4 papers
Preconditioning Benefits of Spectral Orthogonalization in Muon
Jianhao Ma, Yu Huang, Yuejie Chi +1
The Muon optimizer, a matrix-structured algorithm that leverages spectral orthogonalization of gradients, is a milestone in the pretraining of large language models. However, the u…
LIBRA: Language Model Informed Bandit Recourse Algorithm for Personalized Treatment Planning
Junyu Cao, Ruijiang Gao, Esmaeil Keyvanshokooh +1
We introduce a unified framework that seamlessly integrates algorithmic recourse, contextual bandits, and large language models (LLMs) to support sequential decision-making in high…
Quantization through Piecewise-Affine Regularization: Optimization and Statistical Guarantees
Jianhao Ma, Lin Xiao
Optimization problems over discrete or quantized variables are very challenging in general due to the combinatorial nature of their search space. Piecewise-affine regularization (P…
PARQ: Piecewise-Affine Regularized Quantization
Lisa Jin, Jianhao Ma, Zechun Liu +3
We develop a principled method for quantization-aware training (QAT) of large-scale machine learning models. Specifically, we show that convex, piecewise-affine regularization (PAR…