极限学习机 Extreme Learning Machines (ELM) 程序网址

http://www.ntu.edu.sg/home/egbhuang/

               

Extreme Learning Machines (ELM): Filling the Gap between Frank Rosenblatt's Dream and John von Neumann's Puzzle

- Network architectures: a homogenous hierarchical learning machine for partially or fully connected multi layers / single layer of (artifical or biological) networks with almost any type of practical (artifical) hidden nodes (or bilogical neurons).

- Learning theories: Learning can be made without iteratively tuning (articial) hidden nodes (or biological neurons).

- Learning algorithms: General, unifying and universal (optimization based) learning frameworks for compression, feature learning, clustering, regression and classification. Basic steps:

1) Learning are made layer wise (in white box)

2) Randomly generate (any nonliear piecewise) hidden neurons or inheritate hidden neuorns from ancestors

3) Learn the output weights in each hidden layer (with application based optimization constraints)

           

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