Loading patent…
AssigneeIntel Corporation
InventorsLibin Wang, Yiwen Guo, Anbang Yao, Dongqi Cai, Lin Xu, Ping Hu, Shangong Wang, Wenhua Cheng, Yurong Chen
Estimating the term…
Methods and systems are disclosed for boosting deep neural networks for deep learning. In one example, in a deep neural network including a first shallow network and a second shallow network, a first training sample is processed by the first shallow network using equal weights. A loss for the first shallow network is determined based on the processed training sample using equal weights. Weights for the second shallow network are adjusted based on the determined loss for the first shallow network. A second training sample is processed by the second shallow network using the adjusted weights. In another example, in a deep neural network including a first weak network and a second weak network, a first subset of training samples is processed by the first weak network using initialized weights. A classification error for the first weak network on the first subset of training samples is determined. The second weak network is boosted using the determined classification error of the first weak network with adjusted weights. A second subset of training samples is processed by the second weak network using the adjusted weights.
In a deep neural network including a first shallow network and a second shallow network, a method comprising:
A system for a server comprising:
A deep neural network (DNN) system comprising:
At least one machine-readable medium comprising a plurality of instructions, executed on a computing device, to facilitate the computing device to perform one or more operations comprising:
13-20. (canceled)
Dependencies are inferred from the claim text.