From the 1 of 5 linked papers with an AI index.
5 papers
A Predictive-Prescriptive Analytics Framework for Fair Computed Tomography Scheduling and Radiologist Workload Allocation
Ludovico Ambrosi, Chandra Bortolotto, Sara Cambiaghi +3
Scheduling follow-up Computed Tomography (CT) examinations requires balancing two competing objectives: assigning patients as close as possible to their recommended examination dat…
Divergence Decoding: Training-Free Capability Fusion
Yimi Wang, Hao Li, Shuo Yang +6
The paper proposes Divergence Decoding, a training‑free method that dynamically routes token generation between a generalist LLM and a domain‑specialist LLM using Jensen‑Shannon di…
Scaling Laws for Precision in High-Dimensional Linear Regression
Dechen Zhang, Xuan Tang, Yingyu Liang +1
Low-precision training is critical for optimizing the trade-off between model quality and training costs, necessitating the joint allocation of model size, dataset size, and numeri…
Learning under Quantization for High-Dimensional Linear Regression
Dechen Zhang, Junwei Su, Difan Zou
The use of low-bit quantization has emerged as an indispensable technique for enabling the efficient training of large-scale models. Despite its widespread empirical success, a rig…
Kernel Regression in Structured Non-IID Settings: Theory and Implications for Denoising Score Learning
Dechen Zhang, Zhenmei Shi, Yi Zhang +2
Kernel ridge regression (KRR) is a foundational tool in machine learning, with recent work emphasizing its connections to neural networks. However, existing theory primarily addres…