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Optimization Science

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Optimization Science

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Research Frontiers in Bilevel Optimization Methods

Algorithmic approaches for nested optimization problems with applications to hyperparameter tuning and meta-learning.

Implicit Differentiation in High-Dimensional Bilevel Games
Bilevel Optimization at the Edge of Non-Convexity
Federated Learning Through Nested Optimization Hierarchies
Hypergradient Computation Across Stochastic Bilevel Landscapes
Equilibrium Finding in Competitive Bilevel Structures
Meta-Learning via Bilevel Gradient Dynamics
Distributed Bilevel Algorithms Under Communication Constraints
Adversarial Robustness Through Bilevel Minimax Optimization
Bilevel Optimization in Neural Architecture Search
Second-Order Convergence in Coupled Optimization Hierarchies

All Optimization Science PhD categories