activity
20152023
most citedLifelong Sequential Modeling with Personalized Memorization for User Response Prediction

126 citations · 494 across the 31 of their papers we have counts for

collaborators
Showing 2020Show all

7 papers · 1 filter

cs.IR2020★ 11 cited

Exploration in Online Advertising Systems with Deep Uncertainty-Aware Learning

Chao Du, Zhifeng Gao, Shuo Yuan +7

Modern online advertising systems inevitably rely on personalization methods, such as click-through rate (CTR) prediction. Recent progress in CTR prediction enjoys the rich represe…

cs.AI2020★ 1 cited

Learning to Infer User Hidden States for Online Sequential Advertising

Zhaoqing Peng, Junqi Jin, Lan Luo +11

To drive purchase in online advertising, it is of the advertiser's great interest to optimize the sequential advertising strategy whose performance and interpretability are both im…

cs.SI2020★ 11 cited

A Deep Prediction Network for Understanding Advertiser Intent and Satisfaction

Liyi Guo, Rui Lu, Haoqi Zhang +9

For e-commerce platforms such as Taobao and Amazon, advertisers play an important role in the entire digital ecosystem: their behaviors explicitly influence users' browsing and sho…

cs.LG2020★ 9 cited

Dynamic Knapsack Optimization Towards Efficient Multi-Channel Sequential Advertising

Xiaotian Hao, Zhaoqing Peng, Yi Ma +12

In E-commerce, advertising is essential for merchants to reach their target users. The typical objective is to maximize the advertiser's cumulative revenue over a period of time un…

stat.ML2020★ 7 cited

Learning Optimal Tree Models Under Beam Search

Jingwei Zhuo, Ziru Xu, Wei Dai +4

Retrieving relevant targets from an extremely large target set under computational limits is a common challenge for information retrieval and recommendation systems. Tree models, w…

cs.IR2020★ 1 cited

A Deep Recurrent Survival Model for Unbiased Ranking

Jiarui Jin, Yuchen Fang, Weinan Zhang +7

Position bias is a critical problem in information retrieval when dealing with implicit yet biased user feedback data. Unbiased ranking methods typically rely on causality models a…

cs.DC2020

Learning to Accelerate Heuristic Searching for Large-Scale Maximum Weighted b-Matching Problems in Online Advertising

Xiaotian Hao, Junqi Jin, Jianye Hao +7

Bipartite b-matching is fundamental in algorithm design, and has been widely applied into economic markets, labor markets, etc. These practical problems usually exhibit two distinc…