Kun Gai

According to our database, Kun Gai authored at least 85 papers between 2008 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Enhancing Role-playing Systems through Aggressive Queries: Evaluation and Improvement.

Yihong Tang, Jiao Ou, Che Liu, Fuzheng Zhang, Di Zhang, Kun Gai

CoRR, 2024

Video-LaVIT: Unified Video-Language Pre-training with Decoupled Visual-Motional Tokenization.

Yang Jin, Zhicheng Sun, Kun Xu, Kun Xu, Liwei Chen, Hao Jiang, Quzhe Huang, Chengru Song, Yuliang Liu, Di Zhang, Yang Song, Kun Gai, Yadong Mu

CoRR, 2024

Inverse Learning with Extremely Sparse Feedback for Recommendation.

Guanyu Lin, Chen Gao, Yu Zheng, Yinfeng Li, Jianxin Chang, Yanan Niu, Yang Song, Kun Gai, Zhiheng Li, Depeng Jin, Yong Li

Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

Mixed Attention Network for Cross-domain Sequential Recommendation.

Guanyu Lin, Chen Gao, Yu Zheng, Jianxin Chang, Yanan Niu, Yang Song, Kun Gai, Zhiheng Li, Depeng Jin, Yong Li, Meng Wang

Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

2023

Ask One More Time: Self-Agreement Improves Reasoning of Language Models in (Almost) All Scenarios.

Lei Lin, Jia-Yi Fu, Pengli Liu, Junchen Wan, Fuzheng Zhang, Zhongyuan Wang, Di Zhang, Kun Gai

CoRR, 2023

DialogBench: Evaluating LLMs as Human-like Dialogue Systems.

Jiao Ou, Junda Lu, Che Liu, Yihong Tang, Fuzheng Zhang, Di Zhang, Zhongyuan Wang, Kun Gai

CoRR, 2023

Adaptive Neural Ranking Framework: Toward Maximized Business Goal for Cascade Ranking Systems.

Yunli Wang, Zhiqiang Wang, Jian Yang, Shiyang Wen, Dongying Kong, Han Li, Kun Gai

CoRR, 2023

KwaiYiiMath: Technical Report.

Jia-Yi Fu, Lei Lin, Xiaoyang Gao, Pengli Liu, Zhengzong Chen, Zhirui Yang, Shengnan Zhang, Xue Zheng, Yan Li, Yuliang Liu, Xucheng Ye, Yiqiao Liao, Chao Liao, Bin Chen, Chengru Song, Junchen Wan, Zijia Lin, Fuzheng Zhang, Zhongyuan Wang, Di Zhang, Kun Gai

CoRR, 2023

Parrot: Enhancing Multi-Turn Chat Models by Learning to Ask Questions.

Yuchong Sun, Che Liu, Jinwen Huang, Ruihua Song, Fuzheng Zhang, Di Zhang, Zhongyuan Wang, Kun Gai

CoRR, 2023

AdaRec: Adaptive Sequential Recommendation for Reinforcing Long-term User Engagement.

Zhenghai Xue, Qingpeng Cai, Tianyou Zuo, Bin Yang, Lantao Hu, Peng Jiang, Kun Gai, Bo An

CoRR, 2023

KuaiSim: A Comprehensive Simulator for Recommender Systems.

Kesen Zhao, Shuchang Liu, Qingpeng Cai, Xiangyu Zhao, Ziru Liu, Dong Zheng, Peng Jiang, Kun Gai

CoRR, 2023

Unified Language-Vision Pretraining in LLM with Dynamic Discrete Visual Tokenization.

Yang Jin, Kun Xu, Kun Xu, Liwei Chen, Chao Liao, Jianchao Tan, Quzhe Huang, Bin Chen, Chenyi Lei, An Liu, Chengru Song, Xiaoqiang Lei, Di Zhang, Wenwu Ou, Kun Gai, Yadong Mu

CoRR, 2023

A Large Language Model Enhanced Conversational Recommender System.

