{"total":22,"rows":[{"id":"2205.01491","title":"A Comprehensive Survey of Image Augmentation Techniques for Deep Learning","created":"2022-05-03","cited_by_count":97,"area":null},{"id":"2201.01212","title":"AutoBalance: Optimized Loss Functions for Imbalanced Data","created":"2022-01-04","cited_by_count":49,"area":null},{"id":"2202.12513","title":"TeachAugment: Data Augmentation Optimization Using Teacher Knowledge","created":"2022-02-25","cited_by_count":37,"area":null},{"id":"2212.14032","title":"On Implicit Bias in Overparameterized Bilevel Optimization","created":"2022-12-28","cited_by_count":30,"area":null},{"id":"2104.04282","title":"Direct Differentiable Augmentation Search","created":"2021-04-09","cited_by_count":28,"area":null},{"id":"2111.01754","title":"Meta-Learning to Improve Pre-Training","created":"2021-11-02","cited_by_count":27,"area":null},{"id":"2310.05674","title":"Making Scalable Meta Learning Practical","created":"2023-10-09","cited_by_count":17,"area":null},{"id":"2403.11395","title":"Automated data processing and feature engineering for deep learning and big data applications: a survey","created":"2024-03-18","cited_by_count":14,"area":null},{"id":"2111.08190","title":"Learning Augmentation Distributions using Transformed Risk Minimization","created":"2021-11-16","cited_by_count":13,"area":null},{"id":"2309.04747","title":"When to Learn What: Model-Adaptive Data Augmentation Curriculum","created":"2023-09-09","cited_by_count":13,"area":null},{"id":"2204.04360","title":"Data Augmentation for Electrocardiograms","created":"2022-04-09","cited_by_count":12,"area":null},{"id":"2302.09726","title":"Nystrom Method for Accurate and Scalable Implicit Differentiation","created":"2023-02-20","cited_by_count":8,"area":null},{"id":"2306.09998","title":"SLACK: Stable Learning of Augmentations with Cold-start and KL regularization","created":"2023-06-16","cited_by_count":6,"area":null},{"id":"2209.10307","title":"Understanding the Tricks of Deep Learning in Medical Image Segmentation: Challenges and Future Directions","created":"2022-09-21","cited_by_count":5,"area":null},{"id":"2409.04820","title":"FreeAugment: Data Augmentation Search Across All Degrees of Freedom","created":"2024-09-07","cited_by_count":3,"area":null},{"id":"2307.11808","title":"Automatic Data Augmentation Learning using Bilevel Optimization for Histopathological Images","created":"2023-07-21","cited_by_count":1,"area":null},{"id":"2403.08352","title":"Data augmentation with automated machine learning: approaches and performance comparison with classical data augmentation methods","created":"2024-03-13","cited_by_count":1,"area":null},{"id":"2505.21813","title":"Optimizing Data Augmentation through Bayesian Model Selection","created":"2025-05-27","cited_by_count":1,"area":null},{"id":"2510.00434","title":"On-the-Fly Data Augmentation via Gradient-Guided and Sample-Aware Influence Estimation","created":"2025-10-01","cited_by_count":1,"area":null},{"id":"2311.14182","title":"Gradient-based bilevel optimization for multi-penalty Ridge regression through matrix differential calculus","created":"2023-11-23","cited_by_count":0,"area":null},{"id":"2402.02741","title":"Glocal Hypergradient Estimation with Koopman Operator","created":"2024-02-05","cited_by_count":0,"area":null},{"id":"2408.13426","title":"Optimal Layer Selection for Latent Data Augmentation","created":"2024-08-24","cited_by_count":0,"area":null}],"next_cursor":null}