Welcome to my blog.

I draft some notes on math and programming here, along with my monologue.

As an algorithm engineer, there are several topics that I’ve studied and worked on, such as *recommender system*, *search*, *natural language processing*, *parallel computation*, *data science*, and *symbolic computation*. If anything interests you, feel free to email me.

English

I toke some notes on quasi-Newton methods in this article, including an intuitive derivation of BFGS formula and a demonstration of Wolfe condition. The algorithm, convergence results and limit memory version were discussed as well.

1. Background 2. BERT: higher accuracy and less handcraft Replace manual features Replace classifier for dense feature 3. Scaling with MXNet Model Server Customization Load test 4. Recap In this article, I will give a brief introduction on how to improve intent classification using pre-trained model BERT and MXNet Model Server (MMS).

1. Introduction 2. Sequential Boyer-Moore algorithm 3. Distributed majority voting algorithm Multi-processing Multi-Threading Complexity analysis for distributed version 4. Benchmark 5. Summary 1. Introduction The original majority voting problem is to find the element that appears more than half times in a given array, and if there is no such majority element, algorithm should just return empty result.

Chinese