Yue Feng, Shuchang Liu, Zhenghai Xue, Qingpeng Cai, Lantao Hu, Peng Jiang, Kun Gai, Fei Sun

CoRR, 2023

PANE-GNN: Unifying Positive and Negative Edges in Graph Neural Networks for Recommendation.

Ziyang Liu, Chaokun Wang, Jingcao Xu, Cheng Wu, Kai Zheng, Yang Song, Na Mou, Kun Gai

CoRR, 2023

Disentangled Causal Embedding With Contrastive Learning For Recommender System.

Weiqi Zhao, Dian Tang, Xin Chen, Dawei Lv, Daoli Ou, Biao Li, Peng Jiang, Kun Gai

Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

Divide and Conquer: Towards Better Embedding-based Retrieval for Recommender Systems from a Multi-task Perspective.

Yuan Zhang, Xue Dong, Weijie Ding, Biao Li, Peng Jiang, Kun Gai

Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

Multi-Task Recommendations with Reinforcement Learning.

Ziru Liu, Jiejie Tian, Qingpeng Cai, Xiangyu Zhao, Jingtong Gao, Shuchang Liu, Dayou Chen, Tonghao He, Dong Zheng, Peng Jiang, Kun Gai

Proceedings of the ACM Web Conference 2023, 2023

Exploration and Regularization of the Latent Action Space in Recommendation.

Shuchang Liu, Qingpeng Cai, Bowen Sun, Yuhao Wang, Ji Jiang, Dong Zheng, Peng Jiang, Kun Gai, Xiangyu Zhao, Yongfeng Zhang

Proceedings of the ACM Web Conference 2023, 2023

Two-Stage Constrained Actor-Critic for Short Video Recommendation.

Qingpeng Cai, Zhenghai Xue, Chi Zhang, Wanqi Xue, Shuchang Liu, Ruohan Zhan, Xueliang Wang, Tianyou Zuo, Wentao Xie, Dong Zheng, Peng Jiang, Kun Gai

Proceedings of the ACM Web Conference 2023, 2023

Reinforcing User Retention in a Billion Scale Short Video Recommender System.

Qingpeng Cai, Shuchang Liu, Xueliang Wang, Tianyou Zuo, Wentao Xie, Bin Yang, Dong Zheng, Peng Jiang, Kun Gai

Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

Multi-behavior Self-supervised Learning for Recommendation.

Jingcao Xu, Chaokun Wang, Cheng Wu, Yang Song, Kai Zheng, Xiaowei Wang, Changping Wang, Guorui Zhou, Kun Gai

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

When Search Meets Recommendation: Learning Disentangled Search Representation for Recommendation.

Zihua Si, Zhongxiang Sun, Xiao Zhang, Jun Xu, Xiaoxue Zang, Yang Song, Kun Gai, Ji-Rong Wen

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Understanding and Modeling Passive-Negative Feedback for Short-video Sequential Recommendation.

Yunzhu Pan, Chen Gao, Jianxin Chang, Yanan Niu, Yang Song, Kun Gai, Depeng Jin, Yong Li

Proceedings of the 17th ACM Conference on Recommender Systems, 2023

KuaiSim: A Comprehensive Simulator for Recommender Systems.

Kesen Zhao, Shuchang Liu, Qingpeng Cai, Xiangyu Zhao, Ziru Liu, Dong Zheng, Peng Jiang, Kun Gai

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

State Regularized Policy Optimization on Data with Dynamics Shift.

Zhenghai Xue, Qingpeng Cai, Shuchang Liu, Dong Zheng, Peng Jiang, Kun Gai, Bo An

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

PrefRec: Recommender Systems with Human Preferences for Reinforcing Long-term User Engagement.

Wanqi Xue, Qingpeng Cai, Zhenghai Xue, Shuo Sun, Shuchang Liu, Dong Zheng, Peng Jiang, Kun Gai, Bo An

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Graph Contrastive Learning with Generative Adversarial Network.

