{"total":25,"rows":[{"id":"2302.08893","title":"Active learning for data streams: a survey","created":"2023-02-17","cited_by_count":29,"area":null},{"id":"2310.09702","title":"Inference with Mondrian Random Forests","created":"2023-10-15","cited_by_count":6,"area":null},{"id":"2107.08189","title":"BEDS-Bench: Behavior of EHR-models under Distributional Shift--A Benchmark","created":"2021-07-17","cited_by_count":4,"area":null},{"id":"2109.10541","title":"Minimax Rates for High-Dimensional Random Tessellation Forests","created":"2021-09-22","cited_by_count":4,"area":null},{"id":"2202.10669","title":"On Uncertainty Estimation by Tree-based Surrogate Models in Sequential Model-based Optimization","created":"2022-02-22","cited_by_count":4,"area":null},{"id":"2505.21441","title":"Autoencoding Random Forests","created":"2025-05-27","cited_by_count":3,"area":null},{"id":"2106.14340","title":"Reducing numerical precision preserves classification accuracy in Mondrian Forests","created":"2021-06-28","cited_by_count":2,"area":null},{"id":"2201.06821","title":"Nonparametric Feature Selection by Random Forests and Deep Neural Networks","created":"2022-01-18","cited_by_count":2,"area":null},{"id":"2410.12454","title":"Conditional Outcome Equivalence: A Quantile Alternative to CATE","created":"2024-10-16","cited_by_count":2,"area":null},{"id":"2503.06985","title":"Learning Decision Trees as Amortized Structure Inference","created":"2025-03-10","cited_by_count":2,"area":null},{"id":"2505.17468","title":"Efficient Adaptive Experimentation with Noncompliance","created":"2025-05-23","cited_by_count":2,"area":null},{"id":"2108.02507","title":"Shape Modeling with Spline Partitions","created":"2021-08-05","cited_by_count":1,"area":null},{"id":"2205.07871","title":"Mondrian Forest for Data Stream Classification Under Memory Constraints","created":"2022-05-12","cited_by_count":1,"area":null},{"id":"2309.03616","title":"Filtration Surfaces for Dynamic Graph Classification","created":"2023-09-07","cited_by_count":1,"area":null},{"id":"2407.09964","title":"TrIM: Transformed Iterative Mondrian Forests for Gradient-based Dimension Reduction and High-Dimensional Regression","created":"2024-07-13","cited_by_count":1,"area":null},{"id":"2109.08010","title":"WildWood: a new Random Forest algorithm","created":"2021-09-16","cited_by_count":0,"area":null},{"id":"2110.08483","title":"Extremely Simple Streaming Forest","created":"2021-10-16","cited_by_count":0,"area":null},{"id":"2210.05704","title":"Dynamic Ensemble Size Adjustment for Memory Constrained Mondrian Forest","created":"2022-10-11","cited_by_count":0,"area":null},{"id":"2309.01050","title":"Efficient Curriculum based Continual Learning with Informative Subset Selection for Remote Sensing Scene Classification","created":"2023-09-03","cited_by_count":0,"area":null},{"id":"2406.12531","title":"TREE: Tree Regularization for Efficient Execution","created":"2024-06-18","cited_by_count":0,"area":null},{"id":"2408.07897","title":"The Nah Bandit: Modeling User Non-compliance in Recommendation Systems","created":"2024-08-15","cited_by_count":0,"area":null},{"id":"2502.04323","title":"The Uniformly Rotated Mondrian Kernel","created":"2025-02-06","cited_by_count":0,"area":null},{"id":"2603.13014","title":"FraudFox: Adaptable Fraud Detection in the Real World","created":"2026-03-13","cited_by_count":0,"area":null},{"id":"2603.17548","title":"CLeAN: Continual Learning Adaptive Normalization in Dynamic Environments","created":"2026-03-18","cited_by_count":0,"area":null},{"id":"2605.11841","title":"Minimax Rates and Spectral Distillation for Tree Ensembles","created":"2026-05-12","cited_by_count":0,"area":null}],"next_cursor":null}