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Bilevel Optimization
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Bilevel Optimization is a branch of optimization, which contains a nested optimization problem within the constraints of the outer optimization problem. The outer optimization task is usually referred as the upper level task, and the nested inner optimization task is referred as the lower level task. The lower level problem appears as a constraint, such that only an optimal solution to the lower level optimization problem is a possible feasible candidate to the upper level optimization problem.
Source: Efficient Evolutionary Algorithm for Single-Objective Bilevel Optimization
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Cinofix/beta_poisoning
공식 코드The Hammer and the Nut: Is Bilevel Optimization Really Needed to Poison Linear Classifiers?
https://github.com/ElementAI/bilevel_augment
공식 코드Learning Data Augmentation with Online Bilevel Optimization for Image Classification
https://github.com/Haoran-S/TSP_CL
공식 코드https://github.com/JunjieYang97/MRVRBO
공식 코드https://github.com/KaidongLi/pytorch-LatticePointClassifier
공식 코드https://github.com/Kyubyong/sudoku
공식 코드OptNet: Differentiable Optimization as a Layer in Neural Networks
https://github.com/LIONS-EPFL/BiSAM
공식 코드Improving SAM Requires Rethinking its Optimization Formulation
https://github.com/Liuyuan999/Penalty_Based_Lagrangian_Bilevel
공식 코드A Primal-Dual-Assisted Penalty Approach to Bilevel Optimization with Coupled Constraints
https://github.com/MLOPTPSU/FedTorch
공식 코드https://github.com/MingruiLiu-ML-Lab/Single-Loop-bilevel-Optimizer-under-Unbounded-Smoothness
공식 코드https://github.com/MinkaiXu/ConfVAE-ICML21
공식 코드An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming
https://github.com/MohammadSadeghSalehi/ISGD
공식 코드https://github.com/MohammadSadeghSalehi/MAID
공식 코드https://github.com/PingchuanMa/SGA
공식 코드LLM and Simulation as Bilevel Optimizers: A New Paradigm to Advance Physical Scientific Discovery
https://github.com/QB3/sparse-ho
공식 코드Implicit differentiation for fast hyperparameter selection in non-smooth convex learning
https://github.com/Raymond30/CG-BiO
공식 코드A Conditional Gradient-based Method for Simple Bilevel Optimization with Convex Lower-level Problem
https://github.com/Rayzhangzirui/BILO
공식 코드BiLO: Bilevel Local Operator Learning for PDE inverse problems
https://github.com/RosettaWYzhang/AdaPC
공식 코드On Automatic Data Augmentation for 3D Point Cloud Classification
https://github.com/SewoongLab/ntk-backdoor
공식 코드https://github.com/TaoShuchang/AdvImmune
공식 코드Adversarial Immunization for Certifiable Robustness on Graphs
https://github.com/TinfoilHat0/BiFair
공식 코드Fair Machine Learning under Limited Demographically Labeled Data
https://github.com/VILA-Lab/SRe2L
공식 코드Squeeze, Recover and Relabel: Dataset Condensation at ImageNet Scale From A New Perspective
https://github.com/Wenlin-Chen/ADKF-IFT
공식 코드Meta-learning Adaptive Deep Kernel Gaussian Processes for Molecular Property Prediction
https://github.com/akshaymehra24/poisoning_certified_defenses
공식 코드How Robust are Randomized Smoothing based Defenses to Data Poisoning?
https://github.com/amberyzheng/bloomgml
공식 코드BloomGML: Graph Machine Learning through the Lens of Bilevel Optimization
https://github.com/andyjm3/rhgd
공식 코드A Framework for Bilevel Optimization on Riemannian Manifolds
https://github.com/anuraganands/Single-objective-Bi-level-with-ICHEA--BICHEA-
공식 코드Optimistic variants of single-objective bilevel optimization for evolutionary algorithms
https://github.com/anzhang314/rescore
공식 코드Boosting Differentiable Causal Discovery via Adaptive Sample Reweighting
https://github.com/arghosh/bobcat
공식 코드BOBCAT: Bilevel Optimization-Based Computerized Adaptive Testing
https://github.com/baithebest/samc
공식 코드https://github.com/benchopt/benchmark_bilevel
공식 코드https://github.com/bojianhou/oagd
공식 코드Online Bilevel Optimization: Regret Analysis of Online Alternating Gradient Methods
https://github.com/callous-youth/betak
공식 코드https://github.com/cedricrommel/augnet
공식 코드Deep invariant networks with differentiable augmentation layers
https://github.com/chaoyanghe/MiLeNAS
공식 코드MiLeNAS: Efficient Neural Architecture Search via Mixed-Level Reformulation
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