Gong Ziyang

This experiment report explores the process of using the open-source BERT (Bidirectional Encoder Representations from Transformers) model for Chinese text classification. By fine-tuning this model on a specific news dataset, we evaluate its classification performance and accuracy. The report systematically analyzes the basic principles, architectural design, pre-training tasks, and fine-tuning methods of the BERT pre-trained model while providing experimental results to assess the model's performance.

This article provides a comprehensive review of distributed learning methods for nonparametric and semiparametric estimation.

The Cox proportional hazards model is a semi-parametric model commonly used in survival analysis. It is a regression model that aims to model the hazard function of survival time \(T\), which represents the probability of an event occurring at time \(t\) given that the event has not occurred before time \(t\), that is, \[ \lambda(t)=\lim_{\Delta t\rightarrow 0}\frac{P(t\leq T<t+\Delta t|T\geq t)}{\Delta t}. \]