{"total":30,"rows":[{"id":"2103.12828","title":"Learning to Optimize: A Primer and A Benchmark","created":"2021-03-23","cited_by_count":208,"area":null},{"id":"2403.12143","title":"Graph Neural Networks for Learning Equivariant Representations of Neural Networks","created":"2024-03-18","cited_by_count":59,"area":null},{"id":"2211.09760","title":"VeLO: Training Versatile Learned Optimizers by Scaling Up","created":"2022-11-17","cited_by_count":57,"area":null},{"id":"2110.05649","title":"Learned Robust PCA: A Scalable Deep Unfolding Approach for High-Dimensional Outlier Detection","created":"2021-10-11","cited_by_count":34,"area":null},{"id":"2203.11860","title":"Practical tradeoffs between memory, compute, and performance in learned optimizers","created":"2022-03-22","cited_by_count":32,"area":null},{"id":"2209.11208","title":"A Closer Look at Learned Optimization: Stability, Robustness, and Inductive Biases","created":"2022-09-22","cited_by_count":30,"area":null},{"id":"2203.06578","title":"Symbolic Learning to Optimize: Towards Interpretability and Scalability","created":"2022-03-13","cited_by_count":16,"area":null},{"id":"2304.11787","title":"B2Opt: Learning to Optimize Black-box Optimization with Little Budget","created":"2023-04-24","cited_by_count":15,"area":null},{"id":"2305.18577","title":"Towards Constituting Mathematical Structures for Learning to Optimize","created":"2023-05-29","cited_by_count":13,"area":null},{"id":"2212.02603","title":"Learning to Optimize in Model Predictive Control","created":"2022-12-05","cited_by_count":11,"area":null},{"id":"2401.03244","title":"Artificial Intelligence for Operations Research: Revolutionizing the Operations Research Process","created":"2024-01-06","cited_by_count":11,"area":null},{"id":"2302.01128","title":"Mnemosyne: Learning to Train Transformers with Transformers","created":"2023-02-02","cited_by_count":9,"area":null},{"id":"2302.11085","title":"Learning to Generalize Provably in Learning to Optimize","created":"2023-02-22","cited_by_count":8,"area":null},{"id":"2310.04590","title":"Deep Model Predictive Optimization","created":"2023-10-06","cited_by_count":7,"area":null},{"id":"2406.00153","title":"$\\mu$LO: Compute-Efficient Meta-Generalization of Learned Optimizers","created":"2024-05-31","cited_by_count":7,"area":null},{"id":"2410.19746","title":"Metamizer: a versatile neural optimizer for fast and accurate physics simulations","created":"2024-10-10","cited_by_count":7,"area":null},{"id":"2211.16268","title":"Learning to Optimize with Dynamic Mode Decomposition","created":"2022-11-29","cited_by_count":5,"area":null},{"id":"2112.10377","title":"Learning for Robust Combinatorial Optimization: Algorithm and Application","created":"2021-12-20","cited_by_count":4,"area":null},{"id":"2209.01083","title":"When Bioprocess Engineering Meets Machine Learning: A Survey from the Perspective of Automated Bioprocess Development","created":"2022-09-02","cited_by_count":4,"area":null},{"id":"2303.00039","title":"M-L2O: Towards Generalizable Learning-to-Optimize by Test-Time Fast Self-Adaptation","created":"2023-02-28","cited_by_count":4,"area":null},{"id":"2501.12670","title":"Celo: Training Versatile Learned Optimizers on a Compute Diet","created":"2025-01-22","cited_by_count":4,"area":null},{"id":"2110.08256","title":"Model-Agnostic Meta-Attack: Towards Reliable Evaluation of Adversarial Robustness","created":"2021-10-13","cited_by_count":3,"area":null},{"id":"2312.02204","title":"Meta-learning Optimizers for Communication-Efficient Learning","created":"2023-12-02","cited_by_count":2,"area":null},{"id":"2405.18222","title":"From Learning to Optimize to Learning Optimization Algorithms","created":"2024-05-28","cited_by_count":2,"area":null},{"id":"2106.02615","title":"Consensus Multiplicative Weights Update: Learning to Learn using Projector-based Game Signatures","created":"2021-06-04","cited_by_count":1,"area":null},{"id":"2203.06474","title":"Optimizer Amalgamation","created":"2022-03-12","cited_by_count":1,"area":null},{"id":"2505.22509","title":"Accelerating Optimization via Differentiable Stopping Time","created":"2025-05-28","cited_by_count":1,"area":null},{"id":"2510.08968","title":"Learning Regularizers: Learning Optimizers that can Regularize","created":"2025-10-10","cited_by_count":0,"area":null},{"id":"2607.06772","title":"Efficient Long-Horizon Learning for Learned Optimization","created":"2026-07-07","cited_by_count":0,"area":null},{"id":"2607.27389","title":"FunL2O: LLM-Guided Feature Function Design for Learning to Optimize","created":"2026-07-29","cited_by_count":0,"area":null}],"next_cursor":null}