Nicolas Flammarion

124 papers A* 45A 3Journal 72Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Gradient Flow Polarizes Softmax Outputs towards Low-Entropy Solutions. CoRR Aditya Varre, Mark Rofin, Nicolas Flammarion
2026	J	`jnl`	HalluHard: A Hard Multi-Turn Hallucination Benchmark. CoRR Dongyang Fan, Sebastien Delsad, Nicolas Flammarion, Maksym Andriushchenko
2026	J	`jnl`	Incremental Learning of Sparse Attention Patterns in Transformers. CoRR Oguz Kaan Yüksel, Rodrigo Alvarez Lucendo, Nicolas Flammarion
2026	J	`jnl`	On the Adversarial Robustness of Discrete Image Tokenizers. CoRR Rishika Bhagwatkar, Irina Rish, Nicolas Flammarion, Francesco Croce
2026	J	`jnl`	On the Out-of-Distribution Generalization of Reasoning in Multimodal LLMs for Simple Visual Planning Tasks. CoRR Yannic Neuhaus, Nicolas Flammarion, Matthias Hein, Francesco Croce
2025	J	`jnl`	Chain-of-Frames: Advancing Video Understanding in Multimodal LLMs via Frame-Aware Reasoning. CoRR Sara Ghazanfari, Francesco Croce, Nicolas Flammarion, Prashanth Krishnamurthy, Farshad Khorrami, Siddharth Garg
2025	A*	`conf`	Does Refusal Training in LLMs Generalize to the Past Tense? ICLR Maksym Andriushchenko, Nicolas Flammarion
2025	J	`jnl`	Early Alignment in Two-Layer Networks Training is a Two-Edged Sword. J. Mach. Learn. Res. Etienne Boursier, Nicolas Flammarion
2025	J	`jnl`	Exact Learning of Arithmetic with Differentiable Agents. CoRR Hristo Papazov, Francesco D'Angelo, Nicolas Flammarion
2025	J	`jnl`	FuseLIP: Multimodal Embeddings via Early Fusion of Discrete Tokens. CoRR Christian Schlarmann, Francesco Croce, Nicolas Flammarion, Matthias Hein
2025	A*	`conf`	Is In-Context Learning Sufficient for Instruction Following in LLMs? ICLR Hao Zhao, Maksym Andriushchenko, Francesco Croce, Nicolas Flammarion
2025	A*	`conf`	Jailbreaking Leading Safety-Aligned LLMs with Simple Adaptive Attacks. ICLR Maksym Andriushchenko, Francesco Croce, Nicolas Flammarion
2025	A*	`conf`	Learning Algorithms in the Limit. COLT Hristo Papazov, Nicolas Flammarion
2025	J	`jnl`	Learning Algorithms in the Limit. CoRR Hristo Papazov, Nicolas Flammarion
2025	A*	`conf`	Learning In-context n-grams with Transformers: Sub-n-grams Are Near-Stationary Points. ICML Aditya Varre, Gizem Yüce, Nicolas Flammarion
2025	J	`jnl`	Learning In-context n-grams with Transformers: Sub-n-grams Are Near-stationary Points. CoRR Aditya Varre, Gizem Yüce, Nicolas Flammarion
2025	A*	`conf`	Learning Parametric Distributions from Samples and Preferences. ICML Marc Jourdan, Gizem Yüce, Nicolas Flammarion
2025	J	`jnl`	Learning Parametric Distributions from Samples and Preferences. CoRR Marc Jourdan, Gizem Yüce, Nicolas Flammarion
2025	A*	`conf`	Long-Context Linear System Identification. ICLR Oguz Kaan Yüksel, Mathieu Even, Nicolas Flammarion
2025	J	`jnl`	OS-Harm: A Benchmark for Measuring Safety of Computer Use Agents. CoRR Thomas Kuntz, Agatha Duzan, Hao Zhao, Francesco Croce, Zico Kolter, Nicolas Flammarion, Maksym Andriushchenko
