{"total":20,"rows":[{"id":"2402.03183","title":"Predicting Configuration Performance in Multiple Environments with Sequential Meta-learning","created":"2024-02-05","cited_by_count":17,"area":null},{"id":"2201.07096","title":"Lifelong Dynamic Optimization for Self-Adaptive Systems: Fact or Fiction?","created":"2022-01-18","cited_by_count":16,"area":null},{"id":"2201.08413","title":"Unicorn: Reasoning about Configurable System Performance through the lens of Causality","created":"2022-01-20","cited_by_count":12,"area":null},{"id":"2203.12472","title":"Planning Landscape Analysis for Self-Adaptive Systems","created":"2022-03-23","cited_by_count":12,"area":null},{"id":"2501.00840","title":"Distilled Lifelong Self-Adaptation for Configurable Systems","created":"2025-01-01","cited_by_count":12,"area":null},{"id":"2403.03322","title":"Deep Configuration Performance Learning: A Systematic Survey and Taxonomy","created":"2024-03-05","cited_by_count":8,"area":null},{"id":"2507.08730","title":"Dually Hierarchical Drift Adaptation for Online Configuration Performance Learning","created":"2025-07-11","cited_by_count":8,"area":null},{"id":"2603.19897","title":"Revealing Domain-Spatiality Patterns for Configuration Tuning: Domain Knowledge Meets Fitness Landscapes","created":"2026-03-20","cited_by_count":5,"area":null},{"id":"2103.01755","title":"An Exploratory Study of Log Placement Recommendation in an Enterprise System","created":"2021-03-02","cited_by_count":4,"area":null},{"id":"2301.07690","title":"CaRE: Finding Root Causes of Configuration Issues in Highly-Configurable Robots","created":"2023-01-18","cited_by_count":4,"area":null},{"id":"2409.07629","title":"Dividable Configuration Performance Learning","created":"2024-09-11","cited_by_count":4,"area":null},{"id":"2412.16888","title":"Rethinking Performance Analysis for Configurable Software Systems: A Case Study from a Fitness Landscape Perspective","created":"2024-12-22","cited_by_count":3,"area":null},{"id":"2402.05399","title":"CURE: Simulation-Augmented Auto-Tuning in Robotics","created":"2024-02-08","cited_by_count":2,"area":null},{"id":"2505.07487","title":"Linux Kernel Configurations at Scale: A Dataset for Performance and Evolution Analysis","created":"2025-05-12","cited_by_count":2,"area":null},{"id":"2507.09790","title":"Prompting for Performance: Exploring LLMs for Configuring Software","created":"2025-07-13","cited_by_count":1,"area":null},{"id":"2509.21945","title":"Evaluating Useful Surrogate Models for Configuration Tuning Beyond Accuracy: A Fitness Landscape Analysis Perspective","created":"2025-09-26","cited_by_count":1,"area":null},{"id":"2607.16476","title":"When to Use Which? Benchmarking Optimisers for Configurable Systems under Varying Budgets","created":"2026-07-17","cited_by_count":1,"area":null},{"id":"2212.13359","title":"Uncertainty-Aware Performance Prediction for Highly Configurable Software Systems via Bayesian Neural Networks","created":"2022-12-27","cited_by_count":0,"area":null},{"id":"2509.11000","title":"Hardness, Structural Knowledge, and Opportunity: An Analytical Framework for Modular Performance Modeling","created":"2025-09-13","cited_by_count":0,"area":null},{"id":"2607.00113","title":"SemiScope: Disentangling Classifier Tuning and Joint Optimization in Semi-Supervised Security Classification","created":"2026-06-30","cited_by_count":0,"area":null}],"next_cursor":null}