— Constrained clustering (semi-supervised learning) techniques have attracted more attention in recent years. However, the commonly used constraints are restricted to the instanc...
Abstract. A new constrained model is discussed as a way of incorporating efficiently a priori expert knowledge into a clustering problem of a given individual set. The first innova...
We propose a novel framework for constrained spectral
clustering with pairwise constraints which specify whether
two objects belong to the same cluster or not. Unlike previous
m...
Zhenguo Li (The Chinese University of Hong Kong), ...
In this paper we present a system level technique for mapping large, multiple-IP-block designs to channel-width constrained FPGAs. Most FPGA clustering tools [2, 3, 11] aim to red...
Abstract. Clustering high dimensional data with sparse features is challenging because pairwise distances between data items are not informative in high dimensional space. To addre...