Cheng Wu, Chaokun Wang, Jingcao Xu, Ziyang Liu, Kai Zheng, Xiaowei Wang, Yang Song, Kun Gai

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

PEPNet: Parameter and Embedding Personalized Network for Infusing with Personalized Prior Information.

Jianxin Chang, Chenbin Zhang, Yiqun Hui, Dewei Leng, Yanan Niu, Yang Song, Kun Gai

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

TWIN: TWo-stage Interest Network for Lifelong User Behavior Modeling in CTR Prediction at Kuaishou.

Jianxin Chang, Chenbin Zhang, Zhiyi Fu, Xiaoxue Zang, Lin Guan, Jing Lu, Yiqun Hui, Dewei Leng, Yanan Niu, Yang Song, Kun Gai

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Generative Flow Network for Listwise Recommendation.

Shuchang Liu, Qingpeng Cai, Zhankui He, Bowen Sun, Julian J. McAuley, Dong Zheng, Peng Jiang, Kun Gai

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

A Multi-Agent Framework for Recommendation with Heterogeneous Sources.

Yabin Zhang, Weiqi Shao, Xu Chen, Yali Du, Xiaoxiao Xu, Dong Zheng, Changhua Pei, Shuai Zhang, Peng Jiang, Kun Gai

Proceedings of the International Joint Conference on Neural Networks, 2023

ResAct: Reinforcing Long-term Engagement in Sequential Recommendation with Residual Actor.

Wanqi Xue, Qingpeng Cai, Ruohan Zhan, Dong Zheng, Peng Jiang, Kun Gai, Bo An

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Deconfounding Duration Bias in Watch-time Prediction for Video Recommendation.

Ruohan Zhan, Changhua Pei, Qiang Su, Jianfeng Wen, Xueliang Wang, Guanyu Mu, Dong Zheng, Peng Jiang, Kun Gai

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Real-time Short Video Recommendation on Mobile Devices.

Xudong Gong, Qinlin Feng, Yuan Zhang, Jiangling Qin, Weijie Ding, Biao Li, Peng Jiang, Kun Gai

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021

Truncation-Free Matching System for Display Advertising at Alibaba.

Jin Li, Jie Liu, Shangzhou Li, Yao Xu, Ran Cao, Qi Li, Biye Jiang, Guan Wang, Han Zhu, Kun Gai, Xiaoqiang Zhu

CoRR, 2021

Optimizing Multiple Performance Metrics with Deep GSP Auctions for E-commerce Advertising.

Zhilin Zhang, Xiangyu Liu, Zhenzhe Zheng, Chenrui Zhang, Miao Xu, Junwei Pan, Chuan Yu, Fan Wu, Jian Xu, Kun Gai

Proceedings of the WSDM '21, 2021

Exploration in Online Advertising Systems with Deep Uncertainty-Aware Learning.

Chao Du, Zhifeng Gao, Shuo Yuan, Lining Gao, Ziyan Li, Yifan Zeng, Xiaoqiang Zhu, Jian Xu, Kun Gai, Kuang-Chih Lee

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

2020

Exploration in Online Advertising Systems with Deep Uncertainty-Aware Learning.

Chao Du, Yifan Zeng, Zhifeng Gao, Shuo Yuan, Lining Gao, Ziyan Li, Xiaoqiang Zhu, Jian Xu, Kun Gai

CoRR, 2020

CAN: Revisiting Feature Co-Action for Click-Through Rate Prediction.

Guorui Zhou, Weijie Bian, Kailun Wu, Lejian Ren, Qi Pi, Yujing Zhang, Can Xiao, Xiang-Rong Sheng, Na Mou, Xinchen Luo, Chi Zhang, Xianjie Qiao, Shiming Xiang, Kun Gai, Xiaoqiang Zhu, Jian Xu

CoRR, 2020

COLD: Towards the Next Generation of Pre-Ranking System.

