most citedCombinatorial Optimization by Graph Pointer Networks and Hierarchical Reinforcement Learning

140 citations · 150 across the 4 of their papers we have counts for

collaborators

5 papers

cs.IR2020

Dual Attention Model for Citation Recommendation

Yang Zhang, Qiang Ma

Based on an exponentially increasing number of academic articles, discovering and citing comprehensive and appropriate resources has become a non-trivial task. Conventional citatio…

cs.LG2020

Learning to Solve Combinatorial Optimization Problems on Real-World Graphs in Linear Time

Iddo Drori, Anant Kharkar, William R. Sickinger +7

Combinatorial optimization algorithms for graph problems are usually designed afresh for each new problem with careful attention by an expert to the problem structure. In this work…

cs.CR20206 cited

Voice-Indistinguishability: Protecting Voiceprint in Privacy-Preserving Speech Data Release

Yaowei Han, Sheng Li, Yang Cao +2

With the development of smart devices, such as the Amazon Echo and Apple's HomePod, speech data have become a new dimension of big data. However, privacy and security concerns may…

cs.IR20204 cited

Citation Recommendations Considering Content and Structural Context Embedding

Yang Zhang, Qiang Ma

The number of academic papers being published is increasing exponentially in recent years, and recommending adequate citations to assist researchers in writing papers is a non-triv…

cs.LG2019140 cited

Combinatorial Optimization by Graph Pointer Networks and Hierarchical Reinforcement Learning

Qiang Ma, Suwen Ge, Danyang He +2

In this work, we introduce Graph Pointer Networks (GPNs) trained using reinforcement learning (RL) for tackling the traveling salesman problem (TSP). GPNs build upon Pointer Networ…