研究方向
  • 下一代多场景多模态异构计算引擎

融合与统一批处理、交互式处理和流处理等多种计算模态,研究近似查询、渐进式执行等新技术,支持传统数据分析、图计算、机器学习等各种应用场景和计算需求下一代计算引擎。同时在计算引擎中研究利用GPU、FPGA、ASIC等异构硬件高效率和低延迟的计算性能,将异构硬件的计算能力与传统通用计算整合,更好地满足人工智能、高性能数据分析等计算密集型领域的计算需求。

  • 大规模多样性数据挖掘和机器学习算法及应用

研究在大规模多样性数据(如结构化数据、图数据、信息网络等)上的高效数据挖掘算法和机器学习算法,探索和融合大规模图表征学习、知识图谱等新技术,应用于在线反作弊、推荐系统、和提高搜索效能等场景,服务普惠到社会生活中。

  • 智能与自治化系统

将系统技术与人工智能技术相结合,利用人工智能技术在数据仓库管理、资源调度、引擎优化等各个方面的优势加强与改进系统;同时使用系统技术辅助人工智能中的模型选择、元参数搜索等工作,进行自动的元学习,从而帮助系统变得更加智能,更加安全可靠。

  • 数据安全和隐私保护

研究如何在数据采集、数据共享和数据呈现等多个可能泄露个人敏感信息的数据处理阶段有效保障数据安全和用户隐私,同时降低数据损耗并提供高效的数据分析能力。

  • 超大规模图计算

研究以深度学习和图计算结合的大规模图表征学习为代表的机器学习算法和基于图的知识图谱技术,研发新型架构的超大规模图计算引擎和超大规模知识图谱推理系统。在信息检索、分布式计算、大规模系统设计、机器学习、人工智能、自然语言处理等相关领域做出突破贡献。


产品及应用
  • 超大规模图推理引擎

    图形推理与深度学习相结合,在阿里巴巴的许多业务场景中取得了成功的分阶段结果。例如,个性化推荐系统是信息过滤的重要手段,可以根据习惯和爱好推荐合适的产品或服务。传统的推荐系统存在稀疏性、冷启动和信息可重复性的问题,而大规模图表示可以有效地利用自然人的全球信息。我们正在开发新一代图形学习平台,可以有效地对数十亿个节点和数万亿个边缘进行推理分析。

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  • 电子商务反作弊解决方案

    反作弊大致分成渠道设备反作弊和流量反作弊。渠道设备反作弊的主要任务是识别可疑的模拟器、设备牧场等。我们从各种日志提取设备的各类稀疏和稠密特征,并对Google的Wide&Deep模型基于相关业务场景进行了有效的改造,每日可识别千万级高可信的作弊设备。流量的反作弊更多的是和业务场景强相关。通过进行全局的考虑和建模,聚合可疑流量,在同一个cluster内进行信息的增强和互借,进而提高模型的可信度。我们基于业务的需求和定义提出一系列图模型,每日可在全量流量日志中抓取数百万高可信的作弊cookie。此项成果也被《中国计算机学会通讯》和人工智能顶会IJCAI收录报道。

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研究团队
周靖人达摩院智能计算实验室负责人

哥伦比亚大学计算机博士,IEEE Fellow。拥有几十篇顶级会议和期刊论文,并持有多项专利发明。研究领域包括基于大规模分布式系统的数据计算处理方法和机器学习算法平台。曾任微软研究院研究员、微软研发合伙人。

丁博麟达摩院智能计算实验室资深技术专家

伊利诺伊大学香槟分校博士。研究成果发表于SIGMOD等多个领域的顶尖国际会议,常年担任重要国际会议评审委员会评委。研究领域包括大规模数据的管理和分析等。曾担任美国微软研究院研究员。

钱正平达摩院智能计算实验室资深技术专家

华南理工大学博士。在系统及相关领域顶级会议发表多篇论文,并曾获EuroSys’12最佳论文奖。研究领域是分布式系统与数据并行计算。曾任微软亚洲研究院主管研究员。

杨红霞达摩院智能计算实验室资深算法专家

杜克大学博士。拥有顶级论文30余篇。曾任IBM Watson研究员、Yahoo!主任数据科学家等职。目前致力于研发新一代结合超大规模知识图谱和图计算的推理系统。

曾凯达摩院智能计算实验室高级技术专家

加州大学洛杉矶分校博士,曾在美国加州大学伯克利分校AMP Lab从事博士后研究。拥有顶级论文20余篇,获SIGMOD 2012年最佳论文奖等。研究领域包括大规模分布式系统和数据库系统。曾任微软资深科学家。

于文渊达摩院智能计算实验室资深技术专家

爱丁堡大学博士。研究成果发表于SIGMOD等多个领域的顶尖国际会议,曾获SIGMOD2017和VLDB2010最佳论文奖,VLDB2017最佳演示奖。研究领域包括数据质量管理、图数据管理与计算等。曾担任七桥科技CEO、美国Facebook 研究科学家等。


