公开(公告)号：US11860977B1

公开(公告)日：2024-01-02

申请号：US17307701

申请日：2021-05-04

Applicant: Amazon Technologies, Inc.

Inventor： Yifan Xing ,  Tianjun Xiao ,  Tong He ,  Yongxin Wang ,  Yuanjun Xiong ,  Wei Xia ,  David Paul Wipf ,  Zheng Zhang ,  Stefano Soatto

IPC: G06F18/2323 ,  G06N20/00 ,  G06F18/2415 ,  G06F18/23213 ,  G06F18/2413

CPC classification number: G06F18/2323 ,  G06F18/23213 ,  G06F18/2415 ,  G06F18/24147 ,  G06N20/00

Abstract: Techniques for performing visual clustering with a hierarchical graph neural network framework including a joint linkage prediction and density estimation graph model are described. Embodiments herein recurrently run the joint linkage prediction and density estimation graph model to generate intermediate clusters in multiple iterations (e.g., until convergence) to obtain a final clustering result. In certain embodiments, for each iteration, the input graph contains nodes that are merged from nodes assigned to intermediate clusters from the previous iteration. By using a small and fixed bandwidth k in each iteration, embodiments herein alleviate the sensitivity to the k selection for different clustering applications. Certain embodiments herein remove the tuning of a different k (e.g., k-bandwidth) for k-nearest neighbor graph construction over different clustering applications.