no code implementations • 9 Dec 2023 • Jianghong Zhou, Weizhi Du, Md Omar Faruk Rokon, Zhaodong Wang, Jiaxuan Xu, Isha Shah, Kuang-Chih Lee, Musen Wen
The rapid proliferation of e-commerce platforms accentuates the need for advanced search and retrieval systems to foster a superior user experience.
no code implementations • 24 Oct 2023 • Jianghong Zhou, Bo Liu, Jhalak Nilesh Acharya Yao Hong, Kuang-Chih Lee, Musen Wen
In the dynamic field of eCommerce, the quality and comprehensiveness of product descriptions are pivotal for enhancing search visibility and customer engagement.
no code implementations • 18 Jun 2023 • Hangjian Li, Dong Xu, Konstantin Shmakov, Kuang-Chih Lee, Wei Shen
Online retailers often use third-party demand-side-platforms (DSPs) to conduct offsite advertising and reach shoppers across the Internet on behalf of their advertisers.
no code implementations • 11 Mar 2022 • Di wu, Cheng Chen, Xiujun Chen, Junwei Pan, Xun Yang, Qing Tan, Jian Xu, Kuang-Chih Lee
In order to address the unstable traffic pattern challenge and achieve the optimal overall outcome, we propose a multi-agent reinforcement learning method to adjust the bids from each guaranteed contract, which is simple, converging efficiently and scalable.
no code implementations • 24 Aug 2021 • Bencheng Yan, Pengjie Wang, Kai Zhang, Wei Lin, Kuang-Chih Lee, Jian Xu, Bo Zheng
Each feature value is mapped to an embedding vector via an embedding learning process.
no code implementations • 24 Aug 2021 • Bencheng Yan, Pengjie Wang, Jinquan Liu, Wei Lin, Kuang-Chih Lee, Jian Xu, Bo Zheng
In these applications, embedding learning of categorical features is crucial to the success of deep learning models.
no code implementations • 17 May 2021 • Xu Ma, Pengjie Wang, Hui Zhao, Shaoguo Liu, Chuhan Zhao, Wei Lin, Kuang-Chih Lee, Jian Xu, Bo Zheng
In real-world search, recommendation, and advertising systems, the multi-stage ranking architecture is commonly adopted.
1 code implementation • 25 Nov 2020 • Chao Du, Zhifeng Gao, Shuo Yuan, Lining Gao, Ziyan Li, Yifan Zeng, Xiaoqiang Zhu, Jian Xu, Kun Gai, Kuang-Chih Lee
In this paper, we propose a novel Deep Uncertainty-Aware Learning (DUAL) method to learn CTR models based on Gaussian processes, which can provide predictive uncertainty estimations while maintaining the flexibility of deep neural networks.
1 code implementation • 31 Dec 2018 • Yishuai Du, Yimin Zheng, Kuang-Chih Lee, Shandian Zhe
Tensor decomposition is a fundamental tool for multiway data analysis.
no code implementations • EMNLP 2018 • Changzhi Sun, Yuanbin Wu, Man Lan, Shiliang Sun, Wenting Wang, Kuang-Chih Lee, Kewen Wu
We investigate the task of joint entity relation extraction.
Ranked #1 on Relation Extraction on ACE 2005 (Sentence Encoder metric)
no code implementations • 7 Jun 2018 • Qizhi Zhang, Kuang-Chih Lee, Hongying Bao, Yuan You, Wenjie Li, Dongbai Guo
Therefore, it is infeasible to solve the multi-class classification problem using deep neural network when the number of classes are huge.
no code implementations • 11 Jul 2017 • Abraham Bagherjeiran, Nemanja Djuric, Mihajlo Grbovic, Kuang-Chih Lee, Kun Liu, Vladan Radosavljevic, Suju Rajan
Proceedings of the 2017 AdKDD and TargetAd Workshop held in conjunction with the 23rd ACM SIGKDD Conference on Knowledge Discovery and Data Mining Halifax, Nova Scotia, Canada.
no code implementations • 6 Jun 2017 • Paul Grigas, Alfonso Lobos, Zheng Wen, Kuang-Chih Lee
We develop an optimization model and corresponding algorithm for the management of a demand-side platform (DSP), whereby the DSP aims to maximize its own profit while acquiring valuable impressions for its advertiser clients.
Optimization and Control Computer Science and Game Theory
no code implementations • NeurIPS 2016 • Shandian Zhe, Kai Zhang, Pengyuan Wang, Kuang-Chih Lee, Zenglin Xu, Yuan Qi, Zoubin Ghahramani
Tensor factorization is a powerful tool to analyse multi-way data.
no code implementations • 17 Jul 2015 • Jian Xu, Xuhui Shao, Jianjie Ma, Kuang-Chih Lee, Hang Qi, Quan Lu
In this paper, we propose a new bidding strategy and prove that if the bid price is decided based on the performance lift rather than absolute performance value, advertisers can actually gain more action events.
no code implementations • 18 Jun 2015 • Jian Xu, Kuang-Chih Lee, Wentong Li, Hang Qi, Quan Lu
In this paper, we propose a smart pacing approach in which the delivery pace of each campaign is learned from both offline and online data to achieve smooth delivery and optimal performance goals.
no code implementations • 26 Jan 2015 • Sahin Cem Geyik, Ali Dasdan, Kuang-Chih Lee
In the domain of online advertising, our aim is to serve the best ad to a user who visits a certain webpage, to maximize the chance of a desired action to be performed by this user after seeing the ad.
no code implementations • 21 Nov 2014 • Can Xu, Suleyman Cetintas, Kuang-Chih Lee, Li-Jia Li
Images have become one of the most popular types of media through which users convey their emotions within online social networks.
no code implementations • 14 May 2013 • Kuang-Chih Lee, Ali Jalali, Ali Dasdan
Today, billions of display ad impressions are purchased on a daily basis through a public auction hosted by real time bidding (RTB) exchanges.