tml-epfl / sgd-sparse-featuresLinks
SGD with large step sizes learns sparse features [ICML 2023]
☆32Updated 2 years ago
Alternatives and similar repositories for sgd-sparse-features
Users that are interested in sgd-sparse-features are comparing it to the libraries listed below
Sorting:
- ☆16Updated 2 years ago
- ☆36Updated last year
- Official code for "In Search of Robust Measures of Generalization" (NeurIPS 2020)☆28Updated 4 years ago
- Pytorch optimizers implementing Hilbert Constrained Gradient Descent☆19Updated 6 years ago
- ☆18Updated 2 years ago
- Implementations of orthogonal and semi-orthogonal convolutions in the Fourier domain with applications to adversarial robustness☆46Updated 4 years ago
- Towards Understanding Sharpness-Aware Minimization [ICML 2022]☆35Updated 3 years ago
- CIFAR-5m dataset☆39Updated 4 years ago
- ☆38Updated 4 years ago
- A modern look at the relationship between sharpness and generalization [ICML 2023]☆43Updated last year
- Training vision models with full-batch gradient descent and regularization☆37Updated 2 years ago
- ☆25Updated 5 years ago
- Pytorch code for "Improving Self-Supervised Learning by Characterizing Idealized Representations"☆41Updated 2 years ago
- Code for the CVPR 2021 paper: Understanding Failures of Deep Networks via Robust Feature Extraction☆36Updated 3 years ago
- Learning perturbation sets for robust machine learning☆65Updated 3 years ago
- ☆19Updated 3 years ago
- ☆55Updated 4 years ago
- Code for "The Intrinsic Dimension of Images and Its Impact on Learning" - ICLR 2021 Spotlight https://openreview.net/forum?id=XJk19XzGq2J☆69Updated last year
- Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"☆25Updated 3 years ago
- ☆62Updated 4 years ago
- Fine-grained ImageNet annotations☆29Updated 5 years ago
- [JMLR] TRADES + random smoothing for certifiable robustness☆14Updated 4 years ago
- Gradient Starvation: A Learning Proclivity in Neural Networks☆61Updated 4 years ago
- A simple Jax implementation of influence functions.☆16Updated last year
- Data for "Datamodels: Predicting Predictions with Training Data"☆97Updated 2 years ago
- An empirical investigation of deep learning theory☆16Updated 5 years ago
- Notebooks for managing NeurIPS 2014 and analysing the NeurIPS experiment.☆11Updated last year
- Source code of "What can linearized neural networks actually say about generalization?☆20Updated 3 years ago
- ☆41Updated 2 years ago
- [AAAI 2020 Oral] Low-variance Black-box Gradient Estimates for the Plackett-Luce Distribution☆38Updated 4 years ago