Hyperparameter Trajectory Inference with Conditional Lagrangian Optimal Transport

ArXi:2603.01771v3 Announce Type: replace Neural networks (NNs) often have critical behavioural trade-offs that are set at design time with hyperparameters-such as reward weights in reinforcement learning or quantile targets in regression. Post-deployment, however, user preferences can evolve, making initial settings undesirable, necessitating potentially expensive re