11 citations · 26 across the 9 of their papers we have counts for
9 papers
FAN: Fatigue-Aware Network for Click-Through Rate Prediction in E-commerce Recommendation
Ming Li, Naiyin Liu, Xiaofeng Pan +5
Since clicks usually contain heavy noise, increasing research efforts have been devoted to modeling implicit negative user behaviors (i.e., non-clicks). However, they either rely o…
CHRONOS: Time-Aware Zero-Shot Identification of Libraries from Vulnerability Reports
Yunbo Lyu, Thanh Le-Cong, Hong Jin Kang +5
Tools that alert developers about library vulnerabilities depend on accurate, up-to-date vulnerability databases which are maintained by security researchers. These databases recor…
CaFT: Clustering and Filter on Tokens of Transformer for Weakly Supervised Object Localization
Ming Li
Weakly supervised object localization (WSOL) is a challenging task to localize the object by only category labels. However, there is contradiction between classification and locali…
MetaCVR: Conversion Rate Prediction via Meta Learning in Small-Scale Recommendation Scenarios
Xiaofeng Pan, Ming Li, Jing Zhang +5
Different from large-scale platforms such as Taobao and Amazon, CVR modeling in small-scale recommendation scenarios is more challenging due to the severe Data Distribution Fluctua…
Automatic annotation of visual deep neural networks
Ming Li, ChenHao Guo
Computer vision is widely used in the fields of driverless, face recognition and 3D reconstruction as a technology to help or replace human eye perception images or multidimensiona…
A Next Basket Recommendation Reality Check
Ming Li, Sami Jullien, Mozhdeh Ariannezhad +1
The goal of a next basket recommendation (NBR) system is to recommend items for the next basket for a user, based on the sequence of their prior baskets. Recently, a number of meth…
A Data-Driven Method for Recognizing Automated Negotiation Strategies
Ming Li, Pradeep K. Murukannaiah, Catholijn M. Jonker
Understanding an opponent agent helps in negotiating with it. Existing works on understanding opponents focus on preference modeling (or estimating the opponent's utility function)…
Efficient Spatial Anti-Aliasing Rendering for Line Joins on Vector Maps
Chaoyang He, Ming Li
The spatial anti-aliasing technique for line joins (intersections of the road segments) on vector maps is exclusively crucial to visual experience and system performance. Due to li…
Reliable Weakly Supervised Learning: Maximize Gain and Maintain Safeness
Lan-Zhe Guo, Yu-Feng Li, Ming Li +3
Weakly supervised data are widespread and have attracted much attention. However, since label quality is often difficult to guarantee, sometimes the use of weakly supervised data w…