Minmin Chen

Publication Activity (10 Years)

Years Active: 2008-2024
Publications (10 Years): 58

Top Topics

Reinforcement Learning

Recurrent Neural Networks

User Satisfaction

Recommender Systems

Top Venues

Publications

Minmin Chen
Exploration: Measurements and Systems. ICTIR (2024)
Jianling Wang, Haokai Lu, James Caverlee, Ed H. Chi, Minmin Chen
Large Language Models as Data Augmenters for Cold-Start Item Recommendation. WWW (Companion Volume) (2024)
Jianling Wang, Haokai Lu, Minmin Chen
Fresh Content Recommendation at Scale: A Multi-funnel Solution and the Potential of LLMs. WSDM (2024)
Mihajlo Grbovic, Vladan Radosavljevic, Minmin Chen, Katerina Iliakopoulou-Zanos, Thanasis Noulas, Amit Goyal, Fabrizio Silvestri
TSMO 2024: Two-sided Marketplace Optimization. KDD (2024)
Yi Su, Haokai Lu, Yuening Li, Liang Liu, Shuchao Bi, Ed H. Chi, Minmin Chen
Multi-Task Neural Linear Bandit for Exploration in Recommender Systems. KDD (2024)
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
Long-Term Value of Exploration: Measurements, Findings and Algorithms. WSDM (2024)
Bo Chang, Changping Meng, He Ma, Shuo Chang, Yang Gu, Yajun Peng, Jingchen Feng, Yaping Zhang, Shuchao Bi, Ed H. Chi, Minmin Chen
Cluster Anchor Regularization to Alleviate Popularity Bias in Recommender Systems. WWW (Companion Volume) (2024)
Yuyan Wang, Cheenar Banerjee, Samer Chucri, Fabio Soldo, Sriraj Badam, Ed H. Chi, Minmin Chen
Diversifying by Intent in Recommender Systems. CoRR (2024)
Jianling Wang, Haokai Lu, James Caverlee, Ed H. Chi, Minmin Chen
Large Language Models as Data Augmenters for Cold-Start Item Recommendation. CoRR (2024)
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
LLMs for User Interest Exploration: A Hybrid Approach. CoRR (2024)
Huaixiu Steven Zheng, Swaroop Mishra, Hugh Zhang, Xinyun Chen, Minmin Chen, Azade Nova, Le Hou, Heng-Tze Cheng, Quoc V. Le, Ed H. Chi, Denny Zhou
NATURAL PLAN: Benchmarking LLMs on Natural Language Planning. CoRR (2024)
Abhishek Naik, Bo Chang, Alexandros Karatzoglou, Martin Mladenov, Ed H. Chi, Minmin Chen
Investigating Action-Space Generalization in Reinforcement Learning for Recommendation Systems. WWW (Companion Volume) (2023)
Yi Su, Minmin Chen
Nonlinear Bandits Exploration for Recommendations. RecSys (2023)
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
Large Language Models for User Interest Journeys. CoRR (2023)
Pan Li, Yuyan Wang, Ed H. Chi, Minmin Chen
Hierarchical Reinforcement Learning for Modeling User Novelty-Seeking Intent in Recommender Systems. CoRR (2023)
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
Value of Exploration: Measurements, Findings and Algorithms. CoRR (2023)
Zhenzhen Liu, Chao Wan, Varsha Kishore, Jin Peng Zhou, Minmin Chen, Kilian Q. Weinberger
Correction with Backtracking Reduces Hallucination in Summarization. CoRR (2023)
Jianling Wang, Haokai Lu, Sai Zhang, Bart N. Locanthi, Haoting Wang, Dylan Greaves, Benjamin Lipshitz, Sriraj Badam, Ed H. Chi, Cristos Goodrow, Su-Lin Wu, Lexi Baugher, Minmin Chen
Fresh Content Needs More Attention: Multi-funnel Fresh Content Recommendation. CoRR (2023)
