A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
FQE with deep neural networks achieves asymptotic normality and finite-sample bounds.
AHS framework selects hyperparameters for FQE with error guarantees.
New method stabilizes FQE by reweighting Bellman targets.
Paper improves bootstrapping for off-policy reinforcement learning inference.
BCRL learns a Bellman complete representation for offline RL policy evaluation.
Q-MMR evaluates policies using reweighted rewards and moment matching.
New algorithms for model selection in off-policy evaluation of reinforcement learning.