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ORCIDKuang-chih Lee
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- affiliation: Walmart Lab, CA, USA
- affiliation (former): University of California, San Diego, USA
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2020 – today
- 2024
[c44]Md Omar Faruk Rokon, Andrei Simion, Weizhi Du, Musen Wen, Hong Yao, Kuang-Chih Lee:
Enhancement of E-commerce Sponsored Search Relevancy with LLM. eCom@SIGIR 2024- [c43]Aleksandr Podkopaev, Dong Xu, Kuang-chih Lee:
Adaptive Conformal Inference by Betting. ICML 2024 - [c42]Abraham Bagherjeiran
, Nemanja Djuric, Kuang-Chih Lee, Linsey Pang, Vladan Radosavljevic, Suju Rajan:
AdKDD 2024. KDD 2024: 6706-6707 - [e3]Abraham Bagherjeiran, Nemanja Djuric, Kuang-chih Lee, Linsey Pang, Vladan Radosavljevic, Suju Rajan:
Proceedings of the Workshop on Data Mining for Online Advertising (AdKDD 2024) co-located with the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024), Barcelona, Spain, August 25, 2024. CEUR Workshop Proceedings 3837, CEUR-WS.org 2024 [contents] - 2023
- [c41]Abraham Bagherjeiran, Nemanja Djuric, Kuang-Chih Lee, Linsey Pang, Vladan Radosavljevic, Suju Rajan:
AdKDD 2023. KDD 2023: 5849-5850 - [c40]Ruiming Tang, Xiaoqiang Zhu, Junfeng Ge, Kuang-chih Lee, Biye Jiang, Xingxing Wang, Han Zhu, Tao Zhuang, Weiwen Liu, Kan Ren, Weinan Zhang, Xiangyu Zhao:
International Workshop on Deep Learning Practice for High-Dimensional Sparse Data with RecSys 2023. RecSys 2023: 1276-1280 - [e2]Abraham Bagherjeiran, Nemanja Djuric, Kuang-chih Lee, Linsey Pang, Vladan Radosavljevic, Suju Rajan:
Proceedings of the Workshop on Data Mining for Online Advertising (AdKDD 2023) co-located with the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023), Long Beach, CA, USA, August 7, 2023. CEUR Workshop Proceedings 3556, CEUR-WS.org 2023 [contents] - [i18]Hangjian Li, Dong Xu, Konstantin Shmakov, Kuang-Chih Lee, Wei Shen:
Bid Optimization for Offsite Display Ad Campaigns on eCommerce. CoRR abs/2306.10476 (2023) - [i17]Jianghong Zhou, Bo Liu, Jhalak Nilesh Acharya Yao Hong, Kuang-chih Lee, Musen Wen:
Leveraging Large Language Models for Enhanced Product Descriptions in eCommerce. CoRR abs/2310.18357 (2023) - [i16]Jianghong Zhou, Weizhi Du, Md Omar Faruk Rokon, Zhaodong Wang, Jiaxuan Xu, Isha Shah, Kuang-chih Lee, Musen Wen:
Enhanced E-Commerce Attribute Extraction: Innovating with Decorative Relation Correction and LLAMA 2.0-Based Annotation. CoRR abs/2312.06684 (2023) - 2022
- [c39]Abraham Bagherjeiran, Nemanja Djuric, Mihajlo Grbovic, Kuang-Chih Lee, Kun Liu, Wei Liu, Linsey Pang, Vladan Radosavljevic, Suju Rajan, Kexin Xie:
AdKDD 2022. KDD 2022: 4852-4853 - [c38]Roberto Corizzo, Junfeng Ge, Colin Bellinger, Xiaoqiang Zhu, Paula Branco, Kuang-chih Lee, Nathalie Japkowicz, Ruiming Tang, Tao Zhuang, Han Zhu, Biye Jiang, Jiaxin Mao, Weinan Zhang:
4th Workshop on Deep Learning Practice and Theory for High-Dimensional Sparse and Imbalanced Data with KDD 2022. KDD 2022: 4860-4861 - [i15]Di Wu, Cheng Chen, Xiujun Chen, Junwei Pan, Xun Yang, Qing Tan, Jian Xu, Kuang-Chih Lee:
Impression Allocation and Policy Search in Display Advertising. CoRR abs/2203.07073 (2022) - 2021
