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.
Optimistic covariance-adaptive algorithms improve combinatorial semi-bandits regret.
The paper proposes a method to estimate treatment effects using CAR designs with additional covariates.
Method optimizes diffusion model generation to meet user preferences.
New algorithm reduces semi-bandit regret using covariance estimates.
Estimates treatment effects in randomized experiments with non-compliance.
New method efficiently learns positive-definite curvature for neural nets.
Oracle-efficient algorithms reduce combinatorial semi-bandit regret to logarithmic time.
WHOMP optimizes randomized controlled trials by minimizing subgroup bias.
Proposes a new ridge estimator for smooth covariates with adaptive centering.
DARTS optimizes covariate selection in trials with limited data.
New algorithms identify best arm with less pulls, adapting to arm covariances.