2025	A	`conf`	On the Sample Complexity of Next-Token Prediction. AISTATS Oguz Kaan Yüksel, Nicolas Flammarion
2025	J	`jnl`	Selective Induction Heads: How Transformers Select Causal Structures In Context. CoRR Francesco D'Angelo, Francesco Croce, Nicolas Flammarion
2025	A*	`conf`	Selective induction Heads: How Transformers Select Causal Structures in Context. ICLR Francesco D'Angelo, Francesco Croce, Nicolas Flammarion
2025	A*	`conf`	Simplicity Bias and Optimization Threshold in Two-Layer ReLU Networks. ICML Etienne Boursier, Nicolas Flammarion
2024	J	`jnl`	Competition Report: Finding Universal Jailbreak Backdoors in Aligned LLMs. CoRR Javier Rando, Francesco Croce, Krystof Mitka, Stepan Shabalin, Maksym Andriushchenko, Nicolas Flammarion, Florian Tramèr
2024	J	`jnl`	Could ChatGPT get an Engineering Degree? Evaluating Higher Education Vulnerability to AI Assistants. CoRR Beatriz Borges, Negar Foroutan, Deniz Bayazit, Anna Sotnikova, Syrielle Montariol, Tanya Nazaretzky, Mohammadreza Banaei, Alireza Sakhaeirad, Philippe Servant, Seyed Parsa Neshaei, Jibril Frej, Angelika Romanou, Gail Weiss, Sepideh Mamooler, Zeming Chen, Simin Fan, Silin Gao, Mete Ismayilzada, Debjit Paul, Alexandre Schöpfer, Andrej Janchevski, Anja Tiede, Clarence Linden, Emanuele Troiani, Francesco Salvi, Freya Behrens, Giacomo Orsi, Giovanni Piccioli, Hadrien Sevel, Louis Coulon, Manuela Pineros-Rodriguez, Marin Bonnassies, Pierre Hellich, Puck van Gerwen, Sankalp Gambhir, Solal Pirelli, Thomas Blanchard, Timothée Callens, Toni Abi Aoun, Yannick Calvino Alonso, Yuri Cho, Alberto Silvio Chiappa, Antonio Sclocchi, Étienne Bruno, Florian Hofhammer, Gabriel Pescia, Geovani Rizk, Leello Dadi, Lucas Stoffl, Manoel Horta Ribeiro, Matthieu Bovel, Yueyang Pan, Aleksandra Radenovic, Alexandre Alahi, Alexander Mathis, Anne-Florence Bitbol, Boi Faltings, Cécile Hébert, Devis Tuia, François Maréchal, George Candea, Giuseppe Carleo, Jean-Cédric Chappelier, Nicolas Flammarion, Jean-Marie Fürbringer, Jean-Philippe Pellet, Karl Aberer, Lenka Zdeborová, Marcel Salathé, Martin Jaggi, Martin Rajman, Mathias Payer, Matthieu Wyart, Michael Gastpar, Michele Ceriotti, Ola Svensson, Olivier Lévêque, Paolo Ienne, Rachid Guerraoui, Robert West, Sanidhya Kashyap, Valerio Piazza, Viesturs Simanis, Viktor Kuncak, Volkan Cevher, Philippe Schwaller, Sacha Friedli, Patrick Jermann, Tanja Käser, Antoine Bosselut
2024	J	`jnl`	Does Refusal Training in LLMs Generalize to the Past Tense? CoRR Maksym Andriushchenko, Nicolas Flammarion
2024	J	`jnl`	Early alignment in two-layer networks training is a two-edged sword. CoRR Etienne Boursier, Nicolas Flammarion
2024	A*	`conf`	First-order ANIL provably learns representations despite overparametrisation. ICLR Oguz Kaan Yüksel, Etienne Boursier, Nicolas Flammarion
2024	A*	`conf`	Implicit Bias of Mirror Flow on Separable Data. NeurIPS Scott Pesme, Radu-Alexandru Dragomir, Nicolas Flammarion
2024	J	`jnl`	Implicit Bias of Mirror Flow on Separable Data. CoRR Scott Pesme, Radu-Alexandru Dragomir, Nicolas Flammarion