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
Fresh Content Needs More Attention: Multi-funnel Fresh Content Recommendation. KDD (2023)
Xinyang Yi, Shao-Chuan Wang, Ruining He, Hariharan Chandrasekaran, Charles Wu, Lukasz Heldt, Lichan Hong, Minmin Chen, Ed H. Chi
Online Matching: A Real-time Bandit System for Large-scale Recommendations. RecSys (2023)
Xinyang Yi, Shao-Chuan Wang, Ruining He, Hariharan Chandrasekaran, Charles Wu, Lukasz Heldt, Lichan Hong, Minmin Chen, Ed H. Chi
Online Matching: A Real-time Bandit System for Large-scale Recommendations. CoRR (2023)
Konstantina Christakopoulou, Minmin Chen
Towards Companion Recommenders Assisting Users' Long-Term Journeys. RecSys (2023)
Pan Li, Yuyan Wang, Ed H. Chi, Minmin Chen
Prompt Tuning Large Language Models on Personalized Aspect Extraction for Recommendations. CoRR (2023)
Bo Chang, Alexandros Karatzoglou, Yuyan Wang, Can Xu, Ed H. Chi, Minmin Chen
Latent User Intent Modeling for Sequential Recommenders. WWW (Companion Volume) (2023)
Yuguang Wu, Minmin Chen, Xin Wang
Incentivized self-rebalancing fleet in electric vehicle sharing. IISE Trans. 54 (2) (2022)
Jianling Wang, Ya Le, Bo Chang, Yuyan Wang, Ed H. Chi, Minmin Chen
Learning to Augment for Casual User Recommendation. CoRR (2022)
Minmin Chen, Can Xu, Vince Gatto, Devanshu Jain, Aviral Kumar, Ed H. Chi
Off-Policy Actor-critic for Recommender Systems. RecSys (2022)
Jianling Wang, Ya Le, Bo Chang, Yuyan Wang, Ed H. Chi, Minmin Chen
Learning to Augment for Casual User Recommendation. WWW (2022)
Yuyan Wang, Mohit Sharma, Can Xu, Sriraj Badam, Qian Sun, Lee Richardson, Lisa Chung, Ed H. Chi, Minmin Chen
Surrogate for Long-Term User Experience in Recommender Systems. KDD (2022)
Bo Chang, Can Xu, Matthieu Lê, Jingchen Feng, Ya Le, Sriraj Badam, Ed Chi, Minmin Chen
Recency Dropout for Recurrent Recommender Systems. CoRR (2022)
Konstantina Christakopoulou, Can Xu, Sai Zhang, Sriraj Badam, Trevor Potter, Daniel Li, Hao Wan, Xinyang Yi, Ya Le, Chris Berg, Eric Bencomo Dixon, Ed H. Chi, Minmin Chen
Reward Shaping for User Satisfaction in a REINFORCE Recommender. CoRR (2022)
Minmin Chen
Exploration in Recommender Systems. WSDM (2022)
Bo Chang, Alexandros Karatzoglou, Yuyan Wang, Can Xu, Ed H. Chi, Minmin Chen
Latent User Intent Modeling for Sequential Recommenders. CoRR (2022)
Minmin Chen, Yuyan Wang, Can Xu, Ya Le, Mohit Sharma, Lee Richardson, Su-Lin Wu, Ed Chi
Values of User Exploration in Recommender Systems. RecSys (2021)
Ruohan Zhan, Konstantina Christakopoulou, Ya Le, Jayden Ooi, Martin Mladenov, Alex Beutel, Craig Boutilier, Ed H. Chi, Minmin Chen
Towards Content Provider Aware Recommender Systems: A Simulation Study on the Interplay between User and Provider Utilities. CoRR (2021)
Minmin Chen
Exploration in Recommender Systems. RecSys (2021)
Ruohan Zhan, Konstantina Christakopoulou, Ya Le, Jayden Ooi, Martin Mladenov, Alex Beutel, Craig Boutilier, Ed Chi, Minmin Chen
Towards Content Provider Aware Recommender Systems: A Simulation Study on the Interplay between User and Provider Utilities. WWW (2021)
Yijie Guo, Shengyu Feng, Nicolas Le Roux, Ed Chi, Honglak Lee, Minmin Chen
