VITA-Group / L2O-Training-TechniquesLinks
[NeurIPS 2020 Spotlight Oral] "Training Stronger Baselines for Learning to Optimize", Tianlong Chen*, Weiyi Zhang*, Jingyang Zhou, Shiyu Chang, Sijia Liu, Lisa Amini, Zhangyang Wang
☆28Updated 3 years ago
Alternatives and similar repositories for L2O-Training-Techniques
Users that are interested in L2O-Training-Techniques are comparing it to the libraries listed below
Sorting:
- ☆17Updated 3 years ago
- [ICLR 2021] "Learning a Minimax Optimizer: A Pilot Study" by Jiayi Shen*, Xiaohan Chen*, Howard Heaton*, Tianlong Chen, Jialin Liu, Wotao…☆15Updated 3 years ago
- Bi-level Optimization for Advanced Deep Learning☆47Updated 3 years ago
- Example code for paper "Bilevel Optimization: Nonasymptotic Analysis and Faster Algorithms"☆49Updated 3 years ago
- Official PyTorch implementation of "EvoGrad: Efficient Gradient-Based Meta-Learning and Hyperparameter Optimization"☆22Updated 3 years ago
- Code Repository for NeurIPS 2021 accepted paper, named "Torwards Gradient-based Bilevel Optimization with non-convex Followers and Beyond…☆11Updated 3 years ago
- This is the official implementation for COSMOS: a method to learn Pareto fronts that scales to large datasets and deep models.☆39Updated 4 years ago
- Pytorch version of NIPS'16 "Learning to learn by gradient descent by gradient descent"☆67Updated 2 years ago
- ☆15Updated 4 years ago
- Code for the ICML 2021 paper "Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation", Haoxi…☆68Updated 3 years ago
- Code for "Decision-Focused Learning without Differentiable Optimization: Learning Locally Optimized Decision Losses"☆28Updated last year
- Open-L2O: A Comprehensive and Reproducible Benchmark for Learning to Optimize Algorithms☆280Updated 2 years ago
- Official implementation of Learning The Pareto Front With HyperNetworks [ICLR 2021]☆104Updated 3 years ago
- The official implementation of A Unified Game-Theoretic Interpretation of Adversarial Robustness.☆22Updated 3 years ago
- Exact Pareto Optimal solutions for preference based Multi-Objective Optimization☆65Updated 3 years ago
- Distributional and Outlier Robust Optimization (ICML 2021)☆27Updated 4 years ago
- The code for our NeurIPS 2021 paper "Kernelized Heterogeneous Risk Minimization".☆13Updated 3 years ago
- Efficient joint input optimization and inference with DEQ☆10Updated 3 years ago
- Implementation of SVRG and SAGA optimization algorithms for deep learning topics.☆74Updated 4 years ago
- [NeurIPS 2021 | AIJ 2024] Multi-Objective Meta Learning☆15Updated last year
- [ICML 2021] This is the official github repo for training L_inf dist nets with high certified accuracy.☆42Updated 3 years ago
- Certifying Some Distributional Robustness with Principled Adversarial Training (https://arxiv.org/abs/1710.10571)☆45Updated 7 years ago
- Coresets via Bilevel Optimization☆66Updated 4 years ago
- ☆17Updated 4 years ago
- Learning a Latent Search Space for Routing Problems using Variational Autoencoders☆26Updated 4 years ago
- This repository contains implementations of the paper, Bayesian Model-Agnostic Meta-Learning.☆20Updated 2 years ago
- Numerical illustration of a novel analysis framework for consensus-based optimization (CBO) and numerical experiments demonstrating the p…☆20Updated last year
- Code for the Population-Based Bandits Algorithm, presented at NeurIPS 2020.☆20Updated 4 years ago
- Code for our NeurIPS 2020 paper Improving Generalization in Reinforcement Learning with Mixture Regularization☆33Updated 4 years ago
- Official implementation of Auxiliary learning as an Bargaining Game.☆32Updated last year