Baijiong-Lin / MOML
[NeurIPS 2021 | AIJ 2024] Multi-Objective Meta Learning
☆14Updated 9 months ago
Alternatives and similar repositories for MOML
Users that are interested in MOML are comparing it to the libraries listed below
Sorting:
- Exact Pareto Optimal solutions for preference based Multi-Objective Optimization☆64Updated 2 years ago
- ☆35Updated last year
- ☆17Updated 3 years ago
- A collection of the pytorch implementation of neural bandit algorithm includes neuralUCB(Neural Contextual Bandits with UCB-based Explora…☆14Updated 3 years ago
- Code for "Decision-Focused Learning without Differentiable Optimization: Learning Locally Optimized Decision Losses"☆27Updated last year
- ☆70Updated 8 months 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
- [NeurIPS 2020 Spotlight Oral] "Training Stronger Baselines for Learning to Optimize", Tianlong Chen*, Weiyi Zhang*, Jingyang Zhou, Shiyu …☆26Updated 3 years ago
- Code for the papers "Modeling the Second Player in Distributionally Robust Optimization" and "Distributionally Robust Models with Paramet…☆28Updated 3 years ago
- Official implementation of Learning The Pareto Front With HyperNetworks [ICLR 2021]☆102Updated 3 years ago
- Bi-level Optimization for Advanced Deep Learning☆45Updated 3 years ago
- Official implementation of ICML'24 paper "Offline Multi-Objective Optimization".☆19Updated 7 months ago
- A comprehensive list of gradient-based multi-objective optimization algorithms in deep learning.☆58Updated 2 months ago
- Code for the Population-Based Bandits Algorithm, presented at NeurIPS 2020.☆20Updated 4 years ago
- Implementation of NeurIPS2021 paper <On Effective Scheduling of Model-based Reinforcement Learning>☆13Updated 3 years ago
- LibMOON is a standard and flexible framework to study gradient-based multiobjective optimization.☆96Updated last month
- Official implementation of NeurIPS'22 paper "Monte Carlo Tree Search based Variable Selection for High-Dimensional Bayesian Optimization"☆39Updated 2 years ago
- FlexiBO: Cost-Aware Multi-Objective Optimization of Deep Neural Networks☆14Updated 2 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
- Code for paper: End-to-end Stochastic Optimization with Energy-based Model☆16Updated 2 years ago
- Official repository of "Pareto Manifold Learning: Tackling multiple tasks via ensembles of single-task models" [ICML 2023]☆16Updated 4 months ago
- [AAAI-23] Improving Pareto Front Learning via Multi-Sample Hypernetworks☆9Updated 8 months ago
- Code release for "Supported Policy Optimization for Offline Reinforcement Learning" (NeurIPS 2022), https://arxiv.org/abs/2202.06239☆21Updated last year
- Code for Neural Information Processing Systems (NeurIPS) 2019 paper: Pareto Multi-Task Learning☆138Updated 5 years ago
- ☆11Updated 9 months ago
- Release code for ICML2020 Knowing The What But Not The Where in Bayesian Optimization☆15Updated 2 years ago
- Multi-Objective Reinforcement Learning sandbox☆10Updated 3 years ago
- An official JAX-based code for our NeuraLCB paper, "Offline Neural Contextual Bandits: Pessimism, Optimization and Generalization", ICLR…☆14Updated 3 years ago
- Code accompanying https://arxiv.org/abs/1802.02219☆18Updated 2 years ago
- [ICML 2023] Learning for Edge-Weighted Online Bipartite Matching with Robustness Guarantees☆10Updated last year