2024	J	`jnl`	Is In-Context Learning Sufficient for Instruction Following in LLMs? CoRR Hao Zhao, Maksym Andriushchenko, Francesco Croce, Nicolas Flammarion
2024	A*	`conf`	JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models. NeurIPS Patrick Chao, Edoardo Debenedetti, Alexander Robey, Maksym Andriushchenko, Francesco Croce, Vikash Sehwag, Edgar Dobriban, Nicolas Flammarion, George J. Pappas, Florian Tramèr, Hamed Hassani, Eric Wong
2024	J	`jnl`	JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models. CoRR Patrick Chao, Edoardo Debenedetti, Alexander Robey, Maksym Andriushchenko, Francesco Croce, Vikash Sehwag, Edgar Dobriban, Nicolas Flammarion, George J. Pappas, Florian Tramèr, Hamed Hassani, Eric Wong
2024	J	`jnl`	Jailbreaking Leading Safety-Aligned LLMs with Simple Adaptive Attacks. CoRR Maksym Andriushchenko, Francesco Croce, Nicolas Flammarion
2024	A	`conf`	Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networks. AISTATS Hristo Papazov, Scott Pesme, Nicolas Flammarion
2024	J	`jnl`	Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networks. CoRR Hristo Papazov, Scott Pesme, Nicolas Flammarion
2024	A*	`conf`	Long Is More for Alignment: A Simple but Tough-to-Beat Baseline for Instruction Fine-Tuning. ICML Hao Zhao, Maksym Andriushchenko, Francesco Croce, Nicolas Flammarion
2024	J	`jnl`	Long Is More for Alignment: A Simple but Tough-to-Beat Baseline for Instruction Fine-Tuning. CoRR Hao Zhao, Maksym Andriushchenko, Francesco Croce, Nicolas Flammarion
2024	J	`jnl`	Long-Context Linear System Identification. CoRR Oguz Kaan Yüksel, Mathieu Even, Nicolas Flammarion
2024	A*	`conf`	SGD vs GD: Rank Deficiency in Linear Networks. NeurIPS Aditya Vardhan Varre, Margarita Sagitova, Nicolas Flammarion
2024	J	`jnl`	Simplicity bias and optimization threshold in two-layer ReLU networks. CoRR Etienne Boursier, Nicolas Flammarion
2024	J	`jnl`	Towards Unified Benchmark and Models for Multi-Modal Perceptual Metrics. CoRR Sara Ghazanfari, Siddharth Garg, Nicolas Flammarion, Prashanth Krishnamurthy, Farshad Khorrami, Francesco Croce
2024	A*	`conf`	Why Do We Need Weight Decay in Modern Deep Learning? NeurIPS Francesco D'Angelo, Maksym Andriushchenko, Aditya Vardhan Varre, Nicolas Flammarion
2023	J	`jnl`	(S)GD over Diagonal Linear Networks: Implicit Regularisation, Large Stepsizes and Edge of Stability. CoRR Mathieu Even, Scott Pesme, Suriya Gunasekar, Nicolas Flammarion
2023	A*	`conf`	(S)GD over Diagonal Linear Networks: Implicit bias, Large Stepsizes and Edge of Stability. NeurIPS Mathieu Even, Scott Pesme, Suriya Gunasekar, Nicolas Flammarion
2023	A*	`conf`	A Modern Look at the Relationship between Sharpness and Generalization. ICML Maksym Andriushchenko, Francesco Croce, Maximilian Müller, Matthias Hein, Nicolas Flammarion
2023	J	`jnl`	A modern look at the relationship between sharpness and generalization. CoRR Maksym Andriushchenko, Francesco Croce, Maximilian Müller, Matthias Hein, Nicolas Flammarion
