activity
20152021
most citedCausality Extraction based on Self-Attentive BiLSTM-CRF with Transferred Embeddings

144 citations · 333 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CV2021

Partial Video Domain Adaptation with Partial Adversarial Temporal Attentive Network

Yuecong Xu, Jianfei Yang, Haozhi Cao +3

Partial Domain Adaptation (PDA) is a practical and general domain adaptation scenario, which relaxes the fully shared label space assumption such that the source label space subsum…

cs.LG2021★ 3 cited

AdaptCL: Efficient Collaborative Learning with Dynamic and Adaptive Pruning

Guangmeng Zhou, Ke Xu, Qi Li +2

In multi-party collaborative learning, the parameter server sends a global model to each data holder for local training and then aggregates committed models globally to achieve pri…

cs.CR2021★ 1 cited

Data Poisoning Attacks and Defenses to Crowdsourcing Systems

Minghong Fang, Minghao Sun, Qi Li +3

A key challenge of big data analytics is how to collect a large volume of (labeled) data. Crowdsourcing aims to address this challenge via aggregating and estimating high-quality d…

cs.CR2021★ 119 cited

Data Poisoning Attacks to Deep Learning Based Recommender Systems

Hai Huang, Jiaming Mu, Neil Zhenqiang Gong +3

Recommender systems play a crucial role in helping users to find their interested information in various web services such as Amazon, YouTube, and Google News. Various recommender…

cs.LG2020

Automatic Historical Feature Generation through Tree-based Method in Ads Prediction

Hongjian Wang, Qi Li, Lanbo Zhang +4

Historical features are important in ads click-through rate (CTR) prediction, because they account for past engagements between users and ads. In this paper, we study how to effici…

cs.CV2020★ 39 cited

Cream of the Crop: Distilling Prioritized Paths For One-Shot Neural Architecture Search

Houwen Peng, Hao Du, Hongyuan Yu +3

One-shot weight sharing methods have recently drawn great attention in neural architecture search due to high efficiency and competitive performance. However, weight sharing across…