103 citations · 288 across the 38 of their papers we have counts for
14 papers · 1 filter
Identification of deuteron at BESIII
Wei Wang, Bo Zheng, Jia Jia Qin +1
The identification of deuteron with momentum in range of - GeV/ has been studied with the specific ionization energy loss information, using the data sample collecte…
Prospects of violation in decay with polarized electron beam at STCF
Sheng Zeng, Yue Xu, Xiao Rong Zhou +2
Based on Monte Carlo (MC) events produced from a longitudinally-polarized electron beam, the sensitivity of violation of decay i…
Adversarial Constrained Bidding via Minimax Regret Optimization with Causality-Aware Reinforcement Learning
Haozhe Wang, Chao Du, Panyan Fang +3
The proliferation of the Internet has led to the emergence of online advertising, driven by the mechanics of online auctions. In these repeated auctions, software agents participat…
Rec4Ad: A Free Lunch to Mitigate Sample Selection Bias for Ads CTR Prediction in Taobao
Jingyue Gao, Shuguang Han, Han Zhu +4
Click-Through Rate (CTR) prediction serves as a fundamental component in online advertising. A common practice is to train a CTR model on advertisement (ad) impressions with user f…
COPR: Consistency-Oriented Pre-Ranking for Online Advertising
Zhishan Zhao, Jingyue Gao, Yu Zhang +8
Cascading architecture has been widely adopted in large-scale advertising systems to balance efficiency and effectiveness. In this architecture, the pre-ranking model is expected t…
On Structural Expressive Power of Graph Transformers
Wenhao Zhu, Tianyu Wen, Guojie Song +2
Graph Transformer has recently received wide attention in the research community with its outstanding performance, yet its structural expressive power has not been well analyzed. I…
Latent Magic: An Investigation into Adversarial Examples Crafted in the Semantic Latent Space
BoYang Zheng
Adversarial attacks against Deep Neural Networks(DNN) have been a crutial topic ever since \cite{goodfellow} purposed the vulnerability of DNNs. However, most prior works craft adv…
FedAds: A Benchmark for Privacy-Preserving CVR Estimation with Vertical Federated Learning
Penghui Wei, Hongjian Dou, Shaoguo Liu +4
Conversion rate (CVR) estimation aims to predict the probability of conversion event after a user has clicked an ad. Typically, online publisher has user browsing interests and cli…
Information-containing Adversarial Perturbation for Combating Facial Manipulation Systems
Yao Zhu, Yuefeng Chen, Xiaodan Li +4
With the development of deep learning technology, the facial manipulation system has become powerful and easy to use. Such systems can modify the attributes of the given facial ima…
Leveraging Pretrained Representations with Task-related Keywords for Alzheimer's Disease Detection
Jinchao Li, Kaitao Song, Junan Li +5
With the global population aging rapidly, Alzheimer's disease (AD) is particularly prominent in older adults, which has an insidious onset and leads to a gradual, irreversible dete…
Gradient Coordination for Quantifying and Maximizing Knowledge Transference in Multi-Task Learning
Xuanhua Yang, Jianxin Zhao, Shaoguo Liu +2
Multi-task learning (MTL) has been widely applied in online advertising and recommender systems. To address the negative transfer issue, recent studies have proposed optimization m…
Hybrid Contrastive Constraints for Multi-Scenario Ad Ranking
Shanlei Mu, Penghui Wei, Wayne Xin Zhao +3
Multi-scenario ad ranking aims at leveraging the data from multiple domains or channels for training a unified ranking model to improve the performance at each individual scenario.…
RLTP: Reinforcement Learning to Pace for Delayed Impression Modeling in Preloaded Ads
Penghui Wei, Yongqiang Chen, Shaoguo Liu +2
To increase brand awareness, many advertisers conclude contracts with advertising platforms to purchase traffic and then deliver advertisements to target audiences. In a whole deli…
HIT-SCIR at MMNLU-22: Consistency Regularization for Multilingual Spoken Language Understanding
Bo Zheng, Zhouyang Li, Fuxuan Wei +3
Multilingual spoken language understanding (SLU) consists of two sub-tasks, namely intent detection and slot filling. To improve the performance of these two sub-tasks, we propose…