Schedule (updated)

Schedule (updated)

Opening (1:20pm to 1:30pm)

Keynotes (1:30pm to 2:30pm)

  1. Xiaoli Li, A*STAR, “Machine learning for Recommendation Systems”.
  2. Xia Hu, Texas A&M University, “Recommender Systems in “DEEP”: Architectures and Insights”.

Industry Invited Talk (2:30pm to 3:10pm)

  1. Le Zhang, Microsoft, “Democratizing Recommendation System”.
  2. Xiangyu Chen, Shopee, “Graph Embedding for Effective Recommendations”.

Coffee Break (3:10pm to 3:30pm)

Paper presentations (3:30pm to 5:30pm)

NOTE: each paper will be given 15 minutes for presentation AND Q&A.

  1. Hanqing Zhao, Ya Zhang, and Yanfeng Wang, “Recommendation with Hybrid Interest Model”.
  2. Xiaoyao Zheng, Yonglong Luo, Ji Zhang, Liping Sun, and Fulong Chen, “A Novel Differential Privacy Recommendation Method Based on A Distributed Framework”.
  3. Kun Niu, Haizhen Jiao, Xiao Xu, Cheng Cheng, and Chao Wang, “A Novel Learning Approach to Improve Mobile Application Recommendation Diversity”.
  4. Vaibhav Krishna, Tian Guo, and Nino Antulov-Fantulin, “Is Simple Better? Revisiting Non-linear Matrix Factorization for Learning Incomplete Ratings”.
  5. Anup Anand Deshmukh, Pratheeksha Nair, and Shrisha Rao, “A Scalable Clustering Algorithm for Serendipity in Recommender Systems”.
  6. Iqra Safder and Saeed-Ul Hassan, “DS4A: Deep Search System for Algorithms from Full-text Scholarly Big Data”.
  7. Peter Ballen and Sudipto Guha, “Elastic Nonnegative Matrix Factorization”.
  8. Zhaoqiang Li, Jiajin Huang, and Ning Zhong, “Leveraging Reconstructive Profiles of Users and Items for Tag-Aware Recommendation”.
  9. Guoshuai Zhao, Hao Fu, Ruihua Song, Tetsuya Sakai, Xing Xie, and Xueming Qian, “Why You Should Listen to This Song: Reason Generation for Explainable Recommendation”.


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