公开(公告)号：US20180174042A1

公开(公告)日：2018-06-21

申请号：US15385334

申请日：2016-12-20

Applicant: Intel Corporation

Inventor： Narayan Srinivasa ,  Yongqiang Cao ,  Andreas Wild

IPC: G06N3/08 ,  G06N3/04

CPC classification number: G06N3/08 ,  G06N3/0454 ,  G06N3/049

Abstract: Systems and methods for supervised learning and cascaded training of a neural network are described. In an example, a supervised process is used for strengthening connections to classifier neurons, with a supervised learning process of receiving a first spike at a classifier neuron from a processing neuron in response to training data, and receiving an out-of-band communication of a second desired (artificial) spike at the classifier neuron that corresponds to the classification of the training data. As a result of spike timing dependent plasticity, connections to the classifier neuron are strengthened. In another example, a cascaded technique is disclosed to generate a plurality of trained neural networks that are separately initialized and trained based on different types or forms of training data, which may be used with cascaded or parallel operation of the plurality of trained neural networks.

公开(公告)号：US20190042916A1

公开(公告)日：2019-02-07

申请号：US16147573

申请日：2018-09-28

Applicant: Intel Corporation

Inventor： Yongqiang Cao ,  Helin Cao

IPC: G06N3/04 ,  G06N3/08 ,  G06F1/20

Abstract: Thermal management of a computing device is achieved using reward-based updating of synaptic weights of a spiking neural network. The thermal management is achieved using machine readable mediums having instructions that cause a processor to, during a first time window, generate weights to be applied to input trains of spikes from input neurons of a spiking neural network. The instructions further cause the processor to, based on a number of spikes included in an output train of spikes output by an output neuron of the spiking neural network during the first time window, adjust the workload of the processor, and, based on whether a surface temperature of an enclosure housing the processor meets a first threshold or a workload of the processor meets a second threshold, generate a penalty. The instructions also cause the processor to train the spiking neural network by updating the weights.