Nicolas Flammarion
Publications by Year
Research Areas
Stochastic Gradient Optimization Techniques, Sparse and Compressive Sensing Techniques, Markov Chains and Monte Carlo Methods, Adversarial Robustness in Machine Learning, Statistical Methods and Inference
Most-Cited Works
- → RobustBench: a standardized adversarial robustness benchmark(2020)116 cited
- → Sparse-RS: A Versatile Framework for Query-Efficient Sparse Black-Box Adversarial Attacks(2022)92 cited
- → From Averaging to Acceleration, There is Only a Step-size(2015)66 cited
- → Square Attack: A Query-Efficient Black-Box Adversarial Attack via Random Search(2020)49 cited
- → Understanding and Improving Fast Adversarial Training(2020)45 cited
- → Is There an Analog of Nesterov Acceleration for MCMC?(2019)44 cited
- → Is there an analog of Nesterov acceleration for gradient-based MCMC?(2021)41 cited
- → Averaging Stochastic Gradient Descent on Riemannian Manifolds(2018)40 cited
- → Improved bounds for discretization of Langevin diffusions: Near-optimal rates without convexity(2022)36 cited
- → On the Theory of Variance Reduction for Stochastic Gradient Monte Carlo(2018)29 cited