公开(公告)号：US20230401489A1

公开(公告)日：2023-12-14

申请号：US18239542

申请日：2023-08-29

Applicant: NEC Corporation

Inventor： Hao ZHANG ,  Shinji NAKADAI ,  Kenji FUKUMIZU

IPC: G06N20/10 ,  G06F17/14 ,  G06F18/214 ,  G06F18/2135 ,  G06F18/213

CPC classification number: G06N20/10 ,  G06F17/14 ,  G06F18/214 ,  G06F18/21355 ,  G06F18/213

Abstract: In a kernel learning apparatus, a data preprocessing circuitry preprocesses and represents each data example as a collection of feature representations that need to be interpreted. An explicit feature mapping circuit designs a kernel function with an explicit feature map to embed the feature representations of data into a nonlinear feature space and to produce the explicit feature map for the designed kernel function to train a predictive model. A convex problem formulating circuitry formulates a non-convex problem for training the predictive model into a convex optimization problem based on the explicit feature map. An optimal solution solving circuitry solves the convex optimization problem to obtain a globally optimal solution for training an interpretable predictive model.

公开(公告)号：US20230409981A1

公开(公告)日：2023-12-21

申请号：US18240221

申请日：2023-08-30

Applicant: NEC Corporation

Inventor： Hao ZHANG ,  Shinji NAKADAI ,  Kenji FUKUMIZU

IPC: G06N20/10 ,  G06F17/14 ,  G06F18/214 ,  G06F18/2135 ,  G06F18/213

CPC classification number: G06N20/10 ,  G06F17/14 ,  G06F18/214 ,  G06F18/21355 ,  G06F18/213

Abstract: In a kernel learning apparatus, a data preprocessing circuitry preprocesses and represents each data example as a collection of feature representations that need to be interpreted. An explicit feature mapping circuit designs a kernel function with an explicit feature map to embed the feature representations of data into a nonlinear feature space and to produce the explicit feature map for the designed kernel function to train a predictive model. A convex problem formulating circuitry formulates a non-convex problem for training the predictive model into a convex optimization problem based on the explicit feature map. An optimal solution solving circuitry solves the convex optimization problem to obtain a globally optimal solution for training an interpretable predictive model.

公开(公告)号：US20210027204A1

公开(公告)日：2021-01-28

申请号：US17041733

申请日：2018-03-26

Applicant: NEC Corporation

Inventor： Hao ZHANG ,  Shinji NAKADAI ,  Kenji FUKUMIZU

IPC: G06N20/10 ,  G06F17/14 ,  G06K9/62

Abstract: In a kernel learning apparatus, a data preprocessing circuitry preprocesses and represents each data example as a collection of feature representations that need to be interpreted. An explicit feature mapping circuit designs a kernel function with an explicit feature map to embed the feature representations of data into a nonlinear feature space and to produce the explicit feature map for the designed kernel function to train a predictive model. A convex problem formulating circuitry formulates a non-convex problem for training the predictive model into a convex optimization problem based on the explicit feature map. An optimal solution solving circuitry solves the convex optimization problem to obtain a globally optimal solution for training an interpretable predictive model.