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
Unraveling the Impact of Heterophilic Structures on Graph Positive-Unlabeled Learning—0
Using Hindsight to Anchor Past Knowledge in Continual Learning—0
Using Machine Teaching to Identify Optimal Training-Set Attacks on Machine Learners—0
Using Synthetic Data to Mitigate Unfairness and Preserve Privacy in Collaborative Machine Learning—0
Valuing Distributed Energy Resources for Non-Wires Alternatives—0
Whiteness-based bilevel learning of regularization parameters in imaging—0
A Bayesian-Symbolic Approach to Reasoning and Learning in Intuitive Physics—0
Will Bilevel Optimizers Benefit from Loops—0
Accelerated Fully First-Order Methods for Bilevel and Minimax Optimization—0
Accelerating Inexact HyperGradient Descent for Bilevel Optimization—0
A Challenge in Reweighting Data with Bilevel Optimization—0
Achieving Linear Speedup in Non-IID Federated Bilevel Learning—0
Achieving O(ε^-1.5) Complexity in Hessian/Jacobian-free Stochastic Bilevel Optimization—0
A Communication and Computation Efficient Fully First-order Method for Decentralized Bilevel Optimization—0
A Primal-Dual Approach to Bilevel Optimization with Multiple Inner Minima—0
Adaptive Mirror Descent Bilevel Optimization—0
Adaptive Training Distributions with Scalable Online Bilevel Optimization—0
AdaSTE: An Adaptive Straight-Through Estimator to Train Binary Neural Networks—0
A Data-Driven Sensor Placement Approach for Detecting Voltage Violations in Distribution Systems—0
Adversarial Nonnegative Matrix Factorization—0
A First-order Generative Bilevel Optimization Framework for Diffusion Models—0
A Fully First-Order Method for Stochastic Bilevel Optimization—0
A Fully Single Loop Algorithm for Bilevel Optimization without Hessian Inverse—0
A Game-theoretic Machine Learning Approach for Revenue Maximization in Sponsored Search—0
A Generalized Alternating Method for Bilevel Learning under the Polyak-Łojasiewicz Condition—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