This repository was created for Graduate Admissions. It contains my CV, personal statement, writing samples, transcripts, test scores, research&work experiences, etc. The detailed list as follows:
- CV_KaikaiZhao.pdf: my CV
- PersonalStatement_KaikaiZhao.pdf: my personal statement
- Transcripts_KaikaiZhao.pdf: my undergraduate transcripts, including both original version and translations
- Diploma&BachelorCertificate_KaikaiZhao.pdf: my Diploma and Bachelor Certificate, it is supposed to note that I thought the original version is not required, so I did not ask relevant staff to print and seal it when I went to my undergraduate college in Nov. 2017. If they would be required during later admission processing, I could go there again and fetch it.
- KernelLearning_Presentation_KaikaiZhao.pdf: This file is the slides of my presentation about kernel learning based on random features. I made this presentation on our Machine Learning Group meeting in Oct. 2017, in National University of Defense Technology(NUDT).
- GRE_KaikaiZhao.pdf: This file is my GRE scores downloaded from ETS. To be honest, although a full score of quantitative reasoning is obtained, my verbal reasoning and analytical writing scores are not strong. I have to explain that I spent less than a month preparing for that test because of my busy work in July 2014 when I did not anticipated I would apply for a PhD program in the future.
- IELTS_KaikaiZhao.pdf: It is my IELTS scores and I will take the IELTS test again one month later.
- Large-scale k-means clustering via variance reduction.pdf: I am a co-author of this paper. It proposed a new method to accelerate k-means by using variance reduction technique denoted as VRKM. The variant of VRKM named VRKM++ does not have to compute the batch gradient, and is more efficient. It has been submitted to Neurocomputing in Nov. 2017.
- Multiple kernel k-means clustering with late fusion.pdf: I am the main contributor of this paper. In this paper, an effective method is proposed for multiple kernel k-means which integrates the clustering results from multiple views into an optimal one.
- Co-reading_Activity_Program.pdf: We have launched a co-reading program which is aimed at distant children who love reading, but cannot afford buying books. It provides a platform for warmhearted volunteers in the society to help them read books, to answer questions and doubts, grow together with them and change their fate through reading.
- ViewKernelsFromNeuralNetworkPerspective.pdf: This file is the slides of my presentation on our Machine Learning Group meeting. I presented a paper from NIPS 2018 Conference Proceedings, i.e. An Empirical Study on The Properties of Random Bases for Kernel Methods.