Zhe Wang, Liqin Zhao, Biye Jiang, Guorui Zhou, Xiaoqiang Zhu, Kun Gai

CoRR, 2020

DCAF: A Dynamic Computation Allocation Framework for Online Serving System.

Biye Jiang, Pengye Zhang, Rihan Chen, Binding Dai, Xinchen Luo, Yin Yang, Guan Wang, Guorui Zhou, Xiaoqiang Zhu, Kun Gai

CoRR, 2020

A Deep Recurrent Survival Model for Unbiased Ranking.

Jiarui Jin, Yuchen Fang, Weinan Zhang, Kan Ren, Guorui Zhou, Jian Xu, Yong Yu, Jun Wang, Xiaoqiang Zhu, Kun Gai

Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

Calibrating User Response Predictions in Online Advertising.

Chao Deng, Hao Wang, Qing Tan, Jian Xu, Kun Gai

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Applied Data Science Track, 2020

Learning to Accelerate Heuristic Searching for Large-Scale Maximum Weighted b-Matching Problems in Online Advertising.

Xiaotian Hao, Junqi Jin, Jianye Hao, Jin Li, Weixun Wang, Yi Ma, Zhenzhe Zheng, Han Li, Jian Xu, Kun Gai

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Learning Optimal Tree Models under Beam Search.

Jingwei Zhuo, Ziru Xu, Wei Dai, Han Zhu, Han Li, Jian Xu, Kun Gai

Proceedings of the 37th International Conference on Machine Learning, 2020

Dynamic Knapsack Optimization Towards Efficient Multi-Channel Sequential Advertising.

Xiaotian Hao, Zhaoqing Peng, Yi Ma, Guan Wang, Junqi Jin, Jianye Hao, Shan Chen, Rongquan Bai, Mingzhou Xie, Miao Xu, Zhenzhe Zheng, Chuan Yu, Han Li, Jian Xu, Kun Gai

Proceedings of the 37th International Conference on Machine Learning, 2020

Search-based User Interest Modeling with Lifelong Sequential Behavior Data for Click-Through Rate Prediction.

Qi Pi, Guorui Zhou, Yujing Zhang, Zhe Wang, Lejian Ren, Ying Fan, Xiaoqiang Zhu, Kun Gai

Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

Learning to Infer User Hidden States for Online Sequential Advertising.

Zhaoqing Peng, Junqi Jin, Lan Luo, Yaodong Yang, Rui Luo, Jun Wang, Weinan Zhang, Haiyang Xu, Miao Xu, Chuan Yu, Tiejian Luo, Han Li, Jian Xu, Kun Gai

Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

A Deep Prediction Network for Understanding Advertiser Intent and Satisfaction.

Liyi Guo, Rui Lu, Haoqi Zhang, Junqi Jin, Zhenzhe Zheng, Fan Wu, Jin Li, Haiyang Xu, Han Li, Wenkai Lu, Jian Xu, Kun Gai

Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

Sequential Advertising Agent with Interpretable User Hidden Intents.

Zhaoqing Peng, Junqi Jin, Lan Luo, Yaodong Yang, Rui Luo, Jun Wang, Weinan Zhang, Miao Xu, Chuan Yu, Tiejian Luo, Han Li, Jian Xu, Kun Gai

Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

Progressive Feature Polishing Network for Salient Object Detection.

Bo Wang, Quan Chen, Min Zhou, Zhiqiang Zhang, Xiaogang Jin, Kun Gai

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Res-embedding for Deep Learning Based Click-Through Rate Prediction Modeling.

Guorui Zhou, Kailun Wu, Weijie Bian, Zhao Yang, Xiaoqiang Zhu, Kun Gai

CoRR, 2019

Lifelong Sequential Modeling with Personalized Memorization for User Response Prediction.

