2 papers
stat.ML2026
A Diffusion Approximation for Temporal-Difference Learning with Linear Features under Markovian Noise
M. Forzo, E. Monzio Compagnoni, A. Russo +1
Temporal difference (TD) learning with linear function approximation is a core method for policy evaluation. Its classical continuous-time description is an ordinary differential e…
cs.LG2026
The Good, the Bad, and the Sampled: a No-Regret Approach to Safe Online Classification
Tavor Z. Baharav, Spyros Dragazis, Aldo Pacchiano
We study sequential testing for a binary disease outcome when risk follows an unknown logistic model. At each round, the decision maker may either pay for a test revealing the true…