Daniel F Schmidt — accepted AI-conference papers

2026

Single-Rollout Hidden-State Dynamics for Training-Free RLVR Data Selection

Jianghao Wu, Daniel F Schmidt, Weiqiang Wang, Jin Ye, Jianfei Cai, Yasmeen George

ICML 2026poster

Reinforcement learning with verifiable rewards (RLVR) can yield large reasoning gains from very few training instances, yet its strong sensitivity to which instances are used makes data selection a central bottleneck. Most existing selection pipelines rely on training-time optimization signals and/o…

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2023

Bayes beats Cross Validation: Efficient and Accurate Ridge Regression via Expectation Maximization

Shu Tew, Mario Boley, Daniel F. Schmidt

NeurIPS 2023poster

We present a novel method for tuning the regularization hyper-parameter, $\lambda$, of a ridge regression that is faster to compute than leave-one-out cross-validation (LOOCV) while yielding estimates of the regression parameters of equal, or particularly in the setting of sparse covariates, superio…

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