VITA-Group / L2O-Training-Techniques
[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
☆26Updated 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
- [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
- ☆17Updated 3 years ago
- Pytorch version of NIPS'16 "Learning to learn by gradient descent by gradient descent"☆67Updated last year
- "Learning to learn by gradient descent by gradient descent "by PyTorch -- a simple re-implementation.☆60Updated 5 years ago
- Distributional and Outlier Robust Optimization (ICML 2021)☆27Updated 3 years ago
- Learning To Stop While Learning To Predict☆34Updated 2 years ago
- Example code for paper "Bilevel Optimization: Nonasymptotic Analysis and Faster Algorithms"☆47Updated 3 years ago
- Official PyTorch implementation of "EvoGrad: Efficient Gradient-Based Meta-Learning and Hyperparameter Optimization"☆21Updated 3 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
- Exact Pareto Optimal solutions for preference based Multi-Objective Optimization☆63Updated 2 years ago
- ☆32Updated 2 years ago
- [NeurIPS 2021 | AIJ 2024] Multi-Objective Meta Learning☆14Updated 9 months ago
- This is the official repo for the experiments in the paper "Bilevel Programming for Hyperparameter Optimization and Meta-Learning"☆30Updated 6 years ago
- Bi-level Optimization for Advanced Deep Learning☆45Updated 3 years ago
- The code for our NeurIPS 2021 paper "Kernelized Heterogeneous Risk Minimization".☆12Updated 3 years ago
- [ICLR 2022] "Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How" by Yuning You, Yue Cao, Tianl…☆14Updated 2 years ago
- This is the official implementation of the ICML 2023 paper - Can Forward Gradient Match Backpropagation ?☆12Updated last year
- Code for "Decision-Focused Learning without Differentiable Optimization: Learning Locally Optimized Decision Losses"☆28Updated last year
- A PyTorch implementation of "Meta-Amortized Variational Inference and Learning" (https://arxiv.org/abs/1902.01950)☆14Updated 5 years ago
- Coresets via Bilevel Optimization☆65Updated 4 years ago
- This is the official implementation for COSMOS: a method to learn Pareto fronts that scales to large datasets and deep models.☆39Updated 3 years ago
- Efficient joint input optimization and inference with DEQ☆10Updated 3 years ago
- Code Repository for NeurIPS 2021 accepted paper, named "Torwards Gradient-based Bilevel Optimization with non-convex Followers and Beyond…☆10Updated 3 years ago
- Code for the paper "Let’s Make Block Coordinate Descent Go Fast"☆48Updated last year
- Implementation of [Progressive Neural Networks](https://arxiv.org/abs/1606.04671) using Pytorch Framework☆52Updated 5 years ago
- Code for Global Convergence of Block Coordinate Descent in Deep Learning (ICML 2019)☆37Updated 5 years ago
- Code for the paper Adaptive Auxiliary Task Weighting for Reinforcement Learning☆26Updated 4 years ago
- Meta learning for generative models.☆16Updated 5 years ago
- This repository contains implementations of the paper, Bayesian Model-Agnostic Meta-Learning.☆60Updated 5 years ago
- [ICLR '21] Interpretable Neural Architecture Search using Bayesian Optimisation with Weisfiler-Lehman Kernel (NAS-BOWL)☆24Updated 3 years ago