2023	A*	`conf`	Linearization Algorithms for Fully Composite Optimization. COLT Maria-Luiza Vladarean, Nikita Doikov, Martin Jaggi, Nicolas Flammarion
2023	J	`jnl`	Linearization Algorithms for Fully Composite Optimization. CoRR Maria-Luiza Vladarean, Nikita Doikov, Martin Jaggi, Nicolas Flammarion
2023	J	`jnl`	Model agnostic methods meta-learn despite misspecifications. CoRR Yüksel Oguz, Etienne Boursier, Nicolas Flammarion
2023	J	`jnl`	On Adaptivity in Quantum Testing. Trans. Mach. Learn. Res. Omar Fawzi, Nicolas Flammarion, Aurélien Garivier, Aadil Oufkir
2023	A*	`conf`	On the spectral bias of two-layer linear networks. NeurIPS Aditya Vardhan Varre, Maria-Luiza Vladarean, Loucas Pillaud-Vivien, Nicolas Flammarion
2023	A*	`conf`	Penalising the biases in norm regularisation enforces sparsity. NeurIPS Etienne Boursier, Nicolas Flammarion
2023	J	`jnl`	Penalising the biases in norm regularisation enforces sparsity. CoRR Etienne Boursier, Nicolas Flammarion
2023	A*	`conf`	Quantum Channel Certification with Incoherent Measurements. COLT Omar Fawzi, Nicolas Flammarion, Aurélien Garivier, Aadil Oufkir
2023	J	`jnl`	Quantum Channel Certification with Incoherent Strategies. CoRR Omar Fawzi, Nicolas Flammarion, Aurélien Garivier, Aadil Oufkir
2023	A*	`conf`	SGD with Large Step Sizes Learns Sparse Features. ICML Maksym Andriushchenko, Aditya Vardhan Varre, Loucas Pillaud-Vivien, Nicolas Flammarion
2023	A*	`conf`	Saddle-to-Saddle Dynamics in Diagonal Linear Networks. NeurIPS Scott Pesme, Nicolas Flammarion
2023	J	`jnl`	Saddle-to-Saddle Dynamics in Diagonal Linear Networks. CoRR Scott Pesme, Nicolas Flammarion
2023	A*	`conf`	Sharpness-Aware Minimization Leads to Low-Rank Features. NeurIPS Maksym Andriushchenko, Dara Bahri, Hossein Mobahi, Nicolas Flammarion
2023	J	`jnl`	Sharpness-Aware Minimization Leads to Low-Rank Features. CoRR Maksym Andriushchenko, Dara Bahri, Hossein Mobahi, Nicolas Flammarion
2023	A*	`conf`	Transferable Adversarial Robustness for Categorical Data via Universal Robust Embeddings. NeurIPS Klim Kireev, Maksym Andriushchenko, Carmela Troncoso, Nicolas Flammarion
2023	J	`jnl`	Transferable Adversarial Robustness for Categorical Data via Universal Robust Embeddings. CoRR Klim Kireev, Maksym Andriushchenko, Carmela Troncoso, Nicolas Flammarion
2023	J	`jnl`	Why Do We Need Weight Decay in Modern Deep Learning? CoRR Maksym Andriushchenko, Francesco D'Angelo, Aditya Varre, Nicolas Flammarion
2022	—	`conf`	ARIA: Adversarially Robust Image Attribution for Content Provenance. CVPR Workshops Maksym Andriushchenko, Xiaoyang Rebecca Li, Geoffrey Oxholm, Thomas Gittings, Tu Bui, Nicolas Flammarion, John P. Collomosse
2022	J	`jnl`	ARIA: Adversarially Robust Image Attribution for Content Provenance. CoRR Maksym Andriushchenko, Xiaoyang Rebecca Li, Geoffrey Oxholm, Thomas Gittings, Tu Bui, Nicolas Flammarion, John P. Collomosse
2022	A*	`conf`	Accelerated SGD for Non-Strongly-Convex Least Squares. COLT Aditya Varre, Nicolas Flammarion
