Search Results for author: Kuang-Chih Lee

Found 19 papers, 2 papers with code

Leveraging Large Language Models for Enhanced Product Descriptions in eCommerce

no code implementations24 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.

Language Modelling

Bid Optimization for Offsite Display Ad Campaigns on eCommerce

no code implementations18 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.

Impression Allocation and Policy Search in Display Advertising

no code implementations11 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.

Multi-agent Reinforcement Learning

Binary Code based Hash Embedding for Web-scale Applications

no code implementations24 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.

Recommendation Systems

Exploration in Online Advertising Systems with Deep Uncertainty-Aware Learning

1 code implementation25 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.

Click-Through Rate Prediction Gaussian Processes

Large scale classification in deep neural network with Label Mapping

no code implementations7 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.

BIG-bench Machine Learning Classification +2

Proceedings of the 2017 AdKDD & TargetAd Workshop

no code implementations11 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.

Profit Maximization for Online Advertising Demand-Side Platforms

no code implementations6 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

Lift-Based Bidding in Ad Selection

no code implementations17 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.

Smart Pacing for Effective Online Ad Campaign Optimization

no code implementations18 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.

User Clustering in Online Advertising via Topic Models

no code implementations26 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.

Clustering Topic Models +1

Visual Sentiment Prediction with Deep Convolutional Neural Networks

no code implementations21 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.

Object Recognition Sentiment Analysis +2

Real Time Bid Optimization with Smooth Budget Delivery in Online Advertising

no code implementations14 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.

Cannot find the paper you are looking for? You can Submit a new open access paper.