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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 311–320 of 423 papers

TitleStatusHype
Bilevel Online Deep Learning in Non-stationary Environment—0
A unified algorithm framework for mean-variance optimization in discounted Markov decision processes—0
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
Closing the Gap: Tighter Analysis of Alternating Stochastic Gradient Methods for Bilevel Problems—0
On the Bias-Variance-Cost Tradeoff of Stochastic Optimization—0
A Bayesian-Symbolic Approach to Reasoning and Learning in Intuitive Physics—0
SBO-RNN: Reformulating Recurrent Neural Networks via Stochastic Bilevel Optimization—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