李昌(Chang Li)

Li 

Cheers! I'm a final year PhD student at ILPS, University of Amsterdam, UvA, supervised by Prof. Dr. Maarten de Rijke. I am interested in designing online algorithms that solve ranking problems. Typically, I focus on the following topics: online learning to rank, multi-armed bandits, federated learning. I received my bachelor degree from TJU in 2013. My mentor was Dr. Xin Wang. Then I received my master degree from USTC, supervised by Prof. Dr. Huanhuan Chen in 2016. You may find more about me in my CV.

Email: c.li AT uva DOT nl

Preprint

  • Chang Li, Artem Grotov, Ilya Markov, and Maarten de Rijke. Online learning to rank with list-level feedback for image filtering, 2018. (Preprints)

Conference

  • Chang Li, Haoyun Feng and Maarten de Rijke. “Cascading Hybrid Bandits: Online Learning to Rank for Relevance and Diversity”. In RecSys 2020: The ACM Conference on Recommender Systems. ACM, September 2020. (Preprints)

  • Chang Li and Maarten de Rijke. “Cascading Non-Stationary Bandits: Online Learning to Rank in the Non-Stationary Cascade Model”. In IJCAI 2019: Twenty-Eighth International Joint Conference on Artificial Intelligence, August 2019. (Preprints, Code)

  • Chang Li, Branislav Kveton, Tor Lattimore, Ilya Markov, Maarten de Rijke, Csaba Szepesvari, and Masrour Zoghi. “BubbleRank: Safe Online Learning to Re-Rank via Implicit Click Feedback”. In UAI 2019: Conference on Uncertainty in Artificial Intelligence, July 2019.(Preprints, Poster, Code)

  • Chang Li and Huanhuan Chen. “Sparse Bayesian approach for feature selection”, IEEE Symposium on Computational Intelligence in Big Data (CIBD), IEEE Symposium Series on Computational Intelligence (SSCI), 2014. (Link, Slides, Code)

Journal

  • Chang Li, Ilya Markov, Maarten de Rijke, and Masrour Zoghi. “MergeDTS: A Method for Effective Large-Scale Online Ranker Evaluation”, ACM Transactions on Information Systems (TOIS). 38(4), December 2020. (Preprints, Code)

  • Bingbing Jiang, Chang Li, Maarten de Rijke, Xin Yao, and Huanhuan Chen. “Probabilistic feature selection and classification vector machine”, ACM Transactions on Knowledge Discovery from Data (TKDD), 13(2): Article 21, April 2019.(Link, Preprints)

  • Chang Li and Maarten de Rijke. “Incremental Sparse Bayesian Ordinal Regression”, Neural Networks, Volume 106, October 2018, Pages 294-302. (Link, PDF, Code)

Presentations

  • “MergeDTS for Large Scale Condorcet Dueling Bandits”, the 4th annual Machine Learning in the Real World Workshop, at Criteo Paris, France, June 2018. (Slides)

  • “Large Scale Pair-wise Online Ranker Evaluation with Double Thompson Sampling”, Russian Summer School in Information Retrieval, Ekaterinburg, Russia, August 2017.

  • “Sparse Bayesian Learning”, Anhui Conference on Artificial Intelligence, Hefei, Anhui, July 2014. (in Chinese)