activity
20122021
most citedAP-10K: A Benchmark for Animal Pose Estimation in the Wild

36 citations · 41 across the 5 of their papers we have counts for

collaborators

10 papers

cs.CV202136 cited

AP-10K: A Benchmark for Animal Pose Estimation in the Wild

Hang Yu, Yufei Xu, Jing Zhang +3

Accurate animal pose estimation is an essential step towards understanding animal behavior, and can potentially benefit many downstream applications, such as wildlife conservation.…

cs.AI2021

Multi-Agent Cooperative Bidding Games for Multi-Objective Optimization in e-Commercial Sponsored Search

Ziyu Guan, Hongchang Wu, Qingyu Cao +7

Bid optimization for online advertising from single advertiser's perspective has been thoroughly investigated in both academic research and industrial practice. However, existing w…

cs.IR2019

IntentGC: a Scalable Graph Convolution Framework Fusing Heterogeneous Information for Recommendation

Jun Zhao, Zhou Zhou, Ziyu Guan +4

The remarkable progress of network embedding has led to state-of-the-art algorithms in recommendation. However, the sparsity of user-item interactions (i.e., explicit preferences)…

cs.IR2019

Personalized Attraction Enhanced Sponsored Search with Multi-task Learning

Wei Zhao, Boxuan Zhang, Beidou Wang +6

We study a novel problem of sponsored search (SS) for E-Commerce platforms: how we can attract query users to click product advertisements (ads) by presenting them features of prod…

cs.IR20192 cited

Query-based Interactive Recommendation by Meta-Path and Adapted Attention-GRU

Yu Zhu, Yu Gong, Qingwen Liu +6

Recently, interactive recommender systems are becoming increasingly popular. The insight is that, with the interaction between users and the system, (1) users can actively interven…

cs.IR20192 cited

Exact-K Recommendation via Maximal Clique Optimization

Yu Gong, Yu Zhu, Lu Duan +5

This paper targets to a novel but practical recommendation problem named exact-K recommendation. It is different from traditional top-K recommendation, as it focuses more on (const…