%0 Journal Article %1 poggio2017deepbut %A Poggio, Tomaso %A Mhaskar, Hrushikesh %A Rosasco, Lorenzo %A Miranda, Brando %A Liao, Qianli %D 2017 %J International Journal of Automation and Computing %K approximate deep-learning generalization theory %P 1--17 %T Why and when can deep-but not shallow-networks avoid the curse of dimensionality: A review %U https://cbmm.mit.edu/publications/why-and-when-can-deep-not-shallow-networks-avoid-curse-dimensionality-review-0

@article{poggio2017deepbut, added-at = {2019-10-03T12:35:37.000+0200}, author = {Poggio, Tomaso and Mhaskar, Hrushikesh and Rosasco, Lorenzo and Miranda, Brando and Liao, Qianli}, biburl = {https://www.bibsonomy.org/bibtex/22b688147c794d234e82d8a9de41c5e20/kirk86}, description = {Why and when can deep-but not shallow-networks avoid the curse of dimensionality: A review | The Center for Brains, Minds & Machines}, interhash = {99e38247d0adfb5f03c3fb72f78d657e}, intrahash = {2b688147c794d234e82d8a9de41c5e20}, journal = {International Journal of Automation and Computing}, keywords = {approximate deep-learning generalization theory}, pages = {1--17}, timestamp = {2019-10-03T12:35:37.000+0200}, title = {Why and when can deep-but not shallow-networks avoid the curse of dimensionality: A review}, url = {https://cbmm.mit.edu/publications/why-and-when-can-deep-not-shallow-networks-avoid-curse-dimensionality-review-0}, year = 2017 }