1 code implementation • 26 Jan 2025 • Zhijian Duan, Yusen Huo, Tianyu Wang, Zhilin Zhang, Yeshu Li, Chuan Yu, Jian Xu, Bo Zheng, Xiaotie Deng
Extensive simulation experiments and real-world A/B testing validate the effectiveness of ABPlanner, demonstrating its capability to enhance the cumulative value achieved by auto-bidders.
1 code implementation • 14 Dec 2024 • Kefan Su, Yusen Huo, Zhilin Zhang, Shuai Dou, Chuan Yu, Jian Xu, Zongqing Lu, Bo Zheng
We believe that AuctionNet is applicable not only to research on bid decision-making in ad auctions but also to the general area of decision-making in large-scale games.
no code implementations • 27 Nov 2024 • Jie Wang, Yichen Wang, Zhilin Zhang, Jianhao Zeng, Kaidi Wang, Zhiyang Chen
With strong expressive capabilities in Large Language Models(LLMs), generative models effectively capture sentiment structures and deep semantics, however, challenges remain in fine-grained sentiment classification across multi-lingual and complex contexts.
no code implementations • 28 Oct 2024 • Zhilin Zhang, Jie Wang, Ruiqi Zhu, Xiaoliang Gong
Medical Visual Question Answering (MedVQA) has attracted growing interest at the intersection of computer vision and natural language processing.
no code implementations • 17 Jul 2024 • Jiahong Chen, Zhilin Zhang, Lucy Li, Behzad Shahrasbi, Arjun Mishra
Domain adversarial training has shown its effective capability for finding domain invariant feature representations and been successfully adopted for various domain adaptation tasks.
no code implementations • 25 May 2024 • Jiayan Guo, Yusen Huo, Zhilin Zhang, Tianyu Wang, Chuan Yu, Jian Xu, Yan Zhang, Bo Zheng
Auto-bidding plays a crucial role in facilitating online advertising by automatically providing bids for advertisers.
no code implementations • 1 May 2024 • Zhilin Zhang
Visual Question Answering (VQA) has emerged as a highly engaging field in recent years, with increasing research focused on enhancing VQA accuracy through advanced models such as Transformers.
no code implementations • 5 Mar 2024 • Zhen Gong, Lvyin Niu, Yang Zhao, Miao Xu, Zhenzhe Zheng, Haoqi Zhang, Zhilin Zhang, Fan Wu, Rongquan Bai, Chuan Yu, Jian Xu, Bo Zheng
Through extensive offline and online experiments, we demonstrate the effectiveness and efficiency of our method, and we obtain a 7. 01% lift in Gross Merchandise Volume, a 7. 42% lift in Return on Investment, and a 3. 26% lift in ad buy count.
no code implementations • 23 Feb 2024 • Haoming Li, Yusen Huo, Shuai Dou, Zhenzhe Zheng, Zhilin Zhang, Chuan Yu, Jian Xu, Fan Wu
The trained policy can subsequently be deployed for further data collection, resulting in an iterative training framework, which we refer to as iterative offline RL.
no code implementations • 19 Feb 2024 • Zhijian Duan, Haoran Sun, Yichong Xia, Siqiang Wang, Zhilin Zhang, Chuan Yu, Jian Xu, Bo Zheng, Xiaotie Deng
Identifying high-revenue mechanisms that are both dominant strategy incentive compatible (DSIC) and individually rational (IR) is a fundamental challenge in auction design.
1 code implementation • 11 Jun 2021 • Chao Wen, Miao Xu, Zhilin Zhang, Zhenzhe Zheng, Yuhui Wang, Xiangyu Liu, Yu Rong, Dong Xie, Xiaoyang Tan, Chuan Yu, Jian Xu, Fan Wu, Guihai Chen, Xiaoqiang Zhu, Bo Zheng
Third, to deploy MAAB in the large-scale advertising system with millions of advertisers, we propose a mean-field approach.
no code implementations • 7 Jun 2021 • Xiangyu Liu, Chuan Yu, Zhilin Zhang, Zhenzhe Zheng, Yu Rong, Hongtao Lv, Da Huo, YiQing Wang, Dagui Chen, Jian Xu, Fan Wu, Guihai Chen, Xiaoqiang Zhu
In e-commerce advertising, it is crucial to jointly consider various performance metrics, e. g., user experience, advertiser utility, and platform revenue.
no code implementations • 5 Dec 2020 • Zhilin Zhang, Xiangyu Liu, Zhenzhe Zheng, Chenrui Zhang, Miao Xu, Junwei Pan, Chuan Yu, Fan Wu, Jian Xu, Kun Gai
In e-commerce advertising, the ad platform usually relies on auction mechanisms to optimize different performance metrics, such as user experience, advertiser utility, and platform revenue.
no code implementations • 9 Aug 2018 • Zhilin Zhang
In this paper, a concept of $\alpha$-approximation distance is introduced to measure the connectivity between multi-valued objects by taking account of the distribution of the instances.
no code implementations • 21 Apr 2014 • Zhilin Zhang, Tzyy-Ping Jung, Scott Makeig, Zhouyue Pi, Bhaskar D. Rao
Particularly, the proposed algorithm ensured that the BCI classification and the drowsiness estimation had little degradation even when data were compressed by 80%, making it very suitable for continuous wireless telemonitoring of multichannel signals.
no code implementations • 15 Nov 2013 • Zhilin Zhang, Bhaskar D. Rao, Tzyy-Ping Jung
As a lossy compression framework, compressed sensing has drawn much attention in wireless telemonitoring of biosignals due to its ability to reduce energy consumption and make possible the design of low-power devices.
no code implementations • 29 Jan 2013 • Taiyong Li, Zhilin Zhang
Recently, it has been found that algorithms based on a block sparse model can achieve better recognition rates.
no code implementations • 21 Nov 2012 • Benyuan Liu, Zhilin Zhang, Hongqi Fan, Qiang Fu
One typical correlation structure is the intra-block correlation in block sparse signals.
no code implementations • 13 Jun 2012 • Zhilin Zhang, Tzyy-Ping Jung, Scott Makeig, Bhaskar D. Rao
Compressed sensing (CS), as an emerging data compression methodology, is promising in catering to these constraints.
no code implementations • 7 May 2012 • Zhilin Zhang, Tzyy-Ping Jung, Scott Makeig, Bhaskar D. Rao
The design of a telemonitoring system via a wireless body-area network with low energy consumption for ambulatory use is highly desirable.
no code implementations • 4 Jan 2012 • Zhilin Zhang, Bhaskar D. Rao
We examine the recovery of block sparse signals and extend the framework in two important directions; one by exploiting signals' intra-block correlation and the other by generalizing signals' block structure.