5 citations · 5 across the 3 of their papers we have counts for
3 papers
cs.DB2026
LEARNT: A Practical Estimator for Cardinality of LIKE Queries with Formal Accuracy Guarantees
Hai Lan, Zhifeng Bao, Divesh Srivastava +3
We study the problem of cardinality estimation for LIKE queries on string data, focusing on the most common patterns in real workloads: prefix, suffix, and substring queries. We pr…
cs.AI2021
Imitate TheWorld: A Search Engine Simulation Platform
Yongqing Gao, Guangda Huzhang, Weijie Shen +4
Recent E-commerce applications benefit from the growth of deep learning techniques. However, we notice that many works attempt to maximize business objectives by closely matching o…
cs.LG2020★ 5 cited
AliExpress Learning-To-Rank: Maximizing Online Model Performance without Going Online
Guangda Huzhang, Zhen-Jia Pang, Yongqing Gao +8
Learning-to-rank (LTR) has become a key technology in E-commerce applications. Most existing LTR approaches follow a supervised learning paradigm from offline labeled data collecte…