data scarcity

2 items

RESEARCHarXiv CS.LG·4/17/2026

Portfolio Optimization Proxies under Label Scarcity and Regime Shifts via Bayesian and Deterministic Students under Semi-Supervised Sandwich Training

This paper proposes a machine learning-assisted portfolio optimization framework designed for low data environments and regime uncertainty. It uses a teacher-student pipeline where a Conditional Value at Risk (CVaR) optimizer generates labels, and neural models are trained using both real and synthetically augmented data to overcome observation scarcity.

portfolio-optimization Financial AI machine learning data scarcity

RESEARCHarXiv CS.LG·5/8/2026

Physics-Informed Neural Networks with Learnable Loss Balancing and Transfer Learning

This paper introduces a self-supervised physics-informed neural network (PINN) framework that adaptively balances physics-based and data-driven supervision, particularly under data scarcity. It uses a learnable blending neuron to dynamically adjust term contributions based on their uncertainties and integrates transfer learning for enhanced efficiency.

learning Physics-Informed Neural Networks Transfer Learning data scarcity