返回信息流2014年神经计算课程内容预告
The NC course this year will cover but not limited to the following topics:
- the classical Bias-Variance decomposition and its application, e.g. Bagging, Boosting, Random Forest
- the VC learning theory and SVM
- the Regularization technique, e.g. SVM, Kernel method, RBF.
- the Gaussian processes
- the MLE, MAP, and Bayesian estimation, and also Monte Carlo
- the Deep networks or deep learning, e.g. MLP and BP alg., autoencoder networks, dropout
- the Compressive sensing, sparse coding, low-rank models, e.g. SRC, SSC, LRR, RPCA, MC, and some efficient optimization techniques, e.g., ADMM, Proximal method.
If you are really interested in 机器学习, especially the topics mentioned above, please don't hesitate to join us!
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神经计算2014春季课程本周五5-6节重装开课 13:30-15:20 教二-30
LCG444
2014/2/17镜像同步15 回复
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