Some selected summaries, research reports and the like, which I think might be useful when doing sth. professional.

• Competition
  • OPRM-MCM_ICM_Competition_2020.pdf:
    • paper for COMAP's Mathematical Contest in Modeling (MCM), 2020.
    • Teammates: Zhanghan Wang, Zihan Zhou(all USTCers).
    • One-sentence Summary: We put forward the Ball Passing Graph Model (BPGM), the Competitive-Oriented Index Estimation System(COIES), and the Optimal Passing Route Model (OPRM) for a complete analysis for the Huskies’ team cooperation properties.
    • Result: Meritorious Winner(7.09%)
• Research Reports
  • Survey of Multivariate Mutual Information-Information Theory-2021.pdf
    • course work for Information Theory A (Prof. Wenyi Zhang, USTC)
    • One-sentence Summary: We extensively summarize the recent researches of Multivariate Mutual Information (MMI) from aspects of entropic, partial information decomposition and topology, and we unify the metrics by Graph Convergence Measure, following the work of Rahimzamani et al. (2018).
  • USTC QA system-NLP-2020.pdf
    • course experiment for Nature Language Processing(Prof. Zhenhua Ling, USTC)
    • Teammates: Yu Wang, yuhan Dai(all USTCers).
    • One-sentence Summary: We successfully inplemented a USTC Question Answering system based on AskMSR(Brill et. al, EMNLP 2002) and the results are well analyzed qualitatively and quantitatively.
  • Core Vetor Machine-Algorithms for Big Data-2020.pdf
    • course work for Algorithms for Big Data(Prof. Hu Ding, USTC)
    • One-sentence Summary: Core Vector Machine uses the idea of Minimum Enclosing Ball(MEB) so as to approximate the optimal solution from Support Vector Machine, and the time complexity of this algorithm is independent of the size of the training set.
  • Inexact One-dimensional Search-Operation Research-2020.pdf
    • course work for Operations research(Prof. Zhouwang Yang, USTC)
    • One-sentence Summary: I implemented Goldstein step criterion and Wolfe-Powell step criterion for finding the global minimum of certein functions.
  • Collaborative Filtering Models-Intro to Data Science-2019.pdf:
    • course work for Intro to Data Science(Prof. Qi Liu, USTC)
    • One-sentence Summary: A reasearch for Collaborative Filtering Models including NCF(He et. al, WWW 2017), CMN(Ebesu et. al, SIGIR 2018), NCGF(Wang et. al, SIGIR 2019) in recommendation.
• Summaries

  • Causality- Models, Reasoning and Inference

    • Chap1- Introduction to Probabilities Graphs and Causal Models.pdf

  • Artificial Intelligence-2019.pdf:

    • course summary for Artificial Intelligence(Associate Prof. Linli Xu, USTC)
    • One-sentence Summary: including Search, Constraint satisfaction problems, Logical Agent, First-order logical reasoning, Uncertainty quantification and probabilistic reasoning and so on.

  • (to be updated)Machine Learning-Stanford CS229.pdf :

    • course summary for Machine Learning(On line)(Prof. Andrew Ng, Stanford)
    • One-sentence Summary: some basic but important concepts in Machine Learning.

  • Neural Language Processing-2020.pdf:

    • course summary for NLP(Prof. Zhenhua Ling, USTC)
    • One-sentence Summary: including some basic concepts like Finite State Automata(FSA), Part of Speech Tagging(POS), Context-Free Grammer(CFG), and the most intersting part, I think, is Word Sense Disambiguation and Machine Tanslation.

  • (TODO)Computational Methods-2019.pdf:

    • Scripts for Course Computational Methods(Associate Prof. Weihua Tong, USTC)
    • Keywords: Matrix Eigenvalues, Matrix Decomposition, Matrix iterative solutions, Lagrange interpolation.

  • (TODO)Operations Research-2020.pdf:

    • Scripts for Course Operation Research(Prof. Zhouwang Yang, USTC)
    • Keywords: Linear programming, Dynamic Programming, Graph algprithms, Unconstrained optimization and Constrained optimization.