Schmidhuber J. Deep learning in neural networks: an overview. Neural Netw 2015;61:85-117.Schmidhuber J. Deep Learning in neural networks: An overview.[J]. Neural Networks the Official Journal of the Internationa
Title Deep Learning in Neural Networks: An Overview Author(s) Juergen Schmidhuber Publisher: arxiv.org and University of Lugano; eBook (Creative Commons Licensed) License(s): Creative Commons License (CC) Hardcover N/A eBook PDF (206 pages) Language: English ISBN-10: N/A ISBN-13: N/A...
Neural Networks and Deep Learning 3.6 Activation Function sigmoid: a=11+e−za=11+e−z 取值在(0,1)之间,除非是二分类的输出层,一般不选用,因为tanhtanh比sigmoid表现要好。 tanh: a=ez−e−zez+e−za=ez−e−zez+e−z 取值在(-1,1),有数据中心... ...
Deep learning is a subset of machine learning (ML) that uses neural networks with many layers, known as deep neural networks (DNNs). These networks consist of numerous interconnected units called neurons or nodes that act as feature detectors. Each neural network has an input layer to receive ...
Deep neural networks are classified into two networks (shallow and deep), in which shallow network is generally with 1 or 2 hidden layers, and deep network with 3 or more hidden layers. The Deep learning mainly consists of three layers, such as an input layer or one to many convolutional ...
Deep Learning in Neural Networks: An Overview byJuergen Schmidhuber-arXiv In recent years, deep artificial neural networks (including recurrent ones) have won numerous contests in pattern recognition and machine learning. This historical survey compactly summarises relevant work, much of it from the ...
Deep learning in neural networks: an overview. Neural Netw. 61, 85–117 (2015). PubMed Google Scholar LeCun, Y., Bengio, Y. & Hinton, G. Deep learning. Nature 521, 436–444 (2015). CAS PubMed Google Scholar Bottou, L. in Proceedings of Neuro-Nımes ‘91 12 (EC2, 1991)....
Artificial neural networks are not new; they have been around for about 50 years and got some practical recognition after the mid-1980s with the introduction of a method (backpropagation) that allowed for the training of multiple-layer neural networks. However, the true birth of deep learning ...
概括来讲,一旦发现正在优化多于一个的目标函数,你就可以通过多任务学习来有效求解(Generally, as soon as you find yourself optimizing more than one loss function, you are effectively doing multi-task learning (in contrast to single-task learning))。在那种场景中,这样做有利于想清楚我们真正要做的是什么...
Draft: Deep Learning in Neural Networks: An Overview Technical Report IDSIA-03-14 / arXiv:1404.7828 (v1.5) [cs.NE] J¨ urgen Schmidhuber The Swiss AI Lab IDSIA Istituto Dalle Molle di Studi sull’Intelligenza Arti?ciale University of Lugano & SUPSI Galleria 2, 6928 Manno-Lugano Switzerland...