Minmin Chen
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
50
Venues
13
Active years
2008–2025
Best venue rank
A*
Where they publish
Papers
50 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ACL | User Feedback Alignment for LLM-powered Exploration in Large-scale Recommendation Systems. | Jianling Wang, Yifan Liu, Yinghao Sun, Xuejian Ma, Yueqi Wang, He Ma, Zhengyang Su, Minmin Chen, Mingyan Gao, Onkar Dalal, Ed H. Chi, Lichan Hong, Ningren Han, Haokai Lu |
| 2025 | ICML | EVOLvE: Evaluating and Optimizing LLMs For In-Context Exploration. | Allen Nie, Yi Su, Bo Chang, Jonathan Lee, Ed H. Chi, Quoc V. Le, Minmin Chen |
| 2025 | KDD | TSMO 2025: Two-sided Marketplace Optimization: Search, Discovery, Matching, Pricing & Growth. | Mihajlo Grbovic, Vladan Radosavljevic, Amit Goyal, Rui Song, Minmin Chen, Zhiwei Qin, Katerina Iliakopoulou-Zanos, Thanasis Noulas, Hongtu Zhu, Fabrizio Silvestri |
| 2025 | KDD | Beyond Item Dissimilarities: Diversifying by Intent in Recommender Systems. | Yuyan Wang, Cheenar Banerjee, Samer Chucri, Fabio Soldo, Sriraj Badam, Ed H. Chi, Minmin Chen |
| 2024 | ICTIR | Exploration: Measurements and Systems. | Minmin Chen |
| 2024 | KDD | TSMO 2024: Two-sided Marketplace Optimization. | Mihajlo Grbovic, Vladan Radosavljevic, Minmin Chen, Katerina Iliakopoulou-Zanos, Thanasis Noulas, Amit Goyal, Fabrizio Silvestri |
| 2024 | KDD | Multi-Task Neural Linear Bandit for Exploration in Recommender Systems. | Yi Su, Haokai Lu, Yuening Li, Liang Liu, Shuchao Bi, Ed H. Chi, Minmin Chen |
| 2024 | RecSys | LLMs for User Interest Exploration in Large-scale Recommendation Systems. | Jianling Wang, Haokai Lu, Yifan Liu, He Ma, Yueqi Wang, Yang Gu, Shuzhou Zhang, Ningren Han, Shuchao Bi, Lexi Baugher, Ed H. Chi, Minmin Chen |
| 2024 | WWW | Cluster Anchor Regularization to Alleviate Popularity Bias in Recommender Systems. | Bo Chang, Changping Meng, He Ma, Shuo Chang, Yang Gu, Yajun Peng, Jingchen Feng, Yaping Zhang, Shuchao Bi, Ed H. Chi, Minmin Chen |
| 2024 | WWW | Large Language Models as Data Augmenters for Cold-Start Item Recommendation. | Jianling Wang, Haokai Lu, James Caverlee, Ed H. Chi, Minmin Chen |
| 2024 | WSDM | Long-Term 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 H. Chi, Cristos Goodrow, Su-Lin Wu, Lexi Baugher, Minmin Chen |
| 2024 | WSDM | Fresh Content Recommendation at Scale: A Multi-funnel Solution and the Potential of LLMs. | Jianling Wang, Haokai Lu, Minmin Chen |
| 2023 | KDD | Fresh Content Needs More Attention: Multi-funnel Fresh Content Recommendation. | Jianling Wang, Haokai Lu, Sai Zhang, Bart N. Locanthi, Haoting Wang, Dylan Greaves, Benjamin Lipshitz, Sriraj Badam, Ed H. Chi, Cristos J. Goodrow, Su-Lin Wu, Lexi Baugher, Minmin Chen |
| 2023 | RecSys | Towards Companion Recommenders Assisting Users' Long-Term Journeys. | Konstantina Christakopoulou, Minmin Chen |
| 2023 | RecSys | Nonlinear Bandits Exploration for Recommendations. | Yi Su, Minmin Chen |
| 2023 | RecSys | Online Matching: A Real-time Bandit System for Large-scale Recommendations. | Xinyang Yi, Shao-Chuan Wang, Ruining He, Hariharan Chandrasekaran, Charles Wu, Lukasz Heldt, Lichan Hong, Minmin Chen, Ed H. Chi |
| 2023 | WWW | Latent User Intent Modeling for Sequential Recommenders. | Bo Chang, Alexandros Karatzoglou, Yuyan Wang, Can Xu, Ed H. Chi, Minmin Chen |
| 2023 | WWW | Investigating Action-Space Generalization in Reinforcement Learning for Recommendation Systems. | Abhishek Naik, Bo Chang, Alexandros Karatzoglou, Martin Mladenov, Ed H. Chi, Minmin Chen |
| 2022 | KDD | Surrogate for Long-Term User Experience in Recommender Systems. | Yuyan Wang, Mohit Sharma, Can Xu, Sriraj Badam, Qian Sun, Lee Richardson, Lisa Chung, Ed H. Chi, Minmin Chen |
| 2022 | RecSys | Off-Policy Actor-critic for Recommender Systems. | Minmin Chen, Can Xu, Vince Gatto, Devanshu Jain, Aviral Kumar, Ed H. Chi |
| 2022 | WWW | Learning to Augment for Casual User Recommendation. | Jianling Wang, Ya Le, Bo Chang, Yuyan Wang, Ed H. Chi, Minmin Chen |
| 2022 | WSDM | Exploration in Recommender Systems. | Minmin Chen |
| 2021 | ICLR | Batch Reinforcement Learning Through Continuation Method. | Yijie Guo, Shengyu Feng, Nicolas Le Roux, Ed H. Chi, Honglak Lee, Minmin Chen |
