{"total":17,"rows":[{"id":"2301.00557","title":"Learning to Maximize Mutual Information for Dynamic Feature Selection","created":"2023-01-02","cited_by_count":56,"area":null},{"id":"2306.03301","title":"Estimating Conditional Mutual Information for Dynamic Feature Selection","created":"2023-06-05","cited_by_count":21,"area":null},{"id":"2502.11067","title":"A Survey on Active Feature Acquisition Strategies","created":"2025-02-16","cited_by_count":17,"area":null},{"id":"2211.05039","title":"Active Acquisition for Multimodal Temporal Data: A Challenging Decision-Making Task","created":"2022-11-09","cited_by_count":13,"area":null},{"id":"2508.01957","title":"Stochastic Encodings for Active Feature Acquisition","created":"2025-08-03","cited_by_count":9,"area":null},{"id":"2110.14283","title":"How Important is Importance Sampling for Deep Budgeted Training?","created":"2021-10-27","cited_by_count":5,"area":null},{"id":"2210.07198","title":"Towards Trustworthy Automatic Diagnosis Systems by Emulating Doctors' Reasoning with Deep Reinforcement Learning","created":"2022-10-13","cited_by_count":5,"area":null},{"id":"2510.12624","title":"Learning-To-Measure: In-Context Active Feature Acquisition","created":"2025-10-14","cited_by_count":5,"area":null},{"id":"2402.03456","title":"Constrained Multiview Representation for Self-supervised Contrastive Learning","created":"2024-02-05","cited_by_count":3,"area":null},{"id":"2102.13636","title":"Active Selection of Classification Features","created":"2021-02-26","cited_by_count":1,"area":null},{"id":"2503.09181","title":"Dynamic Feature Selection from Variable Feature Sets Using Features of Features","created":"2025-03-12","cited_by_count":1,"area":null},{"id":"2506.20059","title":"DiaLLMs: EHR Enhanced Clinical Conversational System for Clinical Test Recommendation and Diagnosis Prediction","created":"2025-06-24","cited_by_count":1,"area":null},{"id":"2206.03659","title":"Scalable Online Disease Diagnosis via Multi-Model-Fused Actor-Critic Reinforcement Learning","created":"2022-06-08","cited_by_count":0,"area":null},{"id":"2608.02305","title":"BRiG-AFA: Bellman Risk-to-Go Learning for Non-Myopic Active Feature Acquisition","created":"2026-08-03","cited_by_count":0,"area":null},{"id":"2609.32325","title":"Active Feature Acquisition With Incomplete Training Data","created":"2026-09-26","cited_by_count":0,"area":null},{"id":"2610.03454","title":"Measure Less, Know More: Self-Supervised Test-Time Feature Acquisition","created":"2026-10-02","cited_by_count":0,"area":null},{"id":"2610.07615","title":"AFA-BANDIT: Provably Near-Optimal Online Multi-Feature Classification Under Budget Constraints","created":"2026-10-06","cited_by_count":0,"area":null}],"next_cursor":null}