Xiaolong Huang

Efficient Long-Horizon Learning for Learned Optimization

Efficient Long-hOrizon (ELO) learning is introduced, an efficient meta-training algorithm that reallocates wasted meta-training compute to longer failure regimes, achieving efficient long-horizon learning, and enforces decoupled progressive expert supervision, providing stable meta-learning signals that additionally improve the generalization of LOs.