2022	J	`jnl`	Accelerated SGD for Non-Strongly-Convex Least Squares. CoRR Aditya Varre, Nicolas Flammarion
2022	J	`jnl`	An Efficient Sampling Algorithm for Non-smooth Composite Potentials. J. Mach. Learn. Res. Wenlong Mou, Nicolas Flammarion, Martin J. Wainwright, Peter L. Bartlett
2022	A*	`conf`	Gradient flow dynamics of shallow ReLU networks for square loss and orthogonal inputs. NeurIPS Etienne Boursier, Loucas Pillaud-Vivien, Nicolas Flammarion
2022	J	`jnl`	Gradient flow dynamics of shallow ReLU networks for square loss and orthogonal inputs. CoRR Etienne Boursier, Loucas Pillaud-Vivien, Nicolas Flammarion
2022	A*	`conf`	Label noise (stochastic) gradient descent implicitly solves the Lasso for quadratic parametrisation. COLT Loucas Pillaud-Vivien, Julien Reygner, Nicolas Flammarion
2022	J	`jnl`	Label noise (stochastic) gradient descent implicitly solves the Lasso for quadratic parametrisation. CoRR Loucas Pillaud-Vivien, Julien Reygner, Nicolas Flammarion
2022	A	`conf`	On the effectiveness of adversarial training against common corruptions. UAI Klim Kireev, Maksym Andriushchenko, Nicolas Flammarion
2022	J	`jnl`	SGD with large step sizes learns sparse features. CoRR Maksym Andriushchenko, Aditya Varre, Loucas Pillaud-Vivien, Nicolas Flammarion
2022	J	`jnl`	Sequential algorithms for testing identity and closeness of distributions. CoRR Omar Fawzi, Nicolas Flammarion, Aurélien Garivier, Aadil Oufkir
2022	A*	`conf`	Sparse-RS: A Versatile Framework for Query-Efficient Sparse Black-Box Adversarial Attacks. AAAI Francesco Croce, Maksym Andriushchenko, Naman D. Singh, Nicolas Flammarion, Matthias Hein
2022	A*	`conf`	Towards Understanding Sharpness-Aware Minimization. ICML Maksym Andriushchenko, Nicolas Flammarion
2022	J	`jnl`	Towards Understanding Sharpness-Aware Minimization. CoRR Maksym Andriushchenko, Nicolas Flammarion
2022	A*	`conf`	Trace norm regularization for multi-task learning with scarce data. COLT Etienne Boursier, Mikhail Konobeev, Nicolas Flammarion
2022	J	`jnl`	Trace norm regularization for multi-task learning with scarce data. CoRR Etienne Boursier, Mikhail Konobeev, Nicolas Flammarion
2021	J	`jnl`	A Continuized View on Nesterov Acceleration for Stochastic Gradient Descent and Randomized Gossip. CoRR Mathieu Even, Raphaël Berthier, Francis R. Bach, Nicolas Flammarion, Pierre Gaillard, Hadrien Hendrikx, Laurent Massoulié, Adrien B. Taylor
2021	J	`jnl`	A Continuized View on Nesterov Acceleration. CoRR Raphaël Berthier, Francis R. Bach, Nicolas Flammarion, Pierre Gaillard, Adrien B. Taylor
2021	A*	`conf`	Continuized Accelerations of Deterministic and Stochastic Gradient Descents, and of Gossip Algorithms. NeurIPS Mathieu Even, Raphaël Berthier, Francis R. Bach, Nicolas Flammarion, Hadrien Hendrikx, Pierre Gaillard, Laurent Massoulié, Adrien B. Taylor
2021	A*	`conf`	Implicit Bias of SGD for Diagonal Linear Networks: a Provable Benefit of Stochasticity. NeurIPS Scott Pesme, Loucas Pillaud-Vivien, Nicolas Flammarion