Kan Ren, Jiarui Qin, Yuchen Fang, Weinan Zhang, Lei Zheng, Weijie Bian, Guorui Zhou, Jian Xu, Yong Yu, Xiaoqiang Zhu, Kun Gai

Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2019

Joint Optimization of Tree-based Index and Deep Model for Recommender Systems.

Han Zhu, Daqing Chang, Ziru Xu, Pengye Zhang, Xiang Li, Jie He, Han Li, Jian Xu, Kun Gai

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Bid Optimization by Multivariable Control in Display Advertising.

Xun Yang, Yasong Li, Hao Wang, Di Wu, Qing Tan, Jian Xu, Kun Gai

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Practice on Long Sequential User Behavior Modeling for Click-Through Rate Prediction.

Qi Pi, Weijie Bian, Guorui Zhou, Xiaoqiang Zhu, Kun Gai

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Improve Diverse Text Generation by Self Labeling Conditional Variational Auto Encoder.

Yuchi Zhang, Yongliang Wang, Liping Zhang, Zhiqiang Zhang, Kun Gai

Proceedings of the IEEE International Conference on Acoustics, 2019

Stick to the Facts: Learning towards a Fidelity-oriented E-Commerce Product Description Generation.

Zhangming Chan, Xiuying Chen, Yongliang Wang, Juntao Li, Zhiqiang Zhang, Kun Gai, Dongyan Zhao, Rui Yan

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Learning Adaptive Display Exposure for Real-Time Advertising.

Weixun Wang, Junqi Jin, Jianye Hao, Chunjie Chen, Chuan Yu, Weinan Zhang, Jun Wang, Xiaotian Hao, Yixi Wang, Han Li, Jian Xu, Kun Gai

Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

Learning to Advertise for Organic Traffic Maximization in E-Commerce Product Feeds.

Dagui Chen, Junqi Jin, Weinan Zhang, Fei Pan, Lvyin Niu, Chuan Yu, Jun Wang, Han Li, Jian Xu, Kun Gai

Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

Deep Interest Evolution Network for Click-Through Rate Prediction.

Guorui Zhou, Na Mou, Ying Fan, Qi Pi, Weijie Bian, Chang Zhou, Xiaoqiang Zhu, Kun Gai

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

A Multi-Agent Reinforcement Learning Method for Impression Allocation in Online Display Advertising.

Di Wu, Cheng Chen, Xun Yang, Xiujun Chen, Qing Tan, Jian Xu, Kun Gai

CoRR, 2018

Learning to Advertise with Adaptive Exposure via Constrained Two-Level Reinforcement Learning.

Weixun Wang, Junqi Jin, Jianye Hao, Chunjie Chen, Chuan Yu, Weinan Zhang, Jun Wang, Yixi Wang, Han Li, Jian Xu, Kun Gai

CoRR, 2018

Budget Constrained Bidding by Model-free Reinforcement Learning in Display Advertising.

Di Wu, Xiujun Chen, Xun Yang, Hao Wang, Qing Tan, Xiaoxun Zhang, Kun Gai

CoRR, 2018

Learning Tree-based Deep Model for Recommender Systems.

Han Zhu, Pengye Zhang, Guozheng Li, Jie He, Han Li, Kun Gai

CoRR, 2018

Entire Space Multi-Task Model: An Effective Approach for Estimating Post-Click Conversion Rate.

Xiao Ma, Liqin Zhao, Guan Huang, Zhi Wang, Zelin Hu, Xiaoqiang Zhu, Kun Gai

Proceedings of the 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, 2018

Semantic Human Matting.

Quan Chen, Tiezheng Ge, Yanyu Xu, Zhiqiang Zhang, Xinxin Yang, Kun Gai

Proceedings of the 2018 ACM Multimedia Conference on Multimedia Conference, 2018

Learning Tree-based Deep Model for Recommender Systems.

Han Zhu, Xiang Li, Pengye Zhang, Guozheng Li, Jie He, Han Li, Kun Gai

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Deep Interest Network for Click-Through Rate Prediction.

