activity
20202025
most citedA Bi-Level Framework for Learning to Solve Combinatorial Optimization on Graphs

16 citations · 18 across the 6 of their papers we have counts for

collaborators

7 papers

cs.LG2025

Session-Level Dynamic Ad Load Optimization using Offline Robust Reinforcement Learning

Tao Liu, Qi Xu, Wei Shi +2

Session-level dynamic ad load optimization aims to personalize the density and types of delivered advertisements in real time during a user's online session by dynamically balancin…

cs.IR2024

Ads Supply Personalization via Doubly Robust Learning

Wei Shi, Chen Fu, Qi Xu +5

Ads supply personalization aims to balance the revenue and user engagement, two long-term objectives in social media ads, by tailoring the ad quantity and density. In the industry-…

cs.DS2022

A Practical Distributed ADMM Solver for Billion-Scale Generalized Assignment Problems

Jun Zhou, Feng Qi, Zhigang Hua +5

Assigning items to owners is a common problem found in various real-world applications, for example, audience-channel matching in marketing campaigns, borrower-lender matching in l…

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.LG2020

Variational Optimization for the Submodular Maximum Coverage Problem

Jian Du, Zhigang Hua, Shuang Yang

We examine the \emph{submodular maximum coverage problem} (SMCP), which is related to a wide range of applications. We provide the first variational approximation for this problem…