most citedUnsupervised Learning for Combinatorial Optimization with Principled Objective Relaxation

4 citations · 12 across the 10 of their papers we have counts for

collaborators

10 papers

cond-mat.dis-nn2023

Unsupervised machine learning for identifying phase transition using two-times clustering

Nan Wu, Zhuohan Li, Wanzhou Zhang

In recent years, developing unsupervised machine learning for identifying phase transition is a research direction. In this paper, we introduce a two-times clustering method that c…

cs.AR20233 cited

Gamora: Graph Learning based Symbolic Reasoning for Large-Scale Boolean Networks

Nan Wu, Yingjie Li, Cong Hao +3

Reasoning high-level abstractions from bit-blasted Boolean networks (BNs) such as gate-level netlists can significantly benefit functional verification, logic minimization, datapat…

eess.SP20231 cited

Air-Ground Integrated Sensing and Communications: Opportunities and Challenges

Zesong Fei, Xinyi Wang, Nan Wu +2

The air-ground integrated sensing and communications (AG-ISAC) network, which consists of unmanned aerial vehicles (UAVs) and ground terrestrial networks, offers unique capabilitie…

cs.CR2023

Privacy-Preserving Record Linkage for Cardinality Counting

Nan Wu, Dinusha Vatsalan, Mohamed Ali Kaafar +1

Several applications require counting the number of distinct items in the data, which is known as the cardinality counting problem. Example applications include health applications…

cs.IR2022

GReS: Graphical Cross-domain Recommendation for Supply Chain Platform

Zhiwen Jing, Ziliang Zhao, Yang Feng +6

Supply Chain Platforms (SCPs) provide downstream industries with numerous raw materials. Compared with traditional e-commerce platforms, data in SCPs is more sparse due to limited…

cs.LG2022

Heterogeneous Graph Tree Networks

Nan Wu, Chaofan Wang

Heterogeneous graph neural networks (HGNNs) have attracted increasing research interest in recent three years. Most existing HGNNs fall into two classes. One class is meta-path-bas…