{"total":17,"rows":[{"id":"2103.04628","title":"Personalized Federated Learning using Hypernetworks","created":"2021-03-08","cited_by_count":212,"area":null},{"id":"2101.11517","title":"Investigating Bi-Level Optimization for Learning and Vision from a Unified Perspective: A Survey and Beyond","created":"2021-01-27","cited_by_count":153,"area":null},{"id":"2312.04528","title":"Using Large Language Models for Hyperparameter Optimization","created":"2023-12-07","cited_by_count":71,"area":null},{"id":"2102.03926","title":"Lower Bounds and Accelerated Algorithms for Bilevel Optimization","created":"2021-02-07","cited_by_count":46,"area":null},{"id":"2110.07004","title":"On the Convergence Theory for Hessian-Free Bilevel Algorithms","created":"2021-10-13","cited_by_count":35,"area":null},{"id":"2212.14032","title":"On Implicit Bias in Overparameterized Bilevel Optimization","created":"2022-12-28","cited_by_count":30,"area":null},{"id":"2207.11719","title":"Gradient-based Bi-level Optimization for Deep Learning: A Survey","created":"2022-07-24","cited_by_count":26,"area":null},{"id":"2403.20233","title":"Functional Bilevel Optimization for Machine Learning","created":"2024-03-29","cited_by_count":20,"area":null},{"id":"2212.03905","title":"Multi-Rate VAE: Train Once, Get the Full Rate-Distortion Curve","created":"2022-12-07","cited_by_count":18,"area":null},{"id":"2306.14853","title":"Near-Optimal Nonconvex-Strongly-Convex Bilevel Optimization with Fully First-Order Oracles","created":"2023-06-26","cited_by_count":17,"area":null},{"id":"2207.02829","title":"Online Bilevel Optimization: Regret Analysis of Online Alternating Gradient Methods","created":"2022-07-06","cited_by_count":15,"area":null},{"id":"2406.18630","title":"Improving Hyperparameter Optimization with Checkpointed Model Weights","created":"2024-06-26","cited_by_count":5,"area":null},{"id":"2301.08830","title":"ApproxED: Approximate exploitability descent via learned best responses","created":"2023-01-20","cited_by_count":1,"area":null},{"id":"2602.10905","title":"Natural Hypergradient Descent: Algorithm Design, Convergence Analysis, and Parallel Implementation","created":"2026-02-11","cited_by_count":1,"area":null},{"id":"2205.08231","title":"Hyper-Learning for Gradient-Based Batch Size Adaptation","created":"2022-05-17","cited_by_count":0,"area":null},{"id":"2212.06150","title":"CPMLHO:Hyperparameter Tuning via Cutting Plane and Mixed-Level Optimization","created":"2022-12-11","cited_by_count":0,"area":null},{"id":"2308.10711","title":"Relax and penalize: a new bilevel approach to mixed-binary hyperparameter optimization","created":"2023-08-21","cited_by_count":0,"area":null}],"next_cursor":null}