2021	J	`jnl`	Implicit Bias of SGD for Diagonal Linear Networks: a Provable Benefit of Stochasticity. CoRR Scott Pesme, Loucas Pillaud-Vivien, Nicolas Flammarion
2021	A*	`conf`	Last iterate convergence of SGD for Least-Squares in the Interpolation regime. NeurIPS Aditya Vardhan Varre, Loucas Pillaud-Vivien, Nicolas Flammarion
2021	J	`jnl`	Last iterate convergence of SGD for Least-Squares in the Interpolation regime. CoRR Aditya Varre, Loucas Pillaud-Vivien, Nicolas Flammarion
2021	J	`jnl`	Linear Speedup in Personalized Collaborative Learning. CoRR El Mahdi Chayti, Sai Praneeth Karimireddy, Sebastian U. Stich, Nicolas Flammarion, Martin Jaggi
2021	J	`jnl`	On the effectiveness of adversarial training against common corruptions. CoRR Klim Kireev, Maksym Andriushchenko, Nicolas Flammarion
2021	—	`conf`	RobustBench: a standardized adversarial robustness benchmark. NeurIPS Datasets and Benchmarks Francesco Croce, Maksym Andriushchenko, Vikash Sehwag, Edoardo Debenedetti, Nicolas Flammarion, Mung Chiang, Prateek Mittal, Matthias Hein
2021	A*	`conf`	Sequential Algorithms for Testing Closeness of Distributions. NeurIPS Aadil Oufkir, Omar Fawzi, Nicolas Flammarion, Aurélien Garivier
2020	A*	`conf`	On Convergence-Diagnostic based Step Sizes for Stochastic Gradient Descent. ICML Scott Pesme, Aymeric Dieuleveut, Nicolas Flammarion
2020	J	`jnl`	On Convergence-Diagnostic based Step Sizes for Stochastic Gradient Descent. CoRR Scott Pesme, Aymeric Dieuleveut, Nicolas Flammarion
2020	A*	`conf`	Online Robust Regression via SGD on the l1 loss. NeurIPS Scott Pesme, Nicolas Flammarion
2020	J	`jnl`	Online Robust Regression via SGD on the l1 loss. CoRR Scott Pesme, Nicolas Flammarion
2020	J	`jnl`	Optimal Robust Linear Regression in Nearly Linear Time. CoRR Yeshwanth Cherapanamjeri, Efe Aras, Nilesh Tripuraneni, Michael I. Jordan, Nicolas Flammarion, Peter L. Bartlett
2020	J	`jnl`	RobustBench: a standardized adversarial robustness benchmark. CoRR Francesco Croce, Maksym Andriushchenko, Vikash Sehwag, Nicolas Flammarion, Mung Chiang, Prateek Mittal, Matthias Hein
2020	J	`jnl`	Sparse-RS: a versatile framework for query-efficient sparse black-box adversarial attacks. CoRR Francesco Croce, Maksym Andriushchenko, Naman D. Singh, Nicolas Flammarion, Matthias Hein
2020	—	`conf`	Square Attack: A Query-Efficient Black-Box Adversarial Attack via Random Search. ECCV (23) Maksym Andriushchenko, Francesco Croce, Nicolas Flammarion, Matthias Hein
2020	A*	`conf`	Understanding and Improving Fast Adversarial Training. NeurIPS Maksym Andriushchenko, Nicolas Flammarion
2020	J	`jnl`	Understanding and Improving Fast Adversarial Training. CoRR Maksym Andriushchenko, Nicolas Flammarion
2019	J	`jnl`	An Efficient Sampling Algorithm for Non-smooth Composite Potentials. CoRR Wenlong Mou, Nicolas Flammarion, Martin J. Wainwright, Peter L. Bartlett
2019	A*	`conf`	Escaping from saddle points on Riemannian manifolds. NeurIPS Yue Sun, Nicolas Flammarion, Maryam Fazel
