jean-Philippe Vert:
Efficient RNA isoform identification and quantification from RNA-Seq data with network flows. Bioinform. 30(17): 2447-2455 (2014) - [j10]Julien Mairal, Francis R. Bach, Jean Ponce:
Sparse Modeling for Image and Vision Processing. Found. Trends Comput. Graph. Vis. 8(2-3): 85-283 (2014) - [c18]Yuansi Chen, Julien Mairal, Zaïd Harchaoui:
Fast and Robust Archetypal Analysis for Representation Learning. CVPR 2014: 1478-1485 - [c17]Anoop Cherian, Julien Mairal, Karteek Alahari, Cordelia Schmid:
Mixing Body-Part Sequences for Human Pose Estimation. CVPR 2014: 2361-2368 - [c16]Hyun Oh Song, Ross B. Girshick, Stefanie Jegelka, Julien Mairal, Zaïd Harchaoui, Trevor Darrell:
On learning to localize objects with minimal supervision. ICML 2014: 1611-1619 - [c15]Julien Mairal, Piotr Koniusz, Zaïd Harchaoui, Cordelia Schmid:
Convolutional Kernel Networks. NIPS 2014: 2627-2635 - [i19]Julien Mairal:
Incremental Majorization-Minimization Optimization with Application to Large-Scale Machine Learning. CoRR abs/1402.4419 (2014) - [i18]Hyun Oh Song, Ross B. Girshick, Stefanie Jegelka, Julien Mairal, Zaïd Harchaoui, Trevor Darrell:
One-Bit Object Detection: On learning to localize objects with minimal supervision. CoRR abs/1403.1024 (2014) - [i17]Yuansi Chen, Julien Mairal, Zaïd Harchaoui:
Fast and Robust Archetypal Analysis for Representation Learning. CoRR abs/1405.6472 (2014) - [i16]Julien Mairal, Piotr Koniusz, Zaïd Harchaoui, Cordelia Schmid:
Convolutional Kernel Networks. CoRR abs/1406.3332 (2014) - [i15]Julien Mairal, Francis R. Bach, Jean Ponce:
Sparse Modeling for Image and Vision Processing. CoRR abs/1411.3230 (2014) - 2013
- [j9]Julien Mairal, Bin Yu:
Supervised feature selection in graphs with path coding penalties and network flows. J. Mach. Learn. Res. 14(1): 2449-2485 (2013) - [c14]Anil Kumar Nelakanti, Cédric Archambeau, Julien Mairal, Francis R. Bach, Guillaume Bouchard:
Structured Penalties for Log-Linear Language Models. EMNLP 2013: 233-243 - [c13]Julien Mairal:
Optimization with First-Order Surrogate Functions. ICML (3) 2013: 783-791 - [c12]Julien Mairal:
Stochastic Majorization-Minimization Algorithms for Large-Scale Optimization. NIPS 2013: 2283-2291 - [i14]Julien Mairal:
Optimization with First-Order Surrogate Functions. CoRR abs/1305.3120 (2013) - [i13]Julien Mairal:
Stochastic Majorization-Minimization Optimization with First-Order Surrogate Functions. CoRR abs/1306.4650 (2013) - 2012
- [j8]Francis R. Bach, Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski:
Optimization with Sparsity-Inducing Penalties. Found. Trends Mach. Learn. 4(1): 1-106 (2012) - [j7]Julien Mairal, Francis R. Bach, Jean Ponce:
Task-Driven Dictionary Learning. IEEE Trans. Pattern Anal. Mach. Intell. 34(4): 791-804 (2012) - [c11]Julien Mairal, Bin Yu:
Complexity Analysis of the Lasso Regularization Path. ICML 2012 - [i12]Julien Mairal, Bin Yu:
Supervised Feature Selection in Graphs with Path Coding Penalties and Network Flows. CoRR abs/1204.4539 (2012) - [i11]Julien Mairal, Bin Yu:
Complexity Analysis of the Lasso Regularization Path. CoRR abs/1205.0079 (2012) - 2011
- [j6]Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski, Francis R. Bach:
Proximal Methods for Hierarchical Sparse Coding. J. Mach. Learn. Res. 12: 2297-2334 (2011) - [j5]Julien Mairal, Rodolphe Jenatton, Guillaume Obozinski, Francis R. Bach:
Convex and Network Flow Optimization for Structured Sparsity. J. Mach. Learn. Res. 12: 2681-2720 (2011) - [c10]Louise Benoît, Julien Mairal, Francis R. Bach, Jean Ponce:
Sparse image representation with epitomes. CVPR 2011: 2913-2920 - [i10]Julien Mairal, Rodolphe Jenatton, Guillaume Obozinski, Francis R. Bach:
