by instadatahelp | Aug 28, 2023 | AI Blogs
[Submitted on 25 Aug 2023] Download a PDF of the paper titled “Nonparametric Additive Value Functions: Interpretable Reinforcement Learning with an Application to Surgical Recovery” by Patrick Emedom-Nnamdi and three other authors here. Abstract: We...
by instadatahelp | Aug 28, 2023 | AI Blogs
Learning Optimal Group-structured Individualized Treatment Rules with Many Treatments Haixu Ma, Donglin Zeng, Yufeng Liu; 24(102):1−48, 2023. Abstract In recent years, there has been increased attention towards data-driven individualized decision making problems. One...
by instadatahelp | Aug 28, 2023 | AI Blogs
Business planning relies heavily on time-series forecasts. However, these forecasts often prioritize objectives that do not align with the goals of the business, resulting in forecasts that do not meet business preferences. In this study, we show that optimizing...
by instadatahelp | Aug 28, 2023 | AI Blogs
Efficient Computation of Rankings from Pairwise Comparisons M. E. J. Newman; 24(238):1−25, 2023. Abstract This study focuses on the ranking of individuals, teams, or objects, based on pairwise comparisons between them, using the Bradley-Terry model. The estimation of...
by instadatahelp | Aug 28, 2023 | AI Blogs
Parameter-efficient fine-tuning (PEFT) is a new approach that allows for cost-effective fine-tuning of large language models (LLMs). One popular choice for fine-tuning is low-rank adaptation (LoRA). However, a common issue with fine-tuned LLMs is that they often...
by instadatahelp | Aug 28, 2023 | AI Blogs
A General Theory for Federated Optimization with Asynchronous and Heterogeneous Clients Updates Authors: Yann Fraboni, Richard Vidal, Laetitia Kameni, Marco Lorenzi; Published in 2023, Volume 24, Issue 110, Pages 1-43. Abstract This study presents a novel framework...