- [c37]Penghui Wei, Weimin Zhang, Zixuan Xu, Shaoguo Liu, Kuang-chih Lee, Bo Zheng:
AutoHERI: Automated Hierarchical Representation Integration for Post-Click Conversion Rate Estimation. CIKM 2021: 3528-3532 - [c36]Bencheng Yan, Pengjie Wang, Jinquan Liu, Wei Lin, Kuang-Chih Lee, Jian Xu, Bo Zheng:
Binary Code based Hash Embedding for Web-scale Applications. CIKM 2021: 3563-3567 - [c35]Bencheng Yan, Pengjie Wang, Kai Zhang, Wei Lin, Kuang-Chih Lee, Jian Xu, Bo Zheng:
Learning Effective and Efficient Embedding via an Adaptively-Masked Twins-based Layer. CIKM 2021: 3568-3572 - [c34]Di Wu, Cheng Chen, Xiujun Chen, Junwei Pan, Xun Yang, Qing Tan, Jian Xu, Kuang-Chih Lee:
Impression Allocation and Policy Search in Display Advertising. ICDM 2021: 749-756 - [c33]Chao Du, Zhifeng Gao, Shuo Yuan, Lining Gao, Ziyan Li, Yifan Zeng, Xiaoqiang Zhu, Jian Xu, Kun Gai, Kuang-Chih Lee:
Exploration in Online Advertising Systems with Deep Uncertainty-Aware Learning. KDD 2021: 2792-2801 - [c32]Abraham Bagherjeiran, Nemanja Djuric, Mihajlo Grbovic, Kuang-chih Lee, Kun Liu, Vladan Radosavljevic, Suju Rajan:
AdKDD 2021. KDD 2021: 4106-4107 - [c31]Xiaoqiang Zhu, Kuang-chih Lee, Guorui Zhou, Biye Jiang, Zhe Wang, Ruiming Tang, Kan Ren, Qingyao Ai, Weinan Zhang:
3rd International Workshop on Deep Learning Practice for High-Dimensional Sparse Data with KDD 2021. KDD 2021: 4187-4188 - [c30]Xu Ma, Pengjie Wang, Hui Zhao, Shaoguo Liu, Chuhan Zhao, Wei Lin, Kuang-Chih Lee, Jian Xu, Bo Zheng:
Towards a Better Tradeoff between Effectiveness and Efficiency in Pre-Ranking: A Learnable Feature Selection based Approach. SIGIR 2021: 2036-2040 - [i14]Xu Ma, Pengjie Wang, Hui Zhao, Shaoguo Liu, Chuhan Zhao, Wei Lin, Kuang-Chih Lee, Jian Xu, Bo Zheng:
Towards a Better Tradeoff between Effectiveness and Efficiency in Pre-Ranking: A Learnable Feature Selection based Approach. CoRR abs/2105.07706 (2021) - [i13]Bencheng Yan, Pengjie Wang, Kai Zhang, Wei Lin, Kuang-Chih Lee, Jian Xu, Bo Zheng:
Learning Effective and Efficient Embedding via an Adaptively-Masked Twins-based Layer. CoRR abs/2108.11513 (2021) - [i12]Bencheng Yan, Pengjie Wang, Jinquan Liu, Wei Lin, Kuang-Chih Lee, Jian Xu, Bo Zheng:
Binary Code based Hash Embedding for Web-scale Applications. CoRR abs/2109.02471 (2021) - 2020
- [j3]Donghyuk Shin, Shu He, Gene Moo Lee, Andrew B. Whinston, Suleyman Cetintas, Kuang-Chih Lee:
Enhancing Social Media Analysis with Visual Data Analytics: A Deep Learning Approach. MIS Q. 44(4) (2020) - [c29]Shikai Fang, Shandian Zhe, Kuang-chih Lee, Kai Zhang, Jennifer Neville:
Online Bayesian Sparse Learning with Spike and Slab Priors. ICDM 2020: 142-151
2010 – 2019
- 2019
- [c28]Chao Wei, Weiru Zhang, Shengjie Sun, Fei Li, Xiaonan Meng, Yi Hu, Kuang-chih Lee, Hao Wang:
Optimal Delivery with Budget Constraint in E-Commerce Advertising. ORSUM@RecSys 2019: 46-58 - 2018
- [c27]Changzhi Sun, Yuanbin Wu, Man Lan, Shiliang Sun, Wenting Wang, Kuang-Chih Lee, Kewen Wu:
Extracting Entities and Relations with Joint Minimum Risk Training. EMNLP 2018: 2256-2265 - [c26]Yishuai Du, Yimin Zheng, Kuang-chih Lee, Shandian Zhe:
Probabilistic Streaming Tensor Decomposition. ICDM 2018: 99-108 - [c25]Qizhi Zhang, Kuang-Chih Lee, Hongying Bao, Yuan You, Wenjie Li, Dongbai Guo:
Large Scale Classification in Deep Neural Network with Label Mapping. ICDM Workshops 2018: 1134-1143 - [i11]Qizhi Zhang, Kuang-chih Lee, Hongying Bao, Yuan You, Dongbai Guo:
Category coding with neural network application. CoRR abs/1805.07927 (2018) - [i10]Qizhi Zhang, Kuang-Chih Lee, Hongying Bao, Yuan You, Wenjie Li, Dongbai Guo:
Large scale classification in deep neural network with Label Mapping. CoRR abs/1806.02507 (2018) - 2017
- [c24]Zhihui Xie, Kuang-Chih Lee, Liang Wang:
Optimal Reserve Price for Online Ads Trading Based on Inventory Identification. ADKDD@KDD 2017: 6:1-6:7 - [c23]Paul Grigas, Alfonso Lobos, Zheng Wen, Kuang-chih Lee:
Profit Maximization for Online Advertising Demand-Side Platforms. ADKDD@KDD 2017: 11:1-11:7 - [i9]Paul Grigas, Alfonso Lobos, Zheng Wen, Kuang-chih Lee:
Profit Maximization for Online Advertising Demand-Side Platforms. CoRR abs/1706.01614 (2017) - [i8]Abraham Bagherjeiran, Nemanja Djuric, Mihajlo Grbovic, Kuang-Chih Lee, Kun Liu, Vladan Radosavljevic, Suju Rajan:
Proceedings of the 2017 AdKDD & TargetAd Workshop. CoRR abs/1707.03471 (2017) - [i7]Zhihui Xie, Kuang-Chih Lee, Liang Wang:
Optimal Reserve Price for Online Ads Trading Based on Inventory Identification. CoRR abs/1709.10388 (2017) - 2016
- [c22]Jian Xu, Xuhui Shao, Jianjie Ma, Kuang-chih Lee, Hang Qi, Quan Lu:
Lift-Based Bidding in Ad Selection. AAAI 2016: 651-657 - [c21]Liang Wang, Kuang-chih Lee, Quan Lu:
Improving Advertisement Recommendation by Enriching User Browser Cookie Attributes. CIKM 2016: 2401-2404 - [c20]Miguel Angel Alcobendas Lisbona, Sheide Chammas, Kuang-chih Lee:
Optimal Reserve Prices in Upstream Auctions: Empirical Application on Online Video Advertising. KDD 2016: 1395-1404 - [c19]Shandian Zhe, Kai Zhang, Pengyuan Wang, Kuang-chih Lee, Zenglin Xu, Yuan Qi, Zoubin Ghahramani:
Distributed Flexible Nonlinear Tensor Factorization. NIPS 2016: 920-928 - [i6]Shandian Zhe, Pengyuan Wang, Kuang-chih Lee, Zenglin Xu, Jian Yang, Youngja Park, Yuan Qi:
Distributed Flexible Nonlinear Tensor Factorization. CoRR abs/1604.07928 (2016) - 2015
- [c18]Donghyuk Shin, Suleyman Cetintas, Kuang-Chih Lee, Inderjit S. Dhillon:
Tumblr Blog Recommendation with Boosted Inductive Matrix Completion. CIKM 2015: 203-212 - [c17]Jian Xu, Kuang-chih Lee, Wentong Li, Hang Qi, Quan Lu:
Smart Pacing for Effective Online Ad Campaign Optimization. KDD 2015: 2217-2226 - [i5]Sahin Cem Geyik, Ali Dasdan, Kuang-Chih Lee:
User Clustering in Online Advertising via Topic Models. CoRR abs/1501.06595 (2015) - [i4]Jian Xu, Kuang-chih Lee, Wentong Li, Hang Qi, Quan Lu:
Smart Pacing for Effective Online Ad Campaign Optimization. CoRR abs/1506.05851 (2015) - [i3]Jian Xu, Xuhui Shao, Jianjie Ma, Kuang-chih Lee, Hang Qi, Quan Lu:
Lift-Based Bidding in Ad Selection. CoRR abs/1507.04811 (2015) - 2014
- [c16]Donghyuk Shin, Suleyman Cetintas, Kuang-Chih Lee:
Recommending Tumblr Blogs to Follow with Inductive Matrix Completion. RecSys Posters 2014 - [e1]Esin Saka, Dou Shen, Kuang-chih Lee, Ying Li:
Proceedings of the Eighth International Workshop on Data Mining for Online Advertising, ADKDD 2014, August 24, 2014, New York City, New York, USA. ACM 2014, ISBN 978-1-4503-2999-6 [contents] - [i2]Can Xu, Suleyman Cetintas, Kuang-Chih Lee, Li-Jia Li:
