9 papers
RocketPFN: Accurate Time Series Classification via In-Context Learning
Franco Martino O'Rourke, Ana Trisovic, Dimitris Bertsimas
We introduce RocketPFN, a training-free pipeline for time series classification that combines random convolutional feature extraction (Rocket) with in-context classification via a…
A Causal DAG Prior for Synthetic Time-Series Classification Datasets
Franco Martino O'Rourke, Ana Trisovic, Dimitris Bertsimas
A Prior-data fitted Network learns the posterior predictive induced by its training prior; bringing this paradigm to multivariate time-series classification therefore calls for a s…
Optimal Control of Fluid Restless Multi-armed Bandits: A Machine Learning Approach
Dimitris Bertsimas, Cheol Woo Kim, José Niño-Mora
We present a novel machine learning framework for the optimal control of fluid restless multi-armed bandit problems (FRMABPs) with state equations that are either affine or quadrat…
A Multimodal and Explainable Machine Learning Approach to Diagnosing Multi-Class Ejection Fraction from Electrocardiograms
Catherine Ning, Yu Ma, Cindy Beini Wang +4
Left ventricular ejection fraction (LVEF) assessment depends on echocardiography, limiting access in primary care and resource-constrained settings. We developed a multimodal machi…
Robustifying and Selecting Cohort-Appropriate Prognostic Models under Distributional Shifts
Dimitris Bertsimas, Carol Gao, Angelos G. Koulouras +1
External validation is widely regarded as the gold standard for prognostic model evaluation. In this study, we challenge the assumption that successful external calibration guarant…
Early Warning Index for Patient Deteriorations in Hospitals
Dimitris Bertsimas, Yu Ma, Kimberly Villalobos Carballo +5
Hospitals lack automated systems to harness the growing volume of heterogeneous clinical and operational data to effectively forecast critical events. Early identification of patie…