| 2021 | RecSys | Exploration in Recommender Systems. | Minmin Chen |
| 2021 | RecSys | Values of User Exploration in Recommender Systems. | Minmin Chen, Yuyan Wang, Can Xu, Ya Le, Mohit Sharma, Lee Richardson, Su-Lin Wu, Ed H. Chi |
| 2021 | WWW | Towards Content Provider Aware Recommender Systems: A Simulation Study on the Interplay between User and Provider Utilities. | Ruohan Zhan, Konstantina Christakopoulou, Ya Le, Jayden Ooi, Martin Mladenov, Alex Beutel, Craig Boutilier, Ed H. Chi, Minmin Chen |
| 2021 | WSDM | User Response Models to Improve a REINFORCE Recommender System. | Minmin Chen, Bo Chang, Can Xu, Ed H. Chi |
| 2020 | RecSys | Deconfounding User Satisfaction Estimation from Response Rate Bias. | Konstantina Christakopoulou, Madeleine Traverse, Trevor Potter, Emma Marriott, Daniel Li, Chris Haulk, Ed H. Chi, Minmin Chen |
| 2020 | WWW | Off-policy Learning in Two-stage Recommender Systems. | Jiaqi Ma, Zhe Zhao, Xinyang Yi, Ji Yang, Minmin Chen, Jiaxi Tang, Lichan Hong, Ed H. Chi |
| 2019 | ICLR | AntisymmetricRNN: A Dynamical System View on Recurrent Neural Networks. | Bo Chang, Minmin Chen, Eldad Haber, Ed H. Chi |
| 2019 | KDD | Quantifying Long Range Dependence in Language and User Behavior to improve RNNs. | Francois Belletti, Minmin Chen, Ed H. Chi |
| 2019 | WWW | Towards Neural Mixture Recommender for Long Range Dependent User Sequences. | Jiaxi Tang, Francois Belletti, Sagar Jain, Minmin Chen, Alex Beutel, Can Xu, Ed H. Chi |
| 2019 | WSDM | Top-K Off-Policy Correction for a REINFORCE Recommender System. | Minmin Chen, Alex Beutel, Paul Covington, Sagar Jain, Francois Belletti, Ed H. Chi |
| 2019 | SDM | EstImAgg: A Learning Framework for Groupwise Aggregated Data. | Avradeep Bhowmik, Minmin Chen, Zhengming Xing, Suju Rajan |
| 2018 | ICML | Dynamical Isometry and a Mean Field Theory of RNNs: Gating Enables Signal Propagation in Recurrent Neural Networks. | Minmin Chen, Jeffrey Pennington, Samuel S. Schoenholz |
| 2018 | RecSys | Categorical-attributes-based item classification for recommender systems. | Qian Zhao, Jilin Chen, Minmin Chen, Sagar Jain, Alex Beutel, Francois Belletti, Ed H. Chi |
| 2017 | ICLR | Efficient Vector Representation for Documents through Corruption. | Minmin Chen |
| 2015 | AAAI | Marginalized Denoising for Link Prediction and Multi-Label Learning. | Zheng Chen, Minmin Chen, Kilian Q. Weinberger, Weixiong Zhang |
| 2014 | ICML | Marginalized Denoising Auto-encoders for Nonlinear Representations. | Minmin Chen, Kilian Q. Weinberger, Fei Sha, Yoshua Bengio |
| 2013 | ICML | Fast Image Tagging. | Minmin Chen, Alice X. Zheng, Kilian Q. Weinberger |
| 2013 | ICML | Learning with Marginalized Corrupted Features. | Laurens van der Maaten, Minmin Chen, Stephen Tyree, Kilian Q. Weinberger |
| 2013 | ICML | Cost-Sensitive Tree of Classifiers. | Zhixiang Eddie Xu, Matt J. Kusner, Kilian Q. Weinberger, Minmin Chen |
| 2012 | CIKM | From sBoW to dCoT marginalized encoders for text representation. | Zhixiang Eddie Xu, Minmin Chen, Kilian Q. Weinberger, Fei Sha |
| 2012 | ICML | Marginalized Denoising Autoencoders for Domain Adaptation. | Minmin Chen, Zhixiang Eddie Xu, Kilian Q. Weinberger, Fei Sha |
| 2011 | CIKM | Improving context-aware query classification via adaptive self-training. | Minmin Chen, Jian-Tao Sun, Xiaochuan Ni, Yixin Chen |
| 2011 | ICDM | Medical Data Mining for Early Deterioration Warning in General Hospital Wards. | Yi Mao, Yixin Chen, Gregory Hackmann, Minmin Chen, Chenyang Lu, Marin Kollef, Thomas C. Bailey |
| 2011 | ICML | Automatic Feature Decomposition for Single View Co-training. | Minmin Chen, Kilian Q. Weinberger, Yixin Chen |
| 2009 | ICTAI | Gradient-Based Feature Selection for Conditional Random Fields and its Applications in Computational Genetics. | Minmin Chen, Yixin Chen, Michael R. Brent, Aaron E. Tenney |
| 2009 | KDD | Constrained optimization for validation-guided conditional random field learning. | Minmin Chen, Yixin Chen, Michael R. Brent, Aaron E. Tenney |
| 2008 | AAAI | CRF-OPT: An Efficient High-Quality Conditional Random Field Solver. | Minmin Chen, Yixin Chen, Michael R. Brent |