pmichel31415 / P-DRO
Code for the papers "Modeling the Second Player in Distributionally Robust Optimization" and "Distributionally Robust Models with Parametric Likelihood Ratios"
☆27Updated 2 years ago
Alternatives and similar repositories for P-DRO:
Users that are interested in P-DRO are comparing it to the libraries listed below
- PyTorch implementation of efficient algorithms for DRO with CVaR and Chi-Square uncertainty sets☆59Updated 2 years ago
- Code for paper: End-to-end Stochastic Optimization with Energy-based Model☆16Updated 2 years ago
- Distributional and Outlier Robust Optimization (ICML 2021)☆26Updated 3 years ago
- [ICLR 2022] "Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How" by Yuning You, Yue Cao, Tianl…☆13Updated 2 years ago
- Code for "Decision-Focused Learning without Differentiable Optimization: Learning Locally Optimized Decision Losses"☆27Updated last year
- [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
- ☆31Updated 2 years ago
- Experiments with distributionally robust optimization (DRO) for deep neural networks☆35Updated 5 years ago
- The code for our NeurIPS 2021 paper "Kernelized Heterogeneous Risk Minimization".☆12Updated 3 years ago
- ☆15Updated 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
- ☆10Updated 2 years ago
- ☆24Updated last year
- ☆29Updated last year
- Repo for the paper "Landscape Surrogate Learning Decision Losses for Mathematical Optimization Under Partial Information"☆36Updated last year
- Benchmark for bi-level optimization solvers☆43Updated 3 months ago
- Exact Pareto Optimal solutions for preference based Multi-Objective Optimization☆63Updated 2 years ago
- ☆15Updated 4 years ago
- Code for Accelerated Linearized Laplace Approximation for Bayesian Deep Learning (ELLA, NeurIPS 22')☆16Updated 2 years ago
- Principled learning method for Wasserstein distributionally robust optimization with local perturbations (ICML 2020)☆21Updated last year
- Gradient Estimation with Discrete Stein Operators (NeurIPS 2022)☆17Updated last year
- Post-processing for fair classification☆13Updated 2 months ago
- Improving Transformation Invariance in Contrastive Representation Learning☆13Updated 4 years ago
- Source code for the Paper: CombOptNet: Fit the Right NP-Hard Problem by Learning Integer Programming Constraints}☆72Updated 2 years ago
- Accompanying code for our NeurIPS 2019 paper☆12Updated 5 years ago
- Code for A General Recipe for Likelihood-free Bayesian Optimization, ICML 2022☆44Updated 2 years ago
- General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.☆38Updated 2 years ago
- Source code for paper Conservative Uncertainty Estimation By Fitting Prior Networks (ICLR 2020)☆21Updated 2 years ago
- Energy-Based Models for Continual Learning Official Repository (PyTorch)☆40Updated 2 years ago
- Learning a Latent Search Space for Routing Problems using Variational Autoencoders☆25Updated 3 years ago