学术成果
论文
  • Zuozhi Wang, Kai Zeng, Botong Huang, Wei Chen, Xiaozong Cui, Bo Wang, Ji Liu, Liya Fan, Dachuan Qu, Zhenyu Hou, Tao Guan, Chen Li, Jingren Zhou. Beanstalk: A General Cost-Based Optimizer Framework for Incremental Data Processing. VLDB 2021.
  • Tianhao Wang, Bolin Ding, Min Xu, Zhicong Huang, Cheng Hong, Jingren Zhou, Ninghui Li, and Somesh Jha. Improving Utility and Security of the Shuffler-based Differential Privacy. VLDB 2021.
  • Yang, H. and Zhou, J., The Study of Cognitive Graph and its Practice in E-Commerce, Communications for China Computer Federation. CCCF 2020.
  • Ji, Yu., Yin, M., Yang, H., Zhou, J., Zheng, V., Shi, C. and Fang, Y. Accelerating Large-Scale Heterogeneous Interaction Graph Embedding Learning via Importance Sampling, ACM Transactions on Knowledge Discovery from Data. TKDD 2020.
  • Wenfei Fan, Ping Lu, Chao Tian. Unifying logic rules and machine learning for entity enhancing. SCIC 2020.
  • Wenfei Fan, Xueli Liu, Ping Lu, Chao Tian. Catching Numeric Inconsistencies in Graphs. TODS 2020.
  • Yuan Zhang, Fei Sun, Xiaoyong Yang, Chen Xu, Wenwu Ou and Yan Zhang. 2020. Graph-based Regularization on Embedding Layers for Recommendation. ACM Transactions on Information Systems. TOIS 2020.
  • Wenfei Fan, Ping Lu, Wenyuan Yu, Jingbo Xu, Qiang Yin, Xiaojian Luo, Jingren Zhou, and Ruochun Jin. 2020. Adaptive Asynchronous Parallelization of Graph Algorithms. ACM Transactions on Database Systems. TODS 2020.
  • Yongxin Tong, Yuxiang Zeng, Bolin Ding, Libin Wang, and Lei Chen. Two-Sided Online Micro-Task Assignment in Spatial Crowdsourcing. IEEE Transactions on Knowledge and Data Engineering. TKDE 2020.
  • Ding, M., Zhou, C., Yang, H. and Tang, J., CogLTX: Applying BERT to Long Texts. Neural Information Processing Systems. NeurIPS 2020.
  • Zou, H., Cui, P., Ma, J. and Yang, H., Counterfactual Prediction for Bundle Treatment. Neural Information Processing Systems. NeurIPS 2020.
  • Zhiqiang Tao, Yaliang Li, Bolin Ding, Ce Zhang, Jingren Zhou, Yun Fu. Learning to Mutate with Hypergradient Guided Population. Neural Information Processing Systems. NeurIPS 2020.
  • Ming Chen, Zhewei Wei, Bolin Ding, Yaliang Li, Ye Yuan, Xiaoyong Du, Ji-Rong Wen. Scalable Graph Neural Networks via Bidirectional Propagation. Neural Information Processing Systems. NeurIPS 2020.
  • Yufei Feng, Fuyu Lv, Binbin Hu, Fei Sun, Kun Kuang, Yang Liu, Qingwen Liu, Wenwu Ou. MTBRN: Multiplex Target-Behavior Relation Enhanced Network for Click-Through Rate Prediction. International Conference on Information and Knowledge Management. CIKM 2020.
  • Daoyuan Chen, Yaliang Li, Bolin Ding, and Ying Shen. An Adaptive Embedding Framework for Heterogeneous Information Networks. International Conference on Information and Knowledge Management. CIKM 2020.
  • Ji, Y., Yin, M., Fang, Y., Yang, H., Wang, X. and Shi, C., Temporal Heterogeneous Interaction Graph Embedding For Next-Item Recommendation. ECML-PKDD 2020.
  • Wang, Y., Pan, G., Yao, Y., Tong, H., Yang, H., Xu, F. and Lu, J., Bringing Order to Network Embedding: A Relative Ranking based Approach. 29th ACM International Conference on Information and Knowledge Management. CIKM 2020.
  • Zhang, S., Tan, Z., Yu, J., Zhao, Z., Kuang, K., Zhou, J., Yang, H. and Wu, F., Poet: Product-oriented Video Captioner for E-commerce. 28th ACM International Conference on Multimedia. MM 2020.
  • Zhang, S., Jiang, T., Wang, T., Kuang, K, Yu, J., Yang, H. and Wu, F., DeVLBert: Learning Deconfounded Visio-Linguistic Representations. 28th ACM International Conference on Multimedia. MM 2020.
  • Chu, Y., Wang, X., Ma, J., Jia, K., Zhou, J. and Yang, H., Inductive Granger Causal Modeling for Multivariate Time Series. IEEE International Conference on Data Mining series. ICDM 2020.
  • Wenfei Fan, Ruochun Jin, Muyang Liu, Ping Lu, Chao Tian, Jingren Zhou. Capturing Associations in Graphs. VLDB 2020.
  • Wenfei Fan, Muyang Liu, Chao Tian, Ruiqi Xu, Jingren Zhou. Incrementalization of Graph Partitioning Algorithms. VLDB 2020.
