Minmin Chen
About Me
I am a senior staff research scientist at Google Brain. I received my PhD from Washington University in St. Louis, advised by Kilian Weinberger. My main research interests are in reinforcement learning and bandits algorithms and their applications in recommender systems. I am passionate about bringing AI to real life, especially to transform recommendation experiences.
Email me at minminc@google.com or contact me at LinkedIn.
Talks and Activities
[2024 Apr] Co-organizing 2024 KDD workshop on Two-sided Marketplace Optimization: Search, Pricing, Matching & Growth
[2024 Mar] Our paper on Long Term Value of Exploration: Measurements, Findings and Algorithms just won the Best Paper Award at WSDM 2024.
[2023 Dec] Co-organizing 2024 AAAI workshop on Synergy of Reinforcement Learning and Large Language Models (RL+LLMs).
[2023 Sep] Invited talk at 2023 LARGE-SCALE VIDEO RECOMMENDER SYSTEMS on Intents and Journeys: An LLM approach.
[2023 Sep] Invited talk at 2023 RecSys workshop on CONSEQUENCE: Causality, Counterfactuals & Sequential Decision-Making on Exploration.
[2023 Aug] Invited talk at 2023 AI Boot Camp (NTU, Aug. 17) on ALLY: Large Language Models for Recommendations.
[2023 June] Invited talk at 2023 Netflix Personalization, Recommendation and Search on ALLY: Large Language Models for Companion Recommenders.
[2023 May] Guest lecture at Stanford class on Human Centered Artificial Intelligence on Recommender Systems: Reinforcement Learning, Exploration and Languages.
[2023 Apr] Keynote at 2023 WebConf workshop on Decision Making for IR and RecSys on Exploration in Recommender Systems: Measurements and Algorithms.
[2022 Dec] Co-organizing 2022 Neurips workshop on RL for Real Life.
[2022 Nov] Guest lecture at Stanford class on Advance Survey of Reinforcement Learning on Surrogate for Long Term User Experiences in RecSys.
[2022 Feb] Invited talk at 2022 WSDM Industry Day on Measuring Exploration in Recommender Systems.
[2021 Dec] Invited talk at 2021 Neurips workshop on Offline Reinforcement Learning on Batch Reinforcement Learning for Recommender Systems.
[2021 Nov] Co-organizing 2022 Google workshop on Long-term Dynamics for Responsible Recommendation Systems.
[2021 Sep] Invited talk at 2021 RecSys Industry Day Talk on Exploration in Recommender Systems.
[2021 Jul] Co-organizing 2021 ICML workshop on RL for Real Life, moderating the RL for RecSys panel.
[2021 Jul] Co-organizing 2021 Google Research Reinforcement Learning workshop.
[2021 Jul] Keynote at 2021 SIGIR symposium on IR in practice (SIRIP) with Ed Chi on Beyond Being Accurate: Solving Real-World Recommendation Problems.
[2020 Oct] Invited talk at 2020 Search Engines Amsterdam on New Advances in Reinforcement Learning for Recommender Systems.
[2020 Sep] Invited talk at 2020 RecSys workshop on Bandit and Reinforcement Learning from User Interactions on New Applications of Bandits and Reinforcement Learning for Recommender Systems.
[2019 Aug] Co-organizing 2019 KDD workshop on Deep Reinforcement Learning for Knowledge Discovery.
[2019 Aug] Co-organizing 2019 KDD workshop on Offline and Online Evaluation of Interactive Systems.
[2019 May] Invited talk at 2019 Netflix workshop on Personalization, Recommendation and Search on Reinforcement Learning for Recommender Systems.
[2019 Feb] Invited talk at 2019 WSDM Industry Day, won best Industry Day presentation award.
[2018 Oct] Invited talk at 2018 RecSys workshop on Offline Evaluation for Recommender Systems (REVEAL) on RL for RecSys: A Case Study on YouTube.
Area chair for Neurips(2019-2021, 2023), ICLR(2019-2024), ICML (2019-2023), AISTATS 2019.
