The Forget-me-not Process

Modeling non-stationary temporal data sources is a fundamental problem in signal processing, statistical data compression, quantitative finance and model-based reinforcement learning. One widely-adopted and successful approach has been to design meta-algorithms that automatically generalize existing stationary learning algorithms to various non-stationary settings.