divide and conquer methods; graph theory; learning (artificial intelligence); synchronisation; LOE algorithm; arbitrary similarity transformation; directed k-nearest neighbor graph; divide-and-conquer paradigm; geometric embedding problem; group synchronization; local ordinal embedding algorithm; local-to-global algorithm; low-dimensional Euclidean space; machine learning community; ordinal information; rigid transformation; scale synchronization step; sensor network localization; unweighted kNN graph; Approximation algorithms; Multicore processing; Noise measurement; Pipelines; Robustness; Synchronization; Three-dimensional displays; eigenvector synchronization; graph embeddings; k-nearest-neighbor graphs; ordinal constraints;
机译:通过Shierarchical嵌入KNN图形来可视化大规模的高维数据
机译:一种新型量子音频隐写沉默分析方法,使用基于LSFQ的嵌入和基于QKNN的分类器
机译:序列同步标记序列及其隐写型多链路网络封面通道
机译:通过同步对未加权kNN图进行有序嵌入
机译:再谈无权无向图中的Top-K紧密度中心度。
机译:RKNNMDA:MiRNA-疾病关联预测的基于排名的KNN
机译:一种将未加权图嵌入树的常数近似算法