Convex and Network Flow Optimization for Structured Sparsity. CoRR abs/1104.1872 (2011) - [i9]Francis R. Bach, Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski:
Optimization with Sparsity-Inducing Penalties. CoRR abs/1108.0775 (2011) - [i8]Francis R. Bach, Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski:
Structured sparsity through convex optimization. CoRR abs/1109.2397 (2011) - [i7]Florent Couzinie-Devy, Julien Mairal, Francis R. Bach, Jean Ponce:
Dictionary Learning for Deblurring and Digital Zoom. CoRR abs/1110.0957 (2011) - [i6]Louise Benoît, Julien Mairal, Francis R. Bach, Jean Ponce:
Sparse Image Representation with Epitomes. CoRR abs/1110.2855 (2011) - [i5]Julien Mairal, Rodolphe Jenatton, Guillaume Obozinski, Francis R. Bach:
Learning Hierarchical and Topographic Dictionaries with Structured Sparsity. CoRR abs/1110.4481 (2011) - 2010
- [j4]Julien Mairal, Francis R. Bach, Jean Ponce, Guillermo Sapiro:
Online Learning for Matrix Factorization and Sparse Coding. J. Mach. Learn. Res. 11: 19-60 (2010) - [j3]John Wright, Yi Ma, Julien Mairal, Guillermo Sapiro, Thomas S. Huang, Shuicheng Yan:
Sparse Representation for Computer Vision and Pattern Recognition. Proc. IEEE 98(6): 1031-1044 (2010) - [c9]Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski, Francis R. Bach:
Proximal Methods for Sparse Hierarchical Dictionary Learning. ICML 2010: 487-494 - [c8]Julien Mairal, Rodolphe Jenatton, Guillaume Obozinski, Francis R. Bach:
Network Flow Algorithms for Structured Sparsity. NIPS 2010: 1558-1566 - [i4]Julien Mairal, Rodolphe Jenatton, Guillaume Obozinski, Francis R. Bach:
Network Flow Algorithms for Structured Sparsity. CoRR abs/1008.5209 (2010)
2000 – 2009
- 2009
- [c7]Julien Mairal, Francis R. Bach, Jean Ponce, Guillermo Sapiro, Andrew Zisserman:
Non-local sparse models for image restoration. ICCV 2009: 2272-2279 - [c6]Julien Mairal, Francis R. Bach, Jean Ponce, Guillermo Sapiro:
Online dictionary learning for sparse coding. ICML 2009: 689-696 - [i3]Julien Mairal, Francis R. Bach, Jean Ponce, Guillermo Sapiro:
Online Learning for Matrix Factorization and Sparse Coding. CoRR abs/0908.0050 (2009) - 2008
- [j2]Julien Mairal, Guillermo Sapiro, Michael Elad:
Learning Multiscale Sparse Representations for Image and Video Restoration. Multiscale Model. Simul. 7(1): 214-241 (2008) - [j1]Julien Mairal, Michael Elad, Guillermo Sapiro:
Sparse Representation for Color Image Restoration. IEEE Trans. Image Process. 17(1): 53-69 (2008) - [c5]Julien Mairal, Francis R. Bach, Jean Ponce, Guillermo Sapiro, Andrew Zisserman:
Discriminative learned dictionaries for local image analysis. CVPR 2008 - [c4]Julien Mairal, Marius Leordeanu, Francis R. Bach, Martial Hebert, Jean Ponce:
Discriminative Sparse Image Models for Class-Specific Edge Detection and Image Interpretation. ECCV (3) 2008: 43-56 - [c3]Julien Mairal, Francis R. Bach, Jean Ponce, Guillermo Sapiro, Andrew Zisserman:
Supervised Dictionary Learning. NIPS 2008: 1033-1040 - [i2]Julien Mairal, Francis R. Bach, Jean Ponce, Guillermo Sapiro, Andrew Zisserman:
Supervised Dictionary Learning. CoRR abs/0809.3083 (2008) - [i1]Francis R. Bach, Julien Mairal, Jean Ponce:
Convex Sparse Matrix Factorizations. CoRR abs/0812.1869 (2008) - 2007
- [c2]Julien Mairal, Guillermo Sapiro, Michael Elad:
Multiscale Sparse Image Representationwith Learned Dictionaries. ICIP (3) 2007: 105-108 - 2006
- [c1]Julien Mairal, Renaud Keriven, Alexandre Chariot:
Fast and Efficient Dense Variational Stereo on GPU. 3DPVT 2006: 97-104
Coauthor Index
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