Guorui Zhou, Xiaoqiang Zhu, Chengru Song, Ying Fan, Han Zhu, Xiao Ma, Yanghui Yan, Junqi Jin, Han Li, Kun Gai

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Budget Constrained Bidding by Model-free Reinforcement Learning in Display Advertising.

Di Wu, Xiujun Chen, Xun Yang, Hao Wang, Qing Tan, Xiaoxun Zhang, Jian Xu, Kun Gai

Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018

Real-Time Bidding with Multi-Agent Reinforcement Learning in Display Advertising.

Junqi Jin, Chengru Song, Han Li, Kun Gai, Jun Wang, Weinan Zhang

Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018

Image Matters: Visually Modeling User Behaviors Using Advanced Model Server.

Tiezheng Ge, Liqin Zhao, Guorui Zhou, Keyu Chen, Shuying Liu, Huiming Yi, Zelin Hu, Bochao Liu, Peng Sun, Haoyu Liu, Pengtao Yi, Sui Huang, Zhiqiang Zhang, Xiaoqiang Zhu, Yu Zhang, Kun Gai

Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018

Rocket Launching: A Universal and Efficient Framework for Training Well-Performing Light Net.

Guorui Zhou, Ying Fan, Runpeng Cui, Weijie Bian, Xiaoqiang Zhu, Kun Gai

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Image Matters: Jointly Train Advertising CTR Model with Image Representation of Ad and User Behavior.

Tiezheng Ge, Liqin Zhao, Guorui Zhou, Keyu Chen, Shuying Liu, Huiming Yi, Zelin Hu, Bochao Liu, Peng Sun, Haoyu Liu, Pengtao Yi, Sui Huang, Zhiqiang Zhang, Xiaoqiang Zhu, Yu Zhang, Kun Gai

CoRR, 2017

Deep Interest Network for Click-Through Rate Prediction.

Guorui Zhou, Chengru Song, Xiaoqiang Zhu, Xiao Ma, Yanghui Yan, Xingya Dai, Han Zhu, Junqi Jin, Han Li, Kun Gai

CoRR, 2017

Learning Piece-wise Linear Models from Large Scale Data for Ad Click Prediction.

Kun Gai, Xiaoqiang Zhu, Han Li, Kai Liu, Zhe Wang

CoRR, 2017

Optimized Cost per Click in Taobao Display Advertising.

Han Zhu, Junqi Jin, Chang Tan, Fei Pan, Yifan Zeng, Han Li, Kun Gai

Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

2013

Efficient blind separation of reflection layers with nonparametric transformations.

Han Li, Kun Gai, Pinghua Gong, Changshui Zhang

Proceedings of the IEEE International Conference on Acoustics, 2013

2012

Blind Separation of Superimposed Moving Images Using Image Statistics.

Kun Gai, Zhenwei Shi, Changshui Zhang

IEEE Trans. Pattern Anal. Mach. Intell., 2012

Efficient Superimposition Recovering Algorithm

Han Li, Kun Gai, Pinghua Gong, Changshui Zhang

CoRR, 2012

2011

Efficient Euclidean projections via Piecewise Root Finding and its application in gradient projection.

Pinghua Gong, Kun Gai, Changshui Zhang

Neurocomputing, 2011

2010

Learning Kernels with Radiuses of Minimum Enclosing Balls.

Kun Gai, Guangyun Chen, Changshui Zhang

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Learning Discriminative Piecewise Linear Models with Boundary Points.

Kun Gai, Changshui Zhang

Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010

2009

Blind separation of superimposed images with unknown motions.

Kun Gai, Zhenwei Shi, Changshui Zhang

Proceedings of the 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2009), 2009

2008

Blindly separating mixtures of multiple layers with spatial shifts.

Kun Gai, Zhenwei Shi, Changshui Zhang

Proceedings of the 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2008), 2008