Optimizer ideas

Optimizer update-rule variants and parameter-specific step sizes, benchmarked against a learning-rate-tuned baseline.

✗ Failed on benchmark 2026

Martingale Response Control Variate

Use the trajectory martingale decomposition to separate predictable training updates from genuinely unpredictable residual updates, then scale the residual according to its estimated response to future loss. The method targets stochastic or event-driven optimization with history-dependent samples and predicts that response-weighted residual energy, rather than total gradient variance, controls update noise and instability.

Useful7/10
Difficulty7/10
Novelty7/10
Paper: The Memory Hidden in Response Fluctuations: Trajectory-Level Fluctuation-Response Theory and Inequalities for Non-Markovian Jump Dynamics arXiv:2608.20328