Select Publications (Google Scholar)
Recommendation Systems
- Large Language Models for User Interest Journeys
...Konstantina Christakopoulou, Alberto Lalama, Cj Adams, Iris Qu, Yifat Amir, Samer Chucri, Pierce Vollucci, Fabio Soldo, Dina Bseiso, Sarah Scodel, Lucas Dixon, Ed H. Chi, Minmin Chen...Under submission
- Prompt Tuning Large Language Models on Personalized Aspect Extraction for Recommendations
...Pan Li, Yuyan Wang, Ed H. Chi, Minmin Chen...Under submission- Value of Exploration: Measurements, Findings and Algorithms
...Yi Su, Xiangyu Wang, Elaine Ya Le, Liang Liu, Yuening Li, Haokai Lu, Benjamin Lipshitz, Sriraj Badam, Lukasz Heldt, Shuchao Bi, Ed Chi, Cristos Goodrow, Su-Lin Wu, Lexi Baugher, Minmin Chen...WSDM 2024- Fresh Content Needs More Attention: Multi-funnel Fresh Content Recommendation
...Jianling Wang*, Haokai Lu*, Sai zhang, Bart Locanthi, Haoting Wang, Dylan Greaves, Benjamin Lipshitz, Sriraj Badam, Ed H. Chi, Cristos Goodrow, Su-Lin Wu, Lexi Baugher, Minmin Chen...KDD 2023- Off-Policy Actor Critic for Recommender Systems
...Minmin Chen, Can Xu, Vince Gatto, Devanshu Jain, Aviral Kumar, Ed Chi...RecSys 2022- Surrogate for long-term user experience in recommender systems
...Yuyan Wang, Mohit Sharma, Can Xu, Sriraj Badam, Qian Sun, Lee Richardson, Lisa Chung, Ed Chi, Minmin Chen...KDD 2022- Exploration in recommender systems
...Minmin Chen...RecSys 2021- Off-policy learning in two-stage recommender systems
...Jiaqi Ma, Zhe Zhao, Xinyang Yi, Ji Yang, Minmin Chen, Jiaxi Tang, Lichan Hong, Ed Chi...WebConf 2020- Quantifying long range dependence in language and user behavior to improve RNNs
...Francois Belletti, Minmin Chen, Ed Chi...KDD 2019- Top-k off-policy correction for a REINFORCE recommender system
...Minmin Chen, Alex Beutel, Paul Covington, Sagar Jain, Francois Belletti, Ed Chi...WSDM 2019Machine Learning and AI
- Correction with Backtracking Reduces Hallucination in Summarization
...Zhenzhen Liu, Chao Wan, Varsha Kishore, Jin Peng Zhou, Minmin Chen, Kilian Q Weinberger...ArXiv 2023
- Surrogate objectives for batch policy optimization in one-step decision making
...Minmin Chen*, Ramki Gummadi*, Chris Harris*, Dale Schuurmans*...Neurips 2019- AntisymmetricRNN: A Dynamical System View on Recurrent Neural Networks
...Bo Chang, Minmin Chen, Eldad Haber, Ed Chi...ICLR 2019- Dynamical isometry and a mean field theory of RNNs: Gating enables signal propagation in recurrent neural networks
...Minmin Chen, Jeffrey Pennington, Samuel Schoenholz...ICML 2018- Classifier cascades and trees for minimizing feature evaluation cost
...Zhixiang Xu, Matt J Kusner, Kilian Q Weinberger, Minmin Chen, Olivier Chapelle...JMLR 2014- Marginalized denoising auto-encoders for nonlinear representations
...Minmin Chen, Kilian Weinberger, Fei Sha, Yoshua Bengio...ICML 2014- Marginalized denoising autoencoders for domain adaptation
...Minmin Chen, Zhixiang Xu, Kilian Weinberger, Fei Sha...ICML 2012- Co-training for domain adaptation
...Minmin Chen, Kilian Q Weinberger, John Blitzer...Neurips 2011 - Surrogate objectives for batch policy optimization in one-step decision making
- Prompt Tuning Large Language Models on Personalized Aspect Extraction for Recommendations