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New computational algorithms make it possible to build neural networks with many input nodes and many layers, and distinguish "deep learning" of these networks from previous work on artificial neural nets.
Ali Shafahi, Mahyar Najibi, Mohammad Amin Ghiasi, Zheng Xu, John Dickerson, Christoph Studer, Larry S. Davis, Gavin Taylor, Tom Goldstein
Neural Information Processing SystemsFeb-12-2026, 15:15:50 GMT
Neural Information Processing Systems http://nips.cc/
Jianghong Shi, Eric Shea-Brown, Michael Buice
Neural Information Processing SystemsFeb-12-2026, 15:06:39 GMT
Neural Information Processing SystemsFeb-12-2026, 15:05:59 GMT
Zhiqing Sun, Zhuohan Li, Haoqing Wang, Di He, Zi Lin, Zhihong Deng
Neural Information Processing SystemsFeb-12-2026, 14:58:07 GMT
Neural Information Processing SystemsFeb-12-2026, 14:57:28 GMT
Neural Information Processing SystemsFeb-12-2026, 14:57:20 GMT
Nils Bjorck, Carla P. Gomes, Bart Selman, Kilian Q. Weinberger
Neural Information Processing SystemsFeb-12-2026, 14:56:59 GMT
Its tendency to improve accuracy and speed up training have established BN as a favorite technique in deep learning.
Neural Information Processing SystemsFeb-12-2026, 14:56:19 GMT
Eric Wong, Frank Schmidt, Jan Hendrik Metzen, J. Zico Kolter
Neural Information Processing SystemsFeb-12-2026, 14:53:30 GMT
Neural Information Processing SystemsFeb-12-2026, 14:53:15 GMT