Author

Jose H. Blanchet

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#artificial intelligence Jul 2026

A Few Teacher Steps Go a Long Way: Cost-Efficient On-Policy Data Augmentation for Agent Post-Training

Bounded unfiltered teacher continuations at learner-induced contexts improve over pure behavioral cloning at matched budgets and suggest that a few teacher steps, placed at learner-induced contexts, can be a more cost-efficient supervision allocation than longer or more heavily curated teacher completions.

Junze Ye, Jiayi Cheng, Miao Lu et al. · arXiv.org · 2 citations

Preprint Aug 2026

Sobolev Regularized Score Difference Estimation in Diffusion Models

This work proposes a statistically consistent and scalable estimator for score differences based on Sobolev regularization and demonstrates its effectiveness on real-world tasks, including transfer learning for ECG signal generation, where it substantially outperforms non-regularized score difference estimators in downstream classification performance.

Chenghan Xie, Jose H. Blanchet, Renyuan Xu · 0 citations

#machine learning Feb 2026

Robust Assortment Optimization from Observational Data

This work uncover and identify the notion of ``robust item-wise coverage''as the minimal data requirement to enable sample-efficient robust assortment learning and bridges the gap between robustness and statistical efficiency in assortment learning.

Miao Lu, Yuxuan Han, Han Zhong et al. · arXiv.org · 0 citations