Frontiers

Computational Frameworks for Decision-Making: From Bayesian Inference to Reinforcement Learning Models

The ability to make adaptive decisions in uncertain environments is a fundamental characteristic of biological intelligence. Historically, computational ...
Scientific Research Publishing

Anderson, T.W. and Rubin, H. (1956) Statistical Inference in Factor Analysis. In: Neyman, J., Ed., Proceedings of the 3rd Berkeley Symposium on Mathematical Statistics and ...

ABSTRACT: In normal theory exploratory factor analysis, likelihood ratio (LR) statistic plays an important role in evaluating the goodness-of-fit of the model. In this paper, we derive an ...
IEEE

Robust Statistical Inference for Accelerated Life-Tests With One-Shot Devices Under Log-Logistic Distributions

Abstract: A one-shot device is a unit that operates only once, after which it is either destroyed or needs to be rebuilt. For this type of device, the operational status can only be assessed at a ...
IEEE

Hardware Accelerator Design for Sparse DNN Inference and Training: A Tutorial

Abstract: Deep neural networks (DNNs) are widely used in many fields, such as artificial intelligence generated content (AIGC) and robotics. To efficiently support these tasks, the model pruning ...