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 ...
InfoWorld

Google targets AI inference bottlenecks with TurboQuant

Google says its new TurboQuant method could improve how efficiently AI models run by compressing the key-value cache used in LLM inference and supporting more efficient vector search. In tests on ...
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 ...
GitHub

causal_inference_modelling.py

class (aliased as ``IPTWGEEModel`` for backward compatibility).
GitHub

Triton Inference Server Kafka I/O Deployment

Using the Triton Inference Server In-Process Python API you can integrate triton server based models into any Python framework to consume the messages from a Kafka topic and produce the inference ...