Foreclassing: A new machine learning perspective on human decision making with temporal data
Fuente:
arXiv
Guardado en:
| Autores principales: | Coulson, Daniel Andrew, Wells, Martin T. |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Minimaxity and Admissibility of Bayesian Neural Networks
por: Coulson, Daniel Andrew, et al.
Publicado: (2026)
por: Coulson, Daniel Andrew, et al.
Publicado: (2026)
Multi-agent decision making: A Blackwell's informativeness approach
por: Zhang, Zheng, et al.
Publicado: (2026)
por: Zhang, Zheng, et al.
Publicado: (2026)
Predicting human decisions with behavioral theories and machine learning
por: Plonsky, Ori, et al.
Publicado: (2019)
por: Plonsky, Ori, et al.
Publicado: (2019)
The impact of machine learning forecasting on strategic decision-making for Bike Sharing Systems
por: Angelelli, Enrico, et al.
Publicado: (2026)
por: Angelelli, Enrico, et al.
Publicado: (2026)
A feature-stable and explainable machine learning framework for trustworthy decision-making under incomplete clinical data
por: Andrys-Olek, Justyna, et al.
Publicado: (2026)
por: Andrys-Olek, Justyna, et al.
Publicado: (2026)
A new method of modeling the multi-stage decision-making process of CRT using machine learning with uncertainty quantification
por: Larsen, Kristoffer, et al.
Publicado: (2023)
por: Larsen, Kristoffer, et al.
Publicado: (2023)
Automated machine learning: AI-driven decision making in business analytics
por: Schmitt, Marc
Publicado: (2022)
por: Schmitt, Marc
Publicado: (2022)
Joint modeling for learning decision-making dynamics in behavioral experiments
por: Bian, Yuan, et al.
Publicado: (2025)
por: Bian, Yuan, et al.
Publicado: (2025)
Robust estimation of the intrinsic dimension of data sets with quantum cognition machine learning
por: Candelori, Luca, et al.
Publicado: (2024)
por: Candelori, Luca, et al.
Publicado: (2024)
Identifiable Latent Bandits: Leveraging observational data for personalized decision-making
por: Balcıoğlu, Ahmet Zahid, et al.
Publicado: (2024)
por: Balcıoğlu, Ahmet Zahid, et al.
Publicado: (2024)
Causality in the human niche: lessons for machine learning
por: Lange, Richard D., et al.
Publicado: (2025)
por: Lange, Richard D., et al.
Publicado: (2025)
Explanatory machine learning for sequential human teaching
por: Ai, Lun, et al.
Publicado: (2022)
por: Ai, Lun, et al.
Publicado: (2022)
An operator preconditioning perspective on training in physics-informed machine learning
por: De Ryck, Tim, et al.
Publicado: (2023)
por: De Ryck, Tim, et al.
Publicado: (2023)
Variational decision diagrams for quantum-inspired machine learning applications
por: Vargas-Calderón, Vladimir, et al.
Publicado: (2025)
por: Vargas-Calderón, Vladimir, et al.
Publicado: (2025)
Industrial brain: a human-like autonomous neuro-symbolic cognitive decision-making system
por: Wang, Junping, et al.
Publicado: (2025)
por: Wang, Junping, et al.
Publicado: (2025)
Beyond IID: data-driven decision-making in heterogeneous environments
por: Besbes, Omar, et al.
Publicado: (2022)
por: Besbes, Omar, et al.
Publicado: (2022)
A comparison between geostatistical and machine learning models for spatio-temporal prediction of PM2.5 data
por: Mohamed, Zeinab, et al.
Publicado: (2025)
por: Mohamed, Zeinab, et al.
Publicado: (2025)
Compositional learning of functions in humans and machines
por: Zhou, Yanli, et al.
Publicado: (2024)
por: Zhou, Yanli, et al.
Publicado: (2024)
A density estimation perspective on learning from pairwise human preferences
por: Dumoulin, Vincent, et al.
Publicado: (2023)
por: Dumoulin, Vincent, et al.
Publicado: (2023)
Downscaling human mobility data based on demographic socioeconomic and commuting characteristics using interpretable machine learning methods
por: Jiang, Yuqin, et al.
Publicado: (2025)
por: Jiang, Yuqin, et al.
Publicado: (2025)
Adaptive digital twins for predictive decision-making: Online Bayesian learning of transition dynamics
por: Varetti, Eugenio, et al.
Publicado: (2025)
por: Varetti, Eugenio, et al.