Visual Sentiment Prediction with Deep Convolutional Neural Networks. CoRR abs/1411.5731 (2014) - 2013
- [c15]Kuang-Chih Lee, Ali Jalali, Ali Dasdan:
Real time bid optimization with smooth budget delivery in online advertising. AdKDD@KDD 2013: 1:1-1:9 - [i1]Kuang-Chih Lee, Ali Jalali, Ali Dasdan:
Real Time Bid Optimization with Smooth Budget Delivery in Online Advertising. CoRR abs/1305.3011 (2013) - 2012
- [c14]Kuang-chih Lee, Burkay Orten, Ali Dasdan, Wentong Li:
Estimating conversion rate in display advertising from past erformance data. KDD 2012: 768-776
2000 – 2009
- 2008
- [c13]Victor Erukhimov, Kuang-chih Lee:
A bottom-up framework for robust facial feature detection. FG 2008: 1-6 - [c12]Kuang-chih Lee, Dragomir Anguelov, Baris Sumengen, Salih Burak Göktürk:
Markov random field models for hair and face segmentation. FG 2008: 1-6 - 2007
- [c11]Dragomir Anguelov, Kuang-chih Lee, Salih Burak Göktürk, Baris Sumengen:
Contextual Identity Recognition in Personal Photo Albums. CVPR 2007 - 2006
- [c10]Lorenzo Torresani, Kuang-chih Lee:
Large Margin Component Analysis. NIPS 2006: 1385-1392 - 2005
- [b1]Kuang-Chih Lee:
Representing the Appearances of Human Faces for Recognition. University of Illinois Urbana-Champaign, USA, 2005 - [j2]Kuang-Chih Lee, Jeffrey Ho, Ming-Hsuan Yang, David J. Kriegman:
Visual tracking and recognition using probabilistic appearance manifolds. Comput. Vis. Image Underst. 99(3): 303-331 (2005) - [j1]Kuang-Chih Lee, Jeffrey Ho, David J. Kriegman:
Acquiring Linear Subspaces for Face Recognition under Variable Lighting. IEEE Trans. Pattern Anal. Mach. Intell. 27(5): 684-698 (2005) - [c9]Kuang-Chih Lee, Baback Moghaddam:
A Practical Face Relighting Method for Directional Lighting Normalization. AMFG 2005: 155-169 - [c8]Kuang-Chih Lee, David J. Kriegman:
Online Learning of Probabilistic Appearance Manifolds for Video-Based Recognition and Tracking. CVPR (1) 2005: 852-859 - [c7]Huei-Ju Chen, Kuang-Chih Lee, Erik Murphy-Chutorian, Jochen Triesch:
Toward a Unified Probabilistic Framework for Object Recognition and Segmentation. ISVC 2005: 108-117 - 2004
- [c6]Jeffrey Ho, Kuang-Chih Lee, Ming-Hsuan Yang, David J. Kriegman:
Visual Tracking Using Learned Linear Subspaces. CVPR (1) 2004: 782-789 - [c5]Jongwoo Lim, Jeffrey Ho, Ming-Hsuan Yang, Kuang-Chih Lee, David J. Kriegman:
Image Clustering with Metric, Local Linear Structure, and Affine Symmetry. ECCV (1) 2004: 456-468 - 2003
- [c4]Jeffrey Ho, Ming-Hsuan Yang, Jongwoo Lim, Kuang-Chih Lee, David J. Kriegman:
Clustering Appearances of Objects Under Varying Illumination Conditions. CVPR (1) 2003: 11-18 - [c3]Kuang-Chih Lee, Jeffrey Ho, Ming-Hsuan Yang, David J. Kriegman:
Video-Based Face Recognition Using Probabilistic Appearance Manifolds. CVPR (1) 2003: 313-320 - 2001
- [c2]Kuang-Chih Lee, Jeffrey Ho, David J. Kriegman:
Nine Points of Light: Acquiring Subspaces for Face Recognition under Variable Lighting. CVPR (1) 2001: 519-526 - [c1]Jeffrey Ho, Kuang-Chih Lee, David J. Kriegman:
Compressing Large Polygonal Models. IEEE Visualization 2001: 357-362
Coauthor Index
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