I-theory on depth vs width: hierarchical function composition
Deep learning networks with convolution, pooling and subsampling are a special case of hierar- chical architectures, which can be represented by trees (such as binary trees). Hierarchical as well as shallow networks can approximate functions of several variables, in particular those that are com- po...
| Main Authors: | , , |
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| Format: | Technical Report |
| Language: | en_US |
| Published: |
Center for Brains, Minds and Machines (CBMM)
2015
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| Subjects: | |
| Online Access: | http://hdl.handle.net/1721.1/100559 |