kilianFatras / variance_reduced_neural_networks
Implementation of SVRG and SAGA optimization algorithms for deep learning topics.
☆73Updated 4 years ago
Alternatives and similar repositories for variance_reduced_neural_networks
Users that are interested in variance_reduced_neural_networks are comparing it to the libraries listed below
Sorting:
- Implementation of an efficient variant of SVRG that relies on mini-batching implemented in Pytorch☆26Updated 6 years ago
- ☆58Updated 2 years ago
- Rethinking Bias-Variance Trade-off for Generalization of Neural Networks☆49Updated 4 years ago
- ☆122Updated 11 months ago
- Implementation of SVRG for training neural networks☆21Updated 5 years ago
- Code for Global Convergence of Block Coordinate Descent in Deep Learning (ICML 2019)☆37Updated 5 years ago
- Implementation of Stochastic Variance Reduced Gradient Descent☆8Updated 7 years ago
- Implementation of Minimax Pareto Fairness framework☆21Updated 4 years ago
- Example code for paper "Bilevel Optimization: Nonasymptotic Analysis and Faster Algorithms"☆47Updated 3 years ago
- This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).☆49Updated 3 years ago
- LipSDP - Lipschitz Estimation for Neural Networks☆67Updated 3 years ago
- Code for the signSGD paper☆84Updated 4 years ago
- PyTorch implementation of efficient algorithms for DRO with CVaR and Chi-Square uncertainty sets☆60Updated 2 years ago
- Certifying Some Distributional Robustness with Principled Adversarial Training (https://arxiv.org/abs/1710.10571)☆45Updated 7 years ago
- ZOSVRG-BlackBox-Adv☆12Updated 6 years ago
- Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network☆62Updated 5 years ago
- Lipschitz Neural Networks described in "Sorting Out Lipschitz Function Approximation" (ICML 2019).☆56Updated 4 years ago
- PyTorch implementation of FIM and empirical FIM☆60Updated 6 years ago
- Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"☆44Updated 4 years ago
- Tilted Empirical Risk Minimization (ICLR '21)☆59Updated last year
- The codebase for the paper "A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks"☆25Updated 5 years ago
- Official implementation for Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds (NeurIPS, 2021).☆23Updated 2 years ago
- demonstration of the information bottleneck theory for deep learning☆61Updated 7 years ago
- Codes for "Understanding and Accelerating Particle-Based Variational Inference" (ICML-19)☆22Updated 5 years ago
- ☆66Updated 6 years ago
- Hypergradient descent☆146Updated 11 months ago
- SGD with compressed gradients and error-feedback: https://arxiv.org/abs/1901.09847☆30Updated 9 months ago
- Decentralized SGD and Consensus with Communication Compression: https://arxiv.org/abs/1907.09356☆69Updated 4 years ago
- Scaleable input gradient regularization☆22Updated 5 years ago
- Attempt to speed Randomized SVD(Singular Value Decomposition) Using pytorch and it's gnu capabilities.☆17Updated 6 years ago