arXiv Machine Learning By Melika Baghi

Conditional Validity for Adaptive Modality Acquisition: When the Policy Chooses Its Own Calibration Group

Read the original on arXiv Machine Learning →

The paper introduces RouteCert, a method for ensuring risk control in multimodal systems that acquire inputs adaptively. It shows that conditional calibration can remain valid even when the acquisition policy determines the calibration group, and provides two finite‑sample constructions: threshold‑free routing with terminal‑pattern calibration and simultaneous validation of policy‑pattern pairs. Experiments on a clinical ECG task and masked multimodal benchmarks demonstrate that RouteCert achieves low disagreement rates and competitive answered fractions while validating each acquisition stage separately.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

arXiv Computer Vision
Aug 28

Evaluator-Dependent Patient-Adaptive ECG Lead-Channel Allocation

The study investigates how patient‑adaptive ECG lead‑channel allocation policies perform when evaluated by different diagnostic models. Two policies, ECG‑on‑Demand and MGA, trained with a simple logistic evaluator were tested on a more powerful ResNet1D evaluator, revealing that the adaptive advantage observed with the training evaluator disappears or reverses with the stronger evaluator. Across multiple budgets, policies, and metrics, all interactions favor fixed protocols under the strong evaluator, suggesting that adaptive channel selection must be jointly optimized with the diagnostic backbone.

By Xiaoyang Li, Zeyan Tao