activity
20192021
most citedA Bi-Level Framework for Learning to Solve Combinatorial Optimization on Graphs

16 citations · 24 across the 8 of their papers we have counts for

collaborators

8 papers

cs.LG20211 cited

A framework for massive scale personalized promotion

Yitao Shen, Yue Wang, Xingyu Lu +6

Technology companies building consumer-facing platforms may have access to massive-scale user population. In recent years, promotion with quantifiable incentive has become a popula…

cs.LG202116 cited

A Bi-Level Framework for Learning to Solve Combinatorial Optimization on Graphs

Runzhong Wang, Zhigang Hua, Gan Liu +6

Combinatorial Optimization (CO) has been a long-standing challenging research topic featured by its NP-hard nature. Traditionally such problems are approximately solved with heuris…

cs.LG20211 cited

Learning to Schedule DAG Tasks

Zhigang Hua, Feng Qi, Gan Liu +1

Scheduling computational tasks represented by directed acyclic graphs (DAGs) is challenging because of its complexity. Conventional scheduling algorithms rely heavily on simple heu…

cs.AI2020

Language guided machine action

Feng Qi

Here we build a hierarchical modular network called Language guided machine action (LGMA), whose modules process information stream mimicking human cortical network that allows to…

cs.CV2020

Visualizing and Understanding Vision System

Feng Qi, Guanjun Jiang

How the human vision system addresses the object identity-preserving recognition problem is largely unknown. Here, we use a vision recognition-reconstruction network (RRN) to inves…

q-bio.NC20202 cited

Human-like general language processing

Feng Qi, Guanjun Jiang

Using language makes human beings surpass animals in wisdom. To let machines understand, learn, and use language flexibly, we propose a human-like general language processing (HGLP…