activity
20182022
most cited: Field-matrixed Factorization Machines for Recommender Systems

89 citations · 165 across the 9 of their papers we have counts for

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Showing cs.LGShow all

5 papers · 1 filter

cs.LG202112 cited

Follow the Prophet: Accurate Online Conversion Rate Prediction in the Face of Delayed Feedback

Haoming Li, Feiyang Pan, Xiang Ao +6

The delayed feedback problem is one of the imperative challenges in online advertising, which is caused by the highly diversified feedback delay of a conversion varying from a few…

cs.LG2020

DeepLight: Deep Lightweight Feature Interactions for Accelerating CTR Predictions in Ad Serving

Wei Deng, Junwei Pan, Tian Zhou +3

Click-through rate (CTR) prediction is a crucial task in online display advertising. The embedding-based neural networks have been proposed to learn both explicit feature interacti…

cs.LG2019

A Batched Multi-Armed Bandit Approach to News Headline Testing

Yizhi Mao, Miao Chen, Abhinav Wagle +3

Optimizing news headlines is important for publishers and media sites. A compelling headline will increase readership, user engagement and social shares. At Yahoo Front Page, headl…

cs.LG2019

Predicting Different Types of Conversions with Multi-Task Learning in Online Advertising

Junwei Pan, Yizhi Mao, Alfonso Lobos Ruiz +2

Conversion prediction plays an important role in online advertising since Cost-Per-Action (CPA) has become one of the primary campaign performance objectives in the industry. Unlik…

cs.LG2018

Field-weighted Factorization Machines for Click-Through Rate Prediction in Display Advertising

Junwei Pan, Jian Xu, Alfonso Lobos Ruiz +4

Click-through rate (CTR) prediction is a critical task in online display advertising. The data involved in CTR prediction are typically multi-field categorical data, i.e., every fe…