In this paper, we propose two-channel filter-bank designs for signals defined on arbitrary graphs. These filter-banks are local, invertible and critically sampled. Depending on th...
Constructing a good graph to represent data structures is critical for many important machine learning tasks such as clustering and classification. This paper proposes a novel no...
Liansheng Zhuang, Haoyuan Gao, Zhouchen Lin, Yi Ma...
— We present a new linear time technique to compute criticality information in a timing graph by dividing it into “zones”. Errors in using tightness probabilities for critica...
Hushrav Mogal, Haifeng Qian, Sachin S. Sapatnekar,...
A plethora of random graph models have been developed in recent years to study a range of problems on networks, driven by the wide availability of data from many social, telecommu...