Minmin Chen

92 papers A* 19A 18B 1Misc 1Journal 38Unranked 15
YearRankTypeTitle / Venue / Authors
2025 — conf
Beyond Item Dissimilarities: Diversifying by Intent in Recommender Systems.
KDD (1)
Yuyan Wang, Cheenar Banerjee, Samer Chucri, Fabio Soldo, Sriraj Badam, Ed H. Chi, Minmin Chen
2025 J jnl
Conversational Planning for Personal Plans.
CoRR
Konstantina Christakopoulou, Iris Qu, John Canny, Andrew Goodridge, Cj Adams, Minmin Chen, Maja J. Mataric
2025 A* conf
EVOLvE: Evaluating and Optimizing LLMs For In-Context Exploration.
ICML
Allen Nie, Yi Su, Bo Chang, Jonathan Lee, Ed H. Chi, Quoc V. Le, Minmin Chen
2025 — conf
Reward Shaping for User Satisfaction.
ECML/PKDD (6)
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
2025 J jnl
Serendipitous Recommendation with Multimodal LLM.
CoRR
Haoting Wang, Jianling Wang, Hao Li, Fangjun Yi, Mengyu Fu, Youwei Zhang, Yifan Liu, Liang Liu, Minmin Chen, Ed H. Chi, Lichan Hong, Haokai Lu
2025 — conf
TSMO 2025: Two-sided Marketplace Optimization: Search, Discovery, Matching, Pricing & Growth.
KDD (2)
Mihajlo Grbovic, Vladan Radosavljevic, Amit Goyal, Rui Song, Minmin Chen, Zhiwei Qin, Katerina Iliakopoulou-Zanos, Thanasis Noulas, Hongtu Zhu, Fabrizio Silvestri
2025 J jnl
The Blessing of Reasoning: LLM-Based Contrastive Explanations in Black-Box Recommender Systems.
CoRR
Yuyan Wang, Pan Li, Minmin Chen
2025 — conf
User Feedback Alignment for LLM-powered Exploration in Large-scale Recommendation Systems.
ACL (6)
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 J jnl
User Feedback Alignment for LLM-powered Exploration in Large-scale Recommendation Systems.
CoRR
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
2024 — conf
Cluster Anchor Regularization to Alleviate Popularity Bias in Recommender Systems.
WWW (Companion Volume)
Bo Chang, Changping Meng, He Ma, Shuo Chang, Yang Gu, Yajun Peng, Jingchen Feng, Yaping Zhang, Shuchao Bi, Ed H. Chi, Minmin Chen
2024 J jnl
Diversifying by Intent in Recommender Systems.
CoRR
Yuyan Wang, Cheenar Banerjee, Samer Chucri, Fabio Soldo, Sriraj Badam, Ed H. Chi, Minmin Chen
2024 J jnl
EVOLvE: Evaluating and Optimizing LLMs For Exploration.
CoRR
Allen Nie, Yi Su, Bo Chang, Jonathan N. Lee, Ed H. Chi, Quoc V. Le, Minmin Chen
2024 Misc conf
Exploration: Measurements and Systems.
ICTIR
Minmin Chen
2024 A conf
Fresh Content Recommendation at Scale: A Multi-funnel Solution and the Potential of LLMs.
WSDM
Jianling Wang, Haokai Lu, Minmin Chen
2024 A conf
LLMs for User Interest Exploration in Large-scale Recommendation Systems.
RecSys
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 J jnl
LLMs for User Interest Exploration: A Hybrid Approach.
CoRR
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 — conf
Large Language Models as Data Augmenters for Cold-Start Item Recommendation.
WWW (Companion Volume)
Jianling Wang, Haokai Lu, James Caverlee, Ed H. Chi, Minmin Chen
2024 J jnl
Large Language Models as Data Augmenters for Cold-Start Item Recommendation.
CoRR
Jianling Wang, Haokai Lu, James Caverlee, Ed H. Chi, Minmin Chen
2024 A conf
Long-Term Value of Exploration: Measurements, Findings and Algorithms.
WSDM
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 A* conf
Multi-Task Neural Linear Bandit for Exploration in Recommender Systems.
KDD
Yi Su, Haokai Lu, Yuening Li, Liang Liu, Shuchao Bi, Ed H. Chi, Minmin Chen
2024 J jnl
NATURAL PLAN: Benchmarking LLMs on Natural Language Planning.
CoRR
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
2024 A* conf
TSMO 2024: Two-sided Marketplace Optimization.
KDD
Mihajlo Grbovic, Vladan Radosavljevic, Minmin Chen, Katerina Iliakopoulou-Zanos, Thanasis Noulas, Amit Goyal, Fabrizio Silvestri
2023 J jnl
Correction with Backtracking Reduces Hallucination in Summarization.
CoRR
Zhenzhen Liu, Chao Wan, Varsha Kishore, Jin Peng Zhou, Minmin Chen, Kilian Q. Weinberger
2023 A* conf
Fresh Content Needs More Attention: Multi-funnel Fresh Content Recommendation.
KDD
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 J jnl
Fresh Content Needs More Attention: Multi-funnel Fresh Content Recommendation.
CoRR
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
2023 J jnl
Hierarchical Reinforcement Learning for Modeling User Novelty-Seeking Intent in Recommender Systems.
CoRR
Pan Li, Yuyan Wang, Ed H. Chi, Minmin Chen
2023 — conf
Investigating Action-Space Generalization in Reinforcement Learning for Recommendation Systems.
WWW (Companion Volume)
Abhishek Naik, Bo Chang, Alexandros Karatzoglou, Martin Mladenov, Ed H. Chi, Minmin Chen
2023 J jnl
Large Language Models for User Interest Journeys.
CoRR
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
2023 — conf
Latent User Intent Modeling for Sequential Recommenders.
WWW (Companion Volume)
Bo Chang, Alexandros Karatzoglou, Yuyan Wang, Can Xu, Ed H. Chi, Minmin Chen
2023 A conf
Nonlinear Bandits Exploration for Recommendations.