Batch Reinforcement Learning Through Continuation Method. ICLR (2021)
Minmin Chen, Bo Chang, Can Xu, Ed H. Chi
User Response Models to Improve a REINFORCE Recommender System. WSDM (2021)
Konstantina Christakopoulou, Madeleine Traverse, Trevor Potter, Emma Marriott, Daniel Li, Chris Haulk, Ed H. Chi, Minmin Chen
Deconfounding User Satisfaction Estimation from Response Rate Bias. RecSys (2020)
Jiaqi Ma, Zhe Zhao, Xinyang Yi, Ji Yang, Minmin Chen, Jiaxi Tang, Lichan Hong, Ed H. Chi
Off-policy Learning in Two-stage Recommender Systems. WWW (2020)
Bo Chang, Minmin Chen, Eldad Haber, Ed H. Chi
AntisymmetricRNN: A Dynamical System View on Recurrent Neural Networks. ICLR (Poster) (2019)
Jiaxi Tang, Francois Belletti, Sagar Jain, Minmin Chen, Alex Beutel, Can Xu, Ed H. Chi
Towards Neural Mixture Recommender for Long Range Dependent User Sequences. CoRR (2019)
Bo Chang, Minmin Chen, Eldad Haber, Ed H. Chi
AntisymmetricRNN: A Dynamical System View on Recurrent Neural Networks. CoRR (2019)
Avradeep Bhowmik, Minmin Chen, Zhengming Xing, Suju Rajan
EstImAgg: A Learning Framework for Groupwise Aggregated Data. SDM (2019)
Jiaxi Tang, Francois Belletti, Sagar Jain, Minmin Chen, Alex Beutel, Can Xu, Ed H. Chi
Towards Neural Mixture Recommender for Long Range Dependent User Sequences. WWW (2019)
Dar Gilboa, Bo Chang, Minmin Chen, Greg Yang, Samuel S. Schoenholz, Ed H. Chi, Jeffrey Pennington
Dynamical Isometry and a Mean Field Theory of LSTMs and GRUs. CoRR (2019)
Francois Belletti, Minmin Chen, Ed H. Chi
Quantifying Long Range Dependence in Language and User Behavior to improve RNNs. CoRR (2019)
Francois Belletti, Minmin Chen, Ed H. Chi
Quantifying Long Range Dependence in Language and User Behavior to improve RNNs. KDD (2019)
Minmin Chen, Ramki Gummadi, Chris Harris, Dale Schuurmans
Surrogate Objectives for Batch Policy Optimization in One-step Decision Making. NeurIPS (2019)
Minmin Chen, Alex Beutel, Paul Covington, Sagar Jain, Francois Belletti, Ed H. Chi
Top-K Off-Policy Correction for a REINFORCE Recommender System. WSDM (2019)
Qian Zhao, Jilin Chen, Minmin Chen, Sagar Jain, Alex Beutel, Francois Belletti, Ed H. Chi
Categorical-attributes-based item classification for recommender systems. RecSys (2018)
Minmin Chen, Jeffrey Pennington, Samuel S. Schoenholz
Dynamical Isometry and a Mean Field Theory of RNNs: Gating Enables Signal Propagation in Recurrent Neural Networks. ICML (2018)
Minmin Chen, Alex Beutel, Paul Covington, Sagar Jain, Francois Belletti, Ed H. Chi
Top-K Off-Policy Correction for a REINFORCE Recommender System. CoRR (2018)
Minmin Chen, Jeffrey Pennington, Samuel S. Schoenholz
Dynamical Isometry and a Mean Field Theory of RNNs: Gating Enables Signal Propagation in Recurrent Neural Networks. CoRR (2018)
Minmin Chen
Efficient Vector Representation for Documents through Corruption. ICLR (Poster) (2017)
Minmin Chen
MinimalRNN: Toward More Interpretable and Trainable Recurrent Neural Networks. CoRR (2017)
Minmin Chen
Efficient Vector Representation for Documents through Corruption. CoRR (2017)
Zheng Chen, Minmin Chen, Kilian Q. Weinberger, Weixiong Zhang