2019	J	`jnl`	Escaping from saddle points on Riemannian manifolds. CoRR Yue Sun, Nicolas Flammarion, Maryam Fazel
2019	A*	`conf`	Fast Mean Estimation with Sub-Gaussian Rates. COLT Yeshwanth Cherapanamjeri, Nicolas Flammarion, Peter L. Bartlett
2019	J	`jnl`	Fast Mean Estimation with Sub-Gaussian Rates. CoRR Yeshwanth Cherapanamjeri, Nicolas Flammarion, Peter L. Bartlett
2019	J	`jnl`	Is There an Analog of Nesterov Acceleration for MCMC? CoRR Yi-An Ma, Niladri S. Chatterji, Xiang Cheng, Nicolas Flammarion, Peter L. Bartlett, Michael I. Jordan
2019	J	`jnl`	Square Attack: a query-efficient black-box adversarial attack via random search. CoRR Maksym Andriushchenko, Francesco Croce, Nicolas Flammarion, Matthias Hein
2018	A*	`conf`	Averaging Stochastic Gradient Descent on Riemannian Manifolds. COLT Nilesh Tripuraneni, Nicolas Flammarion, Francis R. Bach, Michael I. Jordan
2018	J	`jnl`	Averaging Stochastic Gradient Descent on Riemannian Manifolds. CoRR Nilesh Tripuraneni, Nicolas Flammarion, Francis R. Bach, Michael I. Jordan
2018	J	`jnl`	Gen-Oja: A Simple and Efficient Algorithm for Streaming Generalized Eigenvector Computation. CoRR Kush Bhatia, Aldo Pacchiano, Nicolas Flammarion, Peter L. Bartlett, Michael I. Jordan
2018	A*	`conf`	Gen-Oja: Simple & Efficient Algorithm for Streaming Generalized Eigenvector Computation. NeurIPS Kush Bhatia, Aldo Pacchiano, Nicolas Flammarion, Peter L. Bartlett, Michael I. Jordan
2018	A*	`conf`	On the Theory of Variance Reduction for Stochastic Gradient Monte Carlo. ICML Niladri S. Chatterji, Nicolas Flammarion, Yi-An Ma, Peter L. Bartlett, Michael I. Jordan
2018	J	`jnl`	On the Theory of Variance Reduction for Stochastic Gradient Monte Carlo. CoRR Niladri S. Chatterji, Nicolas Flammarion, Yi-An Ma, Peter L. Bartlett, Michael I. Jordan
2018	J	`jnl`	Sampling Can Be Faster Than Optimization. CoRR Yi-An Ma, Yuansi Chen, Chi Jin, Nicolas Flammarion, Michael I. Jordan
2017	J	`jnl`	Harder, Better, Faster, Stronger Convergence Rates for Least-Squares Regression. J. Mach. Learn. Res. Aymeric Dieuleveut, Nicolas Flammarion, Francis R. Bach
2017	J	`jnl`	Robust Discriminative Clustering with Sparse Regularizers. J. Mach. Learn. Res. Nicolas Flammarion, Balamurugan Palaniappan, Francis R. Bach
2017	—	`—`	Stochastic Approximation and Least-Squares Regression, with Applications to Machine Learning. (Approximation Stochastique et Régression par Moindres Carrés : Applications en Apprentissage Automatique). Nicolas Flammarion
2017	A*	`conf`	Stochastic Composite Least-Squares Regression with Convergence Rate $O(1/n)$. COLT Nicolas Flammarion, Francis R. Bach
2016	J	`jnl`	Harder, Better, Faster, Stronger Convergence Rates for Least-Squares Regression. CoRR Aymeric Dieuleveut, Nicolas Flammarion, Francis R. Bach
2016	J	`jnl`	Robust Discriminative Clustering with Sparse Regularizers. CoRR Nicolas Flammarion, Balamurugan Palaniappan, Francis R. Bach
2015	A*	`conf`	From Averaging to Acceleration, There is Only a Step-size. COLT Nicolas Flammarion, Francis R. Bach