SOTAVerified

Bilevel Optimization

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

Papers

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Showing 276–300 of 423 papers

TitleStatusHype
Target-aware Dual Adversarial Learning and a Multi-scenario Multi-Modality Benchmark to Fuse Infrared and Visible for Object DetectionCode2
Robust Structured Declarative Classifiers for 3D Point Clouds: Defending Adversarial Attacks with Implicit GradientsCode1
Robust Pivoting: Exploiting Frictional Stability Using Bilevel Optimization—0
Min-Max Bilevel Multi-objective Optimization with Applications in Machine LearningCode0
A Primal-Dual Approach to Bilevel Optimization with Multiple Inner Minima—0
Efficiently Escaping Saddle Points in Bilevel Optimization—0
Bilevel Optimization with a Lower-level Contraction: Optimal Sample Complexity without Warm-startCode1
Deep invariant networks with differentiable augmentation layersCode1
Single Time-scale Actor-critic Method to Solve the Linear Quadratic Regulator with Convergence Guarantees—0
A framework for bilevel optimization that enables stochastic and global variance reduction algorithmsCode1
Joint Differentiable Optimization and Verification for Certified Reinforcement Learning—0
Bilevel Online Deep Learning in Non-stationary Environment—0
A unified algorithm framework for mean-variance optimization in discounted Markov decision processes—0
Modeling Mask Uncertainty in Hyperspectral Image ReconstructionCode1
On Automatic Data Augmentation for 3D Point Cloud ClassificationCode0
A Fully Single Loop Algorithm for Bilevel Optimization without Hessian Inverse—0
A Novel Convergence Analysis for Algorithms of the Adam Family—0
AdaSTE: An Adaptive Straight-Through Estimator to Train Binary Neural Networks—0
SBO-RNN: Reformulating Recurrent Neural Networks via Stochastic Bilevel Optimization—0
Closing the Gap: Tighter Analysis of Alternating Stochastic Gradient Methods for Bilevel Problems—0
A Bayesian-Symbolic Approach to Reasoning and Learning in Intuitive Physics—0
On the Bias-Variance-Cost Tradeoff of Stochastic Optimization—0
Amortized Implicit Differentiation for Stochastic Bilevel OptimizationCode0
BiGrad: Differentiating through Bilevel Optimization Programming—0
Bilevel learning of l1-regularizers with closed-form gradients(BLORC)—0
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All datasetsEquilibrium-Traffic-Networks/AnaheimEquilibrium-Traffic-Networks/Eastern MassachusettsEquilibrium-Traffic-Networks/Sioux Falls

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GIN-GAOptimality Gap0.21—Unverified
#ModelMetricClaimedVerifiedStatus
1GIN-GAOptimality Gap0.48—Unverified
#ModelMetricClaimedVerifiedStatus
1GIN-GAOptimality Gap1.44—Unverified