Marginalized Denoising for Link Prediction and Multi-Label Learning. AAAI (2015)
Minmin Chen, Kilian Q. Weinberger, Zhixiang Eddie Xu, Fei Sha
Marginalizing stacked linear denoising autoencoders. J. Mach. Learn. Res. 16 (2015)
Zhixiang Eddie Xu, Matt J. Kusner, Kilian Q. Weinberger, Minmin Chen, Olivier Chapelle
Classifier cascades and trees for minimizing feature evaluation cost. J. Mach. Learn. Res. 15 (1) (2014)
Laurens van der Maaten, Minmin Chen, Stephen Tyree, Kilian Q. Weinberger
Marginalizing Corrupted Features. CoRR (2014)
Minmin Chen, Kilian Q. Weinberger, Fei Sha, Yoshua Bengio
Marginalized Denoising Auto-encoders for Nonlinear Representations. ICML (2014)
Zhixiang Eddie Xu, Matt J. Kusner, Kilian Q. Weinberger, Minmin Chen
Cost-Sensitive Tree of Classifiers. ICML (1) (2013)
Zhixiang Eddie Xu, Minmin Chen, Kilian Q. Weinberger, Fei Sha
An alternative text representation to TF-IDF and Bag-of-Words CoRR (2013)
Minmin Chen, Alice X. Zheng, Kilian Q. Weinberger
Fast Image Tagging. ICML (3) (2013)
Laurens van der Maaten, Minmin Chen, Stephen Tyree, Kilian Q. Weinberger
Learning with Marginalized Corrupted Features. ICML (1) (2013)
Minmin Chen, Zhixiang Eddie Xu, Kilian Q. Weinberger, Fei Sha
Marginalized Denoising Autoencoders for Domain Adaptation CoRR (2012)
Minmin Chen, Zhixiang Eddie Xu, Kilian Q. Weinberger, Fei Sha
Marginalized Denoising Autoencoders for Domain Adaptation. ICML (2012)
Minmin Chen, Zhixiang Eddie Xu, Kilian Q. Weinberger, Olivier Chapelle, Dor Kedem
Classifier Cascade for Minimizing Feature Evaluation Cost. AISTATS (2012)
Zhixiang Eddie Xu, Matt J. Kusner, Kilian Q. Weinberger, Minmin Chen
Cost-Sensitive Tree of Classifiers CoRR (2012)
Zhixiang Eddie Xu, Minmin Chen, Kilian Q. Weinberger, Fei Sha
From sBoW to dCoT marginalized encoders for text representation. CIKM (2012)
Minmin Chen, Jian-Tao Sun, Xiaochuan Ni, Yixin Chen
Improving context-aware query classification via adaptive self-training. CIKM (2011)
Yi Mao, Yixin Chen, Gregory Hackmann, Minmin Chen, Chenyang Lu, Marin Kollef, Thomas C. Bailey
Medical Data Mining for Early Deterioration Warning in General Hospital Wards. ICDM Workshops (2011)
Minmin Chen, Kilian Q. Weinberger, John Blitzer
Co-Training for Domain Adaptation. NIPS (2011)
Minmin Chen, Kilian Q. Weinberger, Yixin Chen
Automatic Feature Decomposition for Single View Co-training. ICML (2011)
Yi Mao, Yixin Chen, Gregory Hackmann, Minmin Chen, Chenyang Lu, Marin Kollef, Thomas C. Bailey
Early Deterioration Warning for Hospitalized Patients by Mining Clinical Data. Int. J. Knowl. Discov. Bioinform. 2 (3) (2011)
Yixin Chen, Minmin Chen
Extended duality for nonlinear programming. Comput. Optim. Appl. 47 (1) (2010)
Minmin Chen, Yixin Chen, Michael R. Brent, Aaron E. Tenney
Gradient-Based Feature Selection for Conditional Random Fields and its Applications in Computational Genetics. ICTAI (2009)
Minmin Chen, Yixin Chen, Michael R. Brent, Aaron E. Tenney
Constrained optimization for validation-guided conditional random field learning. KDD (2009)
Minmin Chen, Yixin Chen, Michael R. Brent
CRF-OPT: An Efficient High-Quality Conditional Random Field Solver. AAAI (2008)