  • Xiaowei Jiang, Yuejun Hu, Yu Xiang, Guangran Jiang, Xiaojun Jin, Chen Xia, Weihua Jiang, Jun Yu, Haitao Wang, Yuan Jiang, Jihong Ma, Li Su, Kai Zeng. Alibaba Hologres: A Cloud-Native Service for Hybrid Serving/Analytical Processing. VLDB 2020.
  • Min Xu, Bolin Ding, Tianhao Wang, and Jingren Zhou. Collecting and Analyzing Data Jointly from Multiple Services under Local Differential Privacy. VLDB 2020.
  • Zuozhi Wang, Kai Zeng, Botong Huang, Wei Chen, Xiaozong Cui, Bo Wang, Ji Liu, Liya Fan, Dachuan Qu, Zhenyu Ho, Tao Guan, Chen Li, Jingren Zhou. Grosbeak: A Data Warehouse Supporting Resource-Aware Incremental Computing. SIGMOD 2020.
  • Ming Chen, Zhewei Wei, Zengfeng Huang, Bolin Ding, and Yaliang Li. Simple and Deep Graph Convolutional Networks. ICML 2020.
  • Haoji Hu, Jinyang Gao and Xiangnan He, Modeling Personalized Item Frequency Information for Next-basket Recommendation. SIGIR 2020.
  • Ruiyang Ren, Zhaoyang Liu, Yaliang Li, Xin Zhao, Hui Wang, Bolin Ding and Jirong Wen, Sequential Recommendation with Self-Attentive Multi-Adversarial Network. SIGIR 2020.
  • Chen Xu, Quan Li, Junfeng Ge, Jinyang Gao, Xiaoyong Yang, Changhua Pei, Fei Sun, Jian Wu, Hanxiao Sun, and Wenwu Ou: Privileged Features Distillation at Taobao Recommendations. KDD 2020.
  • Bingqing Lyu, Lu Qin, Xuemin Lin, Ying Zhang, Zhengping Qian, Jingren Zhou: Maximum Biclique Search at Billion Scale. VLDB 2020.
  • Daoyuan Chen, Yaliang Li, Minghui Qiu, Zhen Wang, Bofang Li, Bolin Ding, Hongbo Deng, Jun Huang, Wei Lin, and Jingren Zhou. AdaBERT: Task-Adaptive BERT Compression with Differentiable Neural Architecture Search. IJCAI 2020.
  • Zhaoyang Liu, Haokun Chen, Fei Sun, Xu Xie, Jinyang Gao, Bolin Ding, and Yanyan Shen. Intent Preference Decoupling for User Representation on Online Recommender System. IJCAI 2020.
  • Ya Zhao,Rui Xu,Xinchao Wang, Peng Hou , Haihong Tang ,Mingli Song. Hearing Lips: Improving Lip Reading by Distilling Speech Recognizers. AAAI 2020.
  • Ruiyang Ren, Zhaoyang Liu, Yaliang Li, Wayne Xin Zhao, Hui Wang, Bolin Ding, and Ji-Rong Wen. Sequential Recommendation with Self-attentive Multi-adversarial Network. SIGIR 2020.
  • Zhuolun Xiang, Bolin Ding, Xi He, and Jingren Zhou. Linear and Range Counting under Metric-based Local Differential Privacy. ISIT 2020.
  • Yaliang Li, Houping Xiao, Zhan Qin, Chenglin Miao, Lu Su, Jing Gao, Kui Ren, and Bolin Ding. Towards Differentially Private Truth Discovery for Crowd Sensing Systems. ICDCS 2020.
  • Hengtong Zhang, Yaliang Li, Bolin Ding, and Jing Gao. Practical Data Poisoning Attack Against Next-Item Recommendation. WWW 2020.
  • Huaxiu Yao, Xian Wu, Zhiqiang Tao, Yaliang Li, Bolin Ding, Ruirui Li, and Zhenhui Li. Automated Relational Meta-learning. ICLR 2020.
  • Chenwei Zhang, Yaliang Li, Nan Du, Wei Fan, and Philip S. Yu. Entity Synonyms Discovery via Multipiece Bilateral Context Matching. IJCAI 2020.
  • Daoyuan Chen, Yaliang Li, Kai Lei, and Ying Shen. Relabel the Noise: Joint Extraction of Entities and Relations via Cooperative Multiagents. ACL 2020.
  • Yuexiang Xie, Ying Shen, Yaliang Li, Min Yang, and Kai Lei. Attentive User-Engaged Adversarial Neural Network for Community Question Answering. AAAI 2020.
  • Shiwen Wu, Xu Xie, Jinyang Gao, Bin Cui. Enhanced Review-based Rating Prediction by Exploiting Aside Information and User Influence. AAAI 2020.
  • Yang Li, Jinyang Gao, Jiawei Jiang, Yingxia Shao, Bin Cui. Efficient Automatic CASH via Rising Bandits. AAAI 2020.
  • Xiaotian Hao, Junqi Jin, Jin Li, Weixun Wang, Yi Ma, Jianye Hao, Zhenzhe Zheng, Han Li, Jian Xu, Kun Gai. Learning to Accelerate Heuristic Searching for Large-Scale Maximum Weighted b-Matching Problems in Online Advertising. IJCAI 2020.
  • 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. Sequential Advertising Agent with Interpretable User Hidden Intents. AAMAS 2020.
  • Wenfei Fan, Ruochun Jin, Muyang Liu, Ping Lu, Xiaojian Luo, Ruiqi Xu, Qiang Yin, Wenyuan Yu and Jingren Zhou. Application Driven Graph Partitioning. SIGMOD 2020.
  • Shengyu Zhang, Ziqi Tan, Jin Yu, Zhou Zhao, Kun Kuang, Hongxia Yang, Fei Wu and Jingren Zhou: Comprehensive Information Integration Modeling Framework for Video Titling. KDD 2020.
