68 citations · 185 across the 18 of their papers we have counts for
4 papers · 1 filter
Hybrid Encoder: Towards Efficient and Precise Native AdsRecommendation via Hybrid Transformer Encoding Networks
Junhan Yang, Zheng Liu, Bowen Jin +7
Transformer encoding networks have been proved to be a powerful tool of understanding natural languages. They are playing a critical role in native ads service, which facilitates t…
Multi-Interest-Aware User Modeling for Large-Scale Sequential Recommendations
Jianxun Lian, Iyad Batal, Zheng Liu +4
Precise user modeling is critical for online personalized recommendation services. Generally, users' interests are diverse and are not limited to a single aspect, which is particul…
Multi-Channel Sequential Behavior Networks for User Modeling in Online Advertising
Iyad Batal, Akshay Soni
Multiple content providers rely on native advertisement for revenue by placing ads within the organic content of their pages. We refer to this setting as ``queryless'' to different…
RIPML: A Restricted Isometry Property based Approach to Multilabel Learning
Akshay Soni, Yashar Mehdad
The multilabel learning problem with large number of labels, features, and data-points has generated a tremendous interest recently. A recurring theme of these problems is that onl…