Publicado: (2025)
Traditional machine learning vs. deep learning from dynamic graph representations of proteins' 3D folds in the task of protein structure classification
por: Wells, Aydin, et al.
Publicado: (2026)
por: Wells, Aydin, et al.
Publicado: (2026)
Generative models for decision-making under distributional shift
por: Cheng, Xiuyuan, et al.
Publicado: (2026)
por: Cheng, Xiuyuan, et al.
Publicado: (2026)
Can humans teach machines to code?
por: Hocquette, Céline, et al.
Publicado: (2024)
por: Hocquette, Céline, et al.
Publicado: (2024)
A new methodology to decompose a parametric domain using reduced order data manifold in machine learning
por: Mang, Chetra, et al.
Publicado: (2025)
por: Mang, Chetra, et al.
Publicado: (2025)
Digital Twins for forecasting and decision optimisation with machine learning: applications in wastewater treatment
por: Colwell, Matthew, et al.
Publicado: (2024)
por: Colwell, Matthew, et al.
Publicado: (2024)
Scenario theory for multi-criteria data-driven decision making
por: Garatti, Simone, et al.
Publicado: (2026)
por: Garatti, Simone, et al.
Publicado: (2026)
Privacy-preserving machine learning for healthcare: open challenges and future perspectives
por: Guerra-Manzanares, Alejandro, et al.
Publicado: (2023)
por: Guerra-Manzanares, Alejandro, et al.
Publicado: (2023)
Analytical results for uncertainty propagation through trained machine learning regression models
por: Thompson, Andrew
Publicado: (2024)
por: Thompson, Andrew
Publicado: (2024)
Incorporating structural uncertainty in causal decision making
por: Kaptein, Maurits
Publicado: (2025)
por: Kaptein, Maurits
Publicado: (2025)
A metrological framework for uncertainty evaluation in machine learning classification models
por: Bilson, Samuel, et al.
Publicado: (2025)
por: Bilson, Samuel, et al.
Publicado: (2025)
A new framework for X-ray absorption spectroscopy data analysis based on machine learning: XASDAML
por: Han, Xue, et al.
Publicado: (2025)
por: Han, Xue, et al.
Publicado: (2025)
Using causal abstractions to accelerate decision-making in complex bandit problems
por: Dyer, Joel, et al.
Publicado: (2025)
por: Dyer, Joel, et al.
Publicado: (2025)
Adaptive decision-making for stochastic service network design
por: Durán-Micco, Javier, et al.
Publicado: (2026)
por: Durán-Micco, Javier, et al.
Publicado: (2026)
Scientific machine learning in Hydrology: a unified perspective
por: Adombi, Adoubi Vincent De Paul
Publicado: (2025)
por: Adombi, Adoubi Vincent De Paul
Publicado: (2025)
Can machine learning solve the challenge of adaptive learning and the individualization of learning paths? A field experiment in an online learning platform
por: Klausmann, Tim, et al.
Publicado: (2024)
por: Klausmann, Tim, et al.
Publicado: (2024)
X-TIME: An in-memory engine for accelerating machine learning on tabular data with CAMs
por: Pedretti, Giacomo, et al.
Publicado: (2023)
por: Pedretti, Giacomo, et al.
Publicado: (2023)
Negative Dependence as a toolbox for machine learning : review and new developments
por: Tran, Hoang-Son, et al.
Publicado: (2025)
por: Tran, Hoang-Son, et al.
Publicado: (2025)
Another look at statistical inference with machine learning-imputed data
por: Gronsbell, Jessica, et al.
Publicado: (2024)
por: Gronsbell, Jessica, et al.
Publicado: (2024)
JAX-Privacy: A library for differentially private machine learning
por: McKenna, Ryan, et al.
Publicado: (2026)
por: McKenna, Ryan, et al.
Publicado: (2026)
Ejemplares similares
-
Minimaxity and Admissibility of Bayesian Neural Networks
por: Coulson, Daniel Andrew, et al.
Publicado: (2026) -
Multi-agent decision making: A Blackwell's informativeness approach
por: Zhang, Zheng, et al.
Publicado: (2026) -
Predicting human decisions with behavioral theories and machine learning
por: Plonsky, Ori, et al.
Publicado: (2019) -
The impact of machine learning forecasting on strategic decision-making for Bike Sharing Systems
por: Angelelli, Enrico, et al.
Publicado: (2026) -
A feature-stable and explainable machine learning framework for trustworthy decision-making under incomplete clinical data
por: Andrys-Olek, Justyna, et al.
Publicado: (2026)