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 301–350 of 423 papers

TitleStatusHype
Learning Surrogate Losses—0
Learning Theory for Kernel Bilevel Optimization—0
Learning to Defend by Learning to Attack—0
Learning to Generalize to Unseen Tasks with Bilevel Optimization—0
Learning to Learn Semantic Factors in Heterogeneous Image Classification—0
Learning to Rank for Active Learning via Multi-Task Bilevel Optimization—0
Learning to Re-weight Examples with Optimal Transport for Imbalanced Classification—0
Learning Variational Models with Unrolling and Bilevel Optimization—0
Learning with Limited Samples -- Meta-Learning and Applications to Communication Systems—0
Learn to Bid as a Price-Maker Wind Power Producer—0
Less or More From Teacher: Exploiting Trilateral Geometry For Knowledge Distillation—0
Generalists vs. Specialists: Evaluating LLMs on Highly-Constrained Biophysical Sequence Optimization Tasks—0
Load Encoding for Learning AC-OPF—0
Local Stochastic Bilevel Optimization with Momentum-Based Variance Reduction—0
Lower Bounds and Accelerated Algorithms for Bilevel Optimization—0
MBL-CPDP: A Multi-objective Bilevel Method for Cross-Project Defect Prediction via Automated Machine Learning—0
Meta-Reinforcement Learning with Universal Policy Adaptation: Provable Near-Optimality under All-task Optimum Comparator—0
MetaStyle: Three-Way Trade-Off Among Speed, Flexibility, and Quality in Neural Style Transfer—0
Meta-Wrapper: Differentiable Wrapping Operator for User Interest Selection in CTR Prediction—0
MoML: Online Meta Adaptation for 3D Human Motion Prediction—0
Multi-Agent Reinforcement Learning for Markov Routing Games: A New Modeling Paradigm For Dynamic Traffic Assignment—0
Multi-block Min-max Bilevel Optimization with Applications in Multi-task Deep AUC Maximization—0
Multi-period Mean-Buffered Probability of Exceedance in Defined Contribution Portfolio Optimization—0
Multi-task Additive Models for Robust Estimation and Automatic Structure Discovery—0
Near-Optimal Nonconvex-Strongly-Convex Bilevel Optimization with Fully First-Order Oracles—0
Network Utility Maximization with Unknown Utility Functions: A Distributed, Data-Driven Bilevel Optimization Approach—0
Non-Convex Bilevel Optimization with Time-Varying Objective Functions—0
On Finding Small Hyper-Gradients in Bilevel Optimization: Hardness Results and Improved Analysis—0
DARTS-PRIME: Regularization and Scheduling Improve Constrained Optimization in Differentiable NAS—0
One-step differentiation of iterative algorithms—0
On Implicit Bias in Overparameterized Bilevel Optimization—0
Online Nonconvex Bilevel Optimization with Bregman Divergences—0
On Momentum-Based Gradient Methods for Bilevel Optimization with Nonconvex Lower-Level—0
On Penalty Methods for Nonconvex Bilevel Optimization and First-Order Stochastic Approximation—0
On Stability and Generalization of Bilevel Optimization Problem—0
Unified Convergence Analysis for Adaptive Optimization with Moving Average Estimator—0
On the Bias-Variance-Cost Tradeoff of Stochastic Optimization—0
On the Communication Complexity of Decentralized Bilevel Optimization—0
On the Complexity of First-Order Methods in Stochastic Bilevel Optimization—0
On the Convergence of Adam-Type Algorithm for Bilevel Optimization under Unbounded Smoothness—0
On the Convergence of Momentum-Based Algorithms for Federated Bilevel Optimization Problems—0
Federated Multi-Sequence Stochastic Approximation with Local Hypergradient EstimationCode0
Sign-MAML: Efficient Model-Agnostic Meta-Learning by SignSGDCode0
Optimizing Decomposition for Optimal Claim VerificationCode0
Few-shot Backdoor Attacks via Neural Tangent KernelsCode0
Loss Distillation via Gradient Matching for Point Cloud Completion with Weighted Chamfer DistanceCode0
Bilevel Generative Learning for Low-Light VisionCode0
Exact Certification of (Graph) Neural Networks Against Label PoisoningCode0
MAP: Towards Balanced Generalization of IID and OOD through Model-Agnostic AdaptersCode0
BILBO: BILevel Bayesian OptimizationCode0
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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