mailitics

Tag: stationary

  • Efficient Learning of Stationary Diffusions with Stein-type Discrepancies

    Efficient Learning of Stationary Diffusions with Stein-type Discrepancies arXiv:2601.16597v1 Announce Type: new Abstract: Learning a stationary diffusion amounts to estimating the parameters of a stochastic differential equation whose stationary distribution matches a target distribution. We build on the recently introduced kernel deviation from stationarity (KDS), which enforces stationarity by evaluating expectations of the diffusion’s generator…

  • Non-Stationary Functional Bilevel Optimization

    Non-Stationary Functional Bilevel Optimization arXiv:2601.15363v1 Announce Type: new Abstract: Functional bilevel optimization (FBO) provides a powerful framework for hierarchical learning in function spaces, yet current methods are limited to static offline settings and perform suboptimally in online, non-stationary scenarios. We propose SmoothFBO, the first algorithm for non-stationary FBO with both theoretical guarantees and practical scalability.…

  • Stationary Reweighting Yields Local Convergence of Soft Fitted Q-Iteration

    Stationary Reweighting Yields Local Convergence of Soft Fitted Q-Iteration arXiv:2512.23927v1 Announce Type: new Abstract: Fitted Q-iteration (FQI) and its entropy-regularized variant, soft FQI, are central tools for value-based model-free offline reinforcement learning, but can behave poorly under function approximation and distribution shift. In the entropy-regularized setting, we show that the soft Bellman operator is locally…

  • Optimal Dynamic Regret by Transformers for Non-Stationary Reinforcement Learning

    Optimal Dynamic Regret by Transformers for Non-Stationary Reinforcement Learning arXiv:2508.16027v1 Announce Type: new Abstract: Transformers have demonstrated exceptional performance across a wide range of domains. While their ability to perform reinforcement learning in-context has been established both theoretically and empirically, their behavior in non-stationary environments remains less understood. In this study, we address this gap…