公开(公告)号：US20200027210A1

公开(公告)日：2020-01-23

申请号：US16515890

申请日：2019-07-18

申请人： NVIDIA Corporation

发明人： Nicholas Haemel ,  Bojan Vukojevic ,  Risto Haukioja ,  Andrew Feng ,  Yan Cheng ,  Sachidanand Alle ,  Daguang Xu ,  Holger Reinhard Roth ,  Johnny Israeli

IPC分类号： G06T7/00 ,  G16H30/20 ,  G06T19/00 ,  G06N5/04 ,  G06N3/04 ,  G06T7/10 ,  G06F9/455 ,  G06F9/54 ,  G06T5/00

摘要： In various examples, a virtualized computing platform for advanced computing operations—including image reconstruction, segmentation, processing, analysis, visualization, and deep learning—may be provided. The platform may allow for inference pipeline customization by selecting, organizing, and adapting constructs of task containers for local, on-premises implementation. Within the task containers, machine learning models generated off-premises may be leveraged and updated for location specific implementation to perform image processing operations. As a result, and using the virtualized computing platform, facilities such as hospitals and clinics may more seamlessly train, deploy, and integrate machine learning models within a production environment for providing informative and actionable medical information to practitioners.

公开(公告)号：US11804050B1

公开(公告)日：2023-10-31

申请号：US16671001

申请日：2019-10-31

申请人： NVIDIA Corporation

发明人： Fausto Milletari ,  Maximilian Baust ,  Nicola Rieke ,  Wenqi Li ,  Daguang Xu ,  Andrew Feng ,  Rong Ou ,  Yan Cheng

IPC分类号： G06V20/64 ,  G06N3/063 ,  G06N3/08 ,  G06N3/045

CPC分类号： G06V20/64 ,  G06N3/045 ,  G06N3/063 ,  G06N3/08

摘要： Apparatuses, systems, and techniques to collaboratively train one or more machine learning models. Parameter reviewers may be configured to compare sets of machine learning model parameter information in order to generate one or more machine learning models, such as neural networks.

公开(公告)号：US12072954B1

公开(公告)日：2024-08-27

申请号：US16676314

申请日：2019-11-06

申请人： NVIDIA Corporation

发明人： Wenqi Li ,  Fausto Milletari ,  Daguang Xu ,  Yan Cheng ,  Nicola Christin Rieke ,  Charles Jonathan Hancox ,  Wentao Zhu ,  Rong Ou ,  Andrew Feng

IPC分类号： G06T7/00 ,  G06F7/57 ,  G06F18/214 ,  G06N3/045 ,  G06N3/063 ,  G06N3/08 ,  G06V10/94 ,  G16H30/20

CPC分类号： G06F18/2148 ,  G06F7/57 ,  G06N3/045 ,  G06N3/063 ,  G06N3/08 ,  G06V10/955 ,  G16H30/20 ,  G06V2201/03

摘要： Apparatuses, systems, and techniques to perform federated training of neural networks while maintaining control over dissemination of local models of neural networks from which aspects of local training data might be extracted. In at least one embodiment, a neural network is trained on local training data and a local model is provided to be aggregated with other local models into a global model that is in turn used for further local model training, wherein a provided local model or training is adjusted to reduce an ability to extract aspects of local training data therefrom.