Machine Learning · Computer Science
Incorporating Experts' Judgment into Machine Learning Models
Hogun Park, Aly Megahed, Peifeng Yin, Yuya Ong +2
2023-05-02
Applications · Statistics
Towards Model-informed Precision Dosing with Expert-in-the-loop Machine Learning
Yihuang Kang, Yi-Wen Chiu, Ming-Yen Lin, Fang-yi Su +1
2021-06-30
Machine Learning · Computer Science
Detecting Interpretable Subgroup Drifts
Flavio Giobergia, Eliana Pastor, Luca de Alfaro, Elena Baralis
2025-05-22
Machine Learning · Computer Science
Dynamic Multi-period Experts for Online Time Series Forecasting
Seungha Hong, Sukang Chae, Suyeon Kim, Sanghwan Jang +1
2026-03-11
Machine Learning · Computer Science
Interpretable Model Drift Detection
Pranoy Panda, Kancheti Sai Srinivas, Vineeth N Balasubramanian, Gaurav Sinha
2025-03-11
Machine Learning · Computer Science
Perspectives on Incorporating Expert Feedback into Model Updates
Valerie Chen, Umang Bhatt, Hoda Heidari, Adrian Weller +1
2022-07-19
Machine Learning · Computer Science
Domain Knowledge in Artificial Intelligence: Using Conceptual Modeling to Increase Machine Learning Accuracy and Explainability
V. C. Storey, J. Parsons, A. Castellanos, M. Tremblay +3
2025-07-08
Machine Learning · Computer Science
Automating concept-drift detection by self-evaluating predictive model degradation
Tania Cerquitelli, Stefano Proto, Francesco Ventura, Daniele Apiletti +1
2019-07-19
Machine Learning · Computer Science
Model Based Explanations of Concept Drift
Fabian Hinder, Valerie Vaquet, Johannes Brinkrolf, Barbara Hammer
2023-03-17
Machine Learning · Statistics
Monitoring the calibration of probability forecasts with an application to concept drift detection involving image classification
Christopher T. Franck, Anne R. Driscoll, Zoe Szajnfarber, William H. Woodall
2025-10-30
Machine Learning · Computer Science
Causal Explanation of Concept Drift -- A Truly Actionable Approach
David Komnick, Kathrin Lammers, Barbara Hammer, Valerie Vaquet +1
2025-10-14
Machine Learning · Computer Science
Amazon SageMaker Model Monitor: A System for Real-Time Insights into Deployed Machine Learning Models
David Nigenda, Zohar Karnin, Muhammad Bilal Zafar, Raghu Ramesha +3
2022-08-08
Computation and Language · Computer Science
Reliable and Interpretable Drift Detection in Streams of Short Texts
Ella Rabinovich, Matan Vetzler, Samuel Ackerman, Ateret Anaby-Tavor
2023-05-30
Machine Learning · Computer Science
A Scalable Approach to Covariate and Concept Drift Management via Adaptive Data Segmentation
Vennela Yarabolu, Govind Waghmare, Sonia Gupta, Siddhartha Asthana
2024-11-26
Machine Learning · Computer Science
A Decision-Based Dynamic Ensemble Selection Method for Concept Drift
Regis Antonio Saraiva Albuquerque, Albert Franca Josua Costa, Eulanda Miranda dos Santos, Robert Sabourin +1
2019-09-27
Computer Vision and Pattern Recognition · Computer Science
Domain-Specialized Object Detection via Model-Level Mixtures of Experts
Svetlana Pavlitska, Malte Stüven, Beyza Keskin, J. Marius Zöllner
2026-04-21
Machine Learning · Computer Science
STUDD: A Student-Teacher Method for Unsupervised Concept Drift Detection
Vitor Cerqueira, Heitor Murilo Gomes, Albert Bifet, Luis Torgo
2021-03-09