  • Jianxin Ma, Chang Zhou, Hongxia Yang, Cui Peng, Xin Wang and Wenwu Zhu: Disentangled Self-Supervision in Sequential Recommenders. KDD 2020.
  • Yukuo Cen, Jianwei Zhang, Xu Zou, Chang Zhou, Hongxia Yang and Jie Tang: Controllable Multi-Interest Framework for Recommendation. KDD 2020.
  • Jiezhong Qiu, Qibin Chen, Hongxia Yang, Ming Ding, Kuansan Wang and Jie Tang: Graph Contrastive Coding for Structural Graph Representation Pre-Training. KDD 2020.
  • Zhen Yang, Ming Ding, Chang Zhou, Hongxia Yang, Jingren Zhou and Jie Tang: Understanding Negative Sampling in Graph Representation Learning. KDD 2020.
  • Yue He, Peng Cui, Jianxin Ma, Zou Hao, Xiaowei Wang, Hongxia Yang and Philip S. Yu: Learning Stable Graphs from Heterogeneous Confounded Environments. KDD 2020.
  • Qiaoyu Tan, Ninghao Liu, Hongxia Yang, Jingren Zhou and Xia Hu: Learning to Hash with Graph Neural Networks for Recommender Systems. WWW 2020.
  • Zhuoren Jiang, Zheng Gao, Jinjiong Lan, Hongxia Yang, Yao Lu and Xiaozhong Liu: Task-Oriented Genetic Activation for Large-Scale Complex Heterogeneous Graph Embedding. WWW 2020.
  • Zhen Zhang, Jiajun Bu, Martin Ester, Jianfeng Zhang, Chengwei Yao, Zhao Li and Can Wang. Learning Temporal Interaction Graph Embedding via Coupled Memory Networks. WWW 2020.
  • Hongrui Zhao, Jin Yu, Donghui Wang, Jie Liu, Hongxia Yang and Fei Wu: Dress like an Internet Celebrity: Fashion Retrieval in Videos. IJCAI 2020.
  • Wentao Huang, Yuchen Li, Yuan Fang and Hongxia Yang: BiANE: Bipartite Attributed Network Embedding. SIGIR 2020.
  • Di Yin, Jiwei Tan, Zhe Zhang, Hongbo Deng, Shujian Huang and Jiajun Chen, Learning to Generate Personalized Query Auto-Completions via a Multi-View Multi-Task Attentive Approach. KDD 2020.
  • Peng Zhang, Kefeng Ning, Wenxiang Zhu, Yu Zhang, Chuanren Liu: Prediction and Profiling of Audience Competition for Online Television Series. KDD 2020.
  • Jiarui Jin, Yuchen Fang, Weinan Zhang, Kan Ren, Guorui Zhou, Jian Xu, Yong Yu, Jun Wang, Xiaoqiang Zhu, Kun Gai. A Deep Recurrent Survival Model for Unbiased Ranking. SIGIR 2020.
  • Hongrui Zhao, Jin Yu, Donghui Wang, Jie Liu, Hongxia Yang and Fei Wu: Dress like an Internet Celebrity: Fashion Retrieval in Videos. IJCAI 2020.
  • Cheng Zhao, Chenliang Li, Rong Xiao, Hongbo Deng and Aixin Sun. CATN: Cross-Domain Recommendation for Cold-Start Users via Aspect Transfer Network. SIGIR 2020.
  • Zhihong Chen, Rong Xiao, Chenliang Li, Gangfeng Ye, Haochuan Sun and Hongbo Deng. ESAM: Discriminative Domain Adaptation with Non-Displayed Items to Improve Long-Tail Performance. SIGIR 2020.
  • Xusheng Luo, Luxin Liu, Yonghua Yang, Le Bo, Yuanpeng Cao, Jinhang Wu, Qiang Li, Kepin Yang and Kenny Q. Zhu. AliCoCo: Alibaba E-commerce Cognitive Concept Net. SIGMOD 2020.
  • Tong Zhang, Baoqliang Cui, Zhen Cui, Haikuan Huang,Jian Yang,Hongbo Deng, Bo Zheng Cross-Graph Convolution Learning for Large-Scale Text-Picture Shopping Guide in E-Commerce Search. ICDE 2020.
  • Zhao Li, Xin Sheng, Yuhang Jiao, Xuming Pan, Pengcheng Zou, Xianling Meng, Chenwei Yao, Jiajun Bu. Hierarchical Bipartite Graph Neural Networks: Towards Large-Scale E-commence Applications. ICDE 2020.
  • Shaofeng Cai, Gang Chen, Beng Chin Ooi, Jinyang Gao. Model Slicing for Supporting Complex Analytics with Elastic Inference Cost and Resource Constraints. VLDB 2020.
  • Kaiping Zheng, Wei Wang, Jinyang Gao, Meihui Zhang, Beng Chin Ooi. OPCM: Optimizing Task Decomposition for Reliable Learning. VLDB 2020.
  • Junshuai Song, Zhao Li, Zehong Hu, Jun Gao. PoisonRec: An Adaptive Data Poisoning Framework for Attacking Black-box Recommender Systems. ICDE 2020.
  • Yukuo Cen , Jing Zhang, Hongxia Yang and Jie Tang, Trust Prediction in Alibaba E-Commerce Platform, ACM Transactions on Knowledge and Data Engineering. TKDE 2019.
  • Zhaojing Luo, Shaofeng Cai, Jinyang Gao, Meihui Zhang, Kee Yuan Ngiam, Gang Chen, Wang-Chien Lee. Improving Data Analytics with Fast and Adaptive Regularization. TKDE 2019.
  • Yu Zhu, Jinghao Lin, Shibi He, Beidou Wang, Ziyu Guan and Deng Cai, Addressing the Item Cold-start Problem by Attribute-driven Active Learning, the IEEE Transactions on Knowledge and Data Engineering, 2019, to appear. TKDE 2019
  • Jinyang Gao, Junjie Yao, Yingxia Shao. Towards Reliable Learning for High Stakes Applications. AAAI 2019.
  • Tianhao Wang, Bolin Ding, Jingren Zhou, Cheng Hong, Zhicong Huang, Ninghui Li, and Somesh Jha. Answering Multi-Dimensional Analytical Queries under Local Differential Privacy. SIGMOD 2019.
  • Cedric Renggli, Bojan Karlas, Bolin Ding, Feng Liu, Kevin Schawinski, Wentao Wu, and Ce Zhang. Continuous Integration of Machine Learning Models: A Rigorous Yet Practical Treatment. SysML 2019.
  • Wei Wang, Jinyang Gao, Meihui Zhang, Sheng Wang, Gang Chen, Teck Khim Ng, Beng Chin Ooi, Jie Shao, Moaz Reyad. Rafiki: Machine Learning as an Analytics Service System. VLDB 2019.
  • Jianxin Ma, Chang Zhou, Peng Cui, Hongxia Yan and Wenwu Zhu. Learning Disentangled Representations for Recommendation. NeurIPS 2019.
  • Han Zhu, Daqing Chang, Ziru Xu, Pengye Zhang, Xiang Li, Jie He, Han Li, Jian Xu, Kun Gai. Joint Optimization of Tree-based Index and Deep Model for Recommender Systems. NeurIPS 2019.
  • Joshua Allen, Bolin Ding, Janardhan Kulkarni, Harsha Nori, Olga Ohrimenko, and Sergey Yekhanin. An Algorithmic Framework For Differentially Private Data Analysis on Trusted Processors. NeurIPS 2019.
  • Ming Ding, Chang Zhou, Qibin Chen, Hongxia Yang and Jie Tang. Cognitive Graph for Multi-Hop Reading Comprehension at Scale. ACL 2019.
  • Xun Yang, Yasong Li, Hao Wang, Di Wu, Qing Tan, Jian Xu, Kun Gai. Bid Optimization by Multivariable Control in Display Advertising. KDD 2019.
  • Shaohua Fan, Junxiong Zhu, Xiaotian Han, Chuan Shi, Linmei Hu, Biyu Ma and Yongliang Li:Metapath-guided Heterogeneous Graph Neural Network for Intent Recommendation. KDD 2019.
  • Jingwen Ye, Yixin Ji, Xinchao Wang, Kairi Ou, Dapeng Tao, Mingli Song.Student Becoming the Master: Knowledge Amalgamation for Joint Scene Parsing, Depth Estimation. CVPR 2019.
  • Anxiang Zeng, Han Yu, Xin Gao, Kairi Ou, Zhenchuan Huang, Peng Hou, Mingli Song, Jingshu Zhang and Chunyan Miao. An Online Intelligent Visual Interaction System PDF. IJCAI 2019.
  • Qianlong Liu, Baoliang Cui, Zhongyu Wei, Baolin Peng, Haikuan Huang, Hongbo Deng, Jianye Hao, Xuanjing Huang and Kam-fai Wong. Building Personalized Simulator for Interactive Search. IJCAI 2019.
  • Qiong Wu, Yong Liu, Chunyan Miao, Binqiang Zhao, Yin Zhao, Lu Guan, PD-GAN: Adversarial Learning for Personalized Diversity-Promoting Recommendation. IJCAI 2019.
  • Qiwei Chen, Huan Zhao,Wei Li, Pipei Huang, Wenwu Ou. Behavior Sequence Transformer for E-commerce Recommendation in Alibaba. KDD 2019.
  • Changhua Pei and Yi Zhang, Yongfeng Zhang, Fei Sun, Xiao Lin, Hanxiao Sun, Jian Wu, Peng Jiang, Junfeng Ge, Wenwu Ou, Dan Pei. Personalized Re-ranking for Recommendation. ReSys 2019.
  • Xiao Lin, Hongjie Chen, Changhua Pei, Fei Sun, Xuanji Xiao, Hanxiao Sun, Yongfeng Zhang, Wenwu Ou, Peng Jiang. A Pareto-Efficient Algorithm for Multiple Objective Optimization in E-Commerce Recommendation. RexSys 2019.
  • Xuanwu Liu, Zhao Li, Jun Wang, Guoxian Yu, Carlotta Domeniconi, and Xiangliang Zhang. Cross-modal Zero-shot Hashing. ICDM 2019.
  • Shen Xin, Martin Ester, Jiajun Bu, Chengwei Yao, Zhao Li, Xun Zhou, Yizhou Ye and Can Wang. Multi-task based Sales Predictions for Online Promotions. ICDM 2019.
  • Longbin Lai, Zhu Qing, Zhengyi Yang, Xin Jin, Zhengmin Lai, Ran Wang, Kongzhang Hao, Xuemin Lin, Lu Qin, Wenjie Zhang, Ying Zhang, Zhengping Qian, Jingren Zhou. Distributed subgraph matching on timely dataflow. VLDB 2019.
  • Min Xu, Tianhao Wang, Bolin Ding, Jingren Zhou, Cheng Hong, and Zhicong Huang. DPSAaS: Multi-Dimensional Data Sharing and Analytics as Services under Local Differential Privacy. VLDB 2019.
  • Yang Deng, Yaliang Li, Nan Du, Wei Fan, Ying Shen, Min Yang, and Kai Lei. MedTruth: A Semi-supervised Approach to Discovering Knowledge Condition Information from Multi-Source Medical Data. CIKM 2019.
  • Yu Zhu, Yu Gong, Qingwen Liu, Yingcai Ma, Wenwu Ou, Junxiong Zhu, Beidou Wang, Ziyu Guan, and Deng Cai. Query-based Interactive Recommendation by Meta-Path and Adapted Attention-GRU. CIKM 2019.
  • Fei Sun, Jun Liu, Jian Wu, Changhua Pei, Xiao Lin, Wenwu Ou and Peng Jiang. BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer. CIKM 2019.
  • Dagui Chen, Junqi Jin, Weinan Zhang, Fei Pan, Lvyin Niu, Chuan Yu, Jun Wang, Han Li, Jian Xu, Kun Gai. Learning to Advertise for Organic Traffic Maximization in E-Commerce Product Feeds. CIKM 2019.
  • Weixun Wang, Junqi Jin, Jianye Hao, Chunjie Chen, Chuan Yu, Weinan Zhang, Jun Wang, Yixi Wang, Han Li, Jian Xu, Kun Gai. Learning Adaptive Display Exposure for Real-Time Advertising. CIKM 2019.
  • Kan Ren, Jiarui Qin, Yuchen Fang, Weinan Zhang, Lei Zheng, Weijie Bian, Guorui Zhou, Jian Xu, Yong Yu, Xiaoqiang Zhu, Kun Gai. Lifelong Sequential Modeling with Personalized Memorization for User Response Prediction. SIGIR 2019.
  • Fei Xiao, Zhen Wang, HaiKuan Huang, et al. AliISA: Creating an Interactive Search Experience in E-commerce Platforms[C]//Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, 2019: 1305-1308. SIGIR 2019.
  • Bo Wang, Minghui Qiu, Xisen Wang, Yaliang Li, Yu Gong, Xiaoyi Zeng, Jun Huang, Bo Zheng, Deng Cai, Jingren Zhou: A Minimax Game for Instance based Selective Transfer Learning. KDD 2019.
  • Minghui Qiu, Bo Wang, Cen Chen, Xiaoyi Zeng, Jun Huang, Deng Cai, Jingren Zhou and Forrest Sheng Bao: Cross-domain Attention Network with Wasserstein Regularizers for E-commerce Search. CIKM 2019.
  • Yatao Yang, Jun Tan, Hongbo Deng, Zibin Zheng, Yutong Lu, Xiangke Liao: An Active and Deep Semantic Matching Framework for Query Rewrite in E-Commercial Search Engine. CIKM 2019.
  • Wen Chen, Pipei Huang, Jiaming Xu, Xin Guo, Cheng Guo, Fei Sun, Chao Li, Andreas Pfadler, Huan Zhao, Binqiang Zhao: POG: Personalized Outfit Generation for Fashion Recommendation at Alibaba iFashion. KDD 2019.
  • Chao Li, Zhiyuan Liu, Mengmeng Wu, Yuchi Xu, Pipei Huang, Huan Zhao, Guoliang Kang, Qiwei Chen, Wei Li, Dik Lun Lee: Multi-Interest Network with Dynamic Routing for Recommendation at Tmall. CIKM 2019.
  • Yu Gong, Yu Zhu, Lu Duan, Qingwen Liu, Guan Ziyu, Fei Sun, Wenwu Ou, Kenny Q. Zhu: Exact-K Recommendation via Maximal Clique Optimization. KDD 2019.
  • Xusong Chen, Chenyi Lei, Dong Liu, Rui Li, Zheng-Jun Zha and Zhiwei Xiong, BERT4SessRec: Content-Based Video Relevance Prediction with Bidirectional Encoder Representations from Transformer. ACM Multimedia 2019.
  • Fuyu Lv, Taiwei Jin, Changlong Yu, Fei Sun, Quan Lin, Keping Yang, Wilfred Ng, SDM: Sequential Deep Matching Model for Online Large-scale Recommender System. CIKM 2019.
  • Rong Xiao, Jianhui Ji, Baoliang Cui, Haihong Tang, Wenwu Ou, Yanghua Xiao, Jiwei Tan, Xuan Ju: Weakly Supervised Co-Training of Query Rewriting and Semantic Matching for e-Commerce. WSDM 2019.
  • Xusheng Luo, Yonghua Yang, Kenny Zhu, Yu Gong and Keping Yang, Conceptualize and Infer User Needs in E-commerce. CIKM 2019.
  • Li Zheng, Zhenpeng Li, Jian Li, Zhao Li, Jun Gao, AddGraph: Anomaly Detection in Dynamic Graph using Attention-based Temporal GCN. IJCAI 2019.
  • Xia Chen, Guoxian Yu, Jun Wang, Carlotta Domeniconi, Zhao Li, Xiangliang Zhang, ActiveHNE: Active Heterogeneous Network Embedding. IJCAI 2019.
  • Yufei Feng, Fuyu Lv, Weichen Shen, Menghan Wang, Fei Sun, Yu Zhu, Keping Yang, Deep Session Interest Network for Click-Through Rate Prediction. IJCAI 2019.
  • Jing He , Meng Han, Shouling Ji, Tianyu Du, and Zhao Li, Spreading Social Influence with both Positive and Negative Opinions in Online Networks. BDMA 2019.
  • Jianguo Zhang, Pengcheng Zou, Zhao Li, Yao Wan, Xiuming Pan, Yu Gong and Philip S Yu, Multi-Modal Generative Adversarial Network for Short Product Title Generation in Mobile E-Commerce. NAACL 2019.
  • Changhua Pei, Xinru Yang, Qing Cui, Xiao Lin, Fei Sun, Peng Jiang, Wenwu Ou, Yongfeng Zhang, Value-aware Recommendation based on Reinforced Profit Maximization in E-commerce Systems. WWW 2019.
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  • Li Chen, Yonghua Yang, Ningxia Wang, Keping Yang, Quan Yuan. How Serendipity Improves User Satisfaction with Recommendations? A Large-Scale User Evaluation. WWW 2019.
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  • Z Li, J Song, S Hu, S Ruan, L Zhang, Z Hu, J Gao. FAIR: Fraud Aware Impression Regulation System in Large-scale Real-time E-Commence Search Platform. ICDE 2019.
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  • Sihang Jiang,Jiaqing Liang,Yanghua Xiao,Haihong Tang,Haikuan Huang,Jun Tan.Towards the Completion of a Domain-Specific Knowledge Base with Emerging Query Terms. ICDE 2019.
  • Silu Huang, Chi Wang, Bolin Ding, and Surajit Chaudhuri. Efficient Identification of Approximate Best Configuration of Training in Large Datasets. AAAI 2019.
  • Hong Wen, Jing Zhang, Quan Lin, Keping Yang, Pipei Huang. Multi-Level Deep Cascade Trees for Conversion Rate Prediction in Recommendation System. AAAI 2019.
  • Z Hu, J Zhang, Z Li. General Robustness Evaluation of Incentive Mechanism Against Bounded Rationality Using Continuum-Armed Bandits. AAAI 2019.
  • Yu Gong , Xusheng Luo, Y Zhu, W Ou, Z Li, M Zhu, K Zhu, L Duan, X Chen. Deep Cascade Multi-task Learning for Slot Filling in Online Shopping Assistant. AAAI 2019.
  • Jing-Cheng Shi, Yang Yu, Qing Da, Shi-Yong Chen, An-Xiang Zeng. Virtual-Taobao: Virtualizing real-world online retail environment for reinforcement learning. AAAI 2019.
  • Feiyang Pan, Qingpeng Cai , An-Xiang Zeng , Chun-Xiang Pan, Qing Da, Hualin He, Qing He, Pingzhong Tang. Policy Optimization with Model-based Explorations. AAAI 2019.
  • P Wang, Z Li, X Pan, D Ding, X Chen, Y Hou. Density Matrix based Preference Evolution Networks for E-commerce Recommendation. DASFAA 2019.
  • Yu Gong, Xusheng Luo, K Q. Zhu, W Ou, Z Li, L Duan. Automatic Generation of Chinese Short Product Titles for Mobile Display. AAAI/IAAI 2019.
  • Z Hu, Y Liang, J Zhang, Z Li and Y Liu. Inference Aided Reinforcement Learning for Incentive Mechanism Design in Crowdsourcing. NIPS 2018.
  • Zhang J, Zou P, Li Z, Wan Y, Liu Y, Pan X, Gong Y, Yu PS. Product Title Refinement via Multi-Modal Generative Adversarial Learning. NIPS 2018.
  • Di Wu, Xiujun Chen, Xun Yang, Hao Wang, Qing Tan, Xiaoxun Zhang, Jian Xu, Kun Gai. Budget constrained bidding by model-free reinforcement learning in display advertising. CIKM 2018.
  • Fei Sun, Peng Jiang, Hanxiao Sun, Changhua Pei, Wenwu Ou and Xiaobo Wang: Multi-Source Pointer Network for Product Title Summarization. CIKM 2018.
  • C Chu, Z Li, B Xin, F Peng, C Liu, R Rohs, Q Luo, J Zhou. Deep Graph Embedding for Ranking Optimization in E-Commence. CIKM 2018.
  • Qiaolin Xia, Peng Jiang, Fei Sun, Yi Zhang, Xiaobo Wang and Zhifang Sui: Modeling Consumer Buying Decision for Recommendation Based on Multi-Task Deep Learning. CIKM 2018.
  • Yunlun Yang, Yu Gong and Xi Chen: Query Tracking for E-commerce Conversational Search: A Machine Comprehension Perspective. ICDM 2018.
  • X Chen, G Yu, C Domeniconi, J Wang, Z Li, and Z Zhang. Cost Effective Multi-label Active Learning via Querying Subexamples. ICDM 2018.
  • G Yu, X Chen, C Domeniconi. J Wang, Z Li, Z Zhang, X Wu. Feature-induced Partial Multi-label Learning. ICDM 2018.
  • J Zhang, J Wang, L He, Z Li, PS Yu. Layerwise Perturbation-Based Adversarial Training for Hard Drive Health Degree Prediction. ICDM 2018.
  • Jun Feng, Heng Li, Minlie Huang, Shichen Liu, Wenwu Ou, Zhirong Wang and Xiaoyan Zhu: "Learning to Collaborate: Multi-Scenario Ranking via Multi-Agent Reinforcement Learning". WWW 2018.
  • Ning Su, Yiqun Liu, Zhao Li, Yuli Liu, Min Zhang, Shaoping Ma: "Detecting Crowdturfing "Add to Favorites" Activities in Online Shopping". WWW 2018.
  • Haiqin Weng, Zhao Li, Shouling Ji, Chen Chu, Haifeng Lu, Tianyu Du, Qinming He: "Online E-Commerce Fraud: A Large-scale Detection and Analysis." ICDE 2018.
  • Zemin Liu, Vincent, Zhou Zhao, Zhao Li, Minghui Wu, Jing Ying, "Interactive Paths Embedding for Semantic Proximity Search on Heterogeneous Graphs". KDD 2018.
  • Jizhe Wang, Pipei Huang, Huan Zhao, Zhibo Zhang, Binqiang Zhao, Dik Lun Lee, "Billion-scale Commodity Embedding for E-commerce Recommendation in Alibaba". KDD 2018.
  • Yujing Hu, Qing Da, Anxiang Zeng, Yang Yu and Yinghui Xu,"Reinforcement Learning to Rank in E-Commerce Search Engine: Formalization, Analysis, and Application". KDD 2018.
  • Yabo Ni, Dan Ou, Shichen Liu, Xiang Li, Wenwu Ou, Anxiang Zeng, Luo Si, "Perceive Your Users in Depth: Learning Universal User Representations from Multiple E-commerce Tasks". KDD 2018.
  • Shi-Yong Chen, Yang Yu, Qing Da , Jun Tan , Hai-Kuan Huang and Hai-Hong Tang,"Stablizing Reinforcement Learning in Dynamic Environment with Application to Online Recommendation". KDD 2018.
  • Yang Yu, Shi-Yong Chen, Qing Da, and Zhi-Hua Zhou, Reusable Reinforcement Learning via Shallow Trails, the IEEE Transactions on Neural Networks and Learning Systems. TNNLS 2018.
  • Tengfei Zhou, Hui Qian, Chengwei Wang, Shichen Liu, Wenwu Ou, Zebang Shen, Chao Zhang, "JUMP: a Jointly Predictor for User Click and Dwell Time". IJCAI 2018.
  • Mengchen Zhao, Zhao Li, Bo An, Haifeng Lu,"Impression Allocation for Combating Fraud in E-commerce Via Deep Reinforcement Learning with Action Norm Penalty". IJCAI 2018.
  • Tao Zhuang, Wenwu Ou, Zhirong Wang, "Globally Optimized Mutual Influence Aware Ranking in E-Commerce Search". IJCAI 2018.
  • Yu Zhu, Junxiong Zhu, Jie Hou, Yongliang Li, Beidou Wang, Ziyu Guan, Deng Cai, "A Brand-level Ranking System with the Customized Attention-GRU Model".IJCAI 2018.
  • Kangqi Luo, Xusheng Luo, Fengli Lin, Kenny Zhu: Knowledge Base Question Answering via Encoding of Complex Query Graphs.EMNLP 2018.
  • Chen Xu, JianQiang Yao, Zhouchen Lin, Wenwu Ou, Yuanbin Cao, Zhirong Wang and Hongbing Zha: "Alternating Multi-bit Quantization for Recurrent Neural Networks". IC 2018
  • J Huang, Z Li, VW Zheng, W Wen, Y Yang, Y Chen. Unsupervised Multi-view Nonlinear Graph Embedding. UAI 2018.
  • H Xu, Z Li, C Chu, Y Chen, Y Yang, H Lu, H Wang, A Stavrou Detecting and Characterizing Web Bot Traffic in a Large E-commerce Marketplace. ESORICS 2018.
  • Zemin Liu, Vincent W. Zheng, Zhou Zhao, Hongxia Yang, Kevin Chen-Chuan Chang, Minghui Wu, Jing Ying. Subgraph-augmented Path Embedding for Semantic User Search on Heterogeneous Social Network. WWW 2018.
  • Zhen Zhang, Hongxia Yang, Jiajun Bu, Sheng Zhou, Pinggang Yu, Jianwei Zhang, Martin Ester, Can Wang. ANRL: Attributed Network Representation Learning via Deep Neural Networks. IJCAI 2018.
  • Ninghao Liu, Hongxia Yang, Xia Hu. Adversarial Detection with Model Interpretation. KDD 2018.
  • Dawei Zhou, Jingrui He, Hongxia Yang, Wei Fan. SPARC: Self-Paced Network Representation for Few-Shot Rare Category Characterization. KDD 2018.
  • Shen Xin, Weizhao Xian, Martin Ester, Hongxia Yang, Zhongyao Wnag, Jiajun Bu, Can Wang. Mobile access record resolution on large-scale identifier-linkage graphs. KDD 2018.
  • Zemin Liu, Vincent W. Zheng, Zhou Zhao, Zhao Li, Hongxia Yang, Minghui Wu, Jing Ying. Interactive Paths Embedding for Semantic Proximity Search on Heterogeneous Graphs. KDD 2018.
  • Xiafei Qiu, Wubin Cen, Zhengping Qian, You Peng, Ying Zhang, Xuemin Lin, Jingren Zhou. Real-time Constrained Cycle Detection in Large Dynamic Graphs. 43rd International Conference on Very Large Data Bases. VLDB 2018.
  • Sheng Zhou, Hongxia Yang, Martin Ester, Jiajun Bu, Pinggang Yu, Can Wang, Jianwei Zhang and Xin Wang. PRRE: Personalized Relation Ranking Embedding for Attributed Network. 27th ACM International Conference on Information and Knowledge Management. CIKM 2018.
  • Hongxia Yang, Yada Zhu, Jingrui He. Local Algorithm for User Action Prediction Towards Display Ads. 23rd ACM SIGKDD Conference on Knowledge Discovery and Data Mining. KDD 2017.
  • Chenglong Wang, Feijun Jiang, Hongxia Yang. Hybrid Framework for Text Modeling with Convolutional RNN. 23rd ACM SIGKDD Conference on Knowledge Discovery and Data Mining. KDD 2017.
  • Hongxia Yang. Bayesian Heteroscedastic Matrix Factorization for Conversion Rate Prediction. 26th ACM International Conference on Information and Knowledge Management. CIKM 2017.
  • Hong Huang, Yuxiao Dong, Jie Tang, Hongxia Yang, Nitesh V. Chawla, Xiaoming Fu. Will Triadic Closure Strengthen Ties in Social Networks, ACM Transactions on Knowledge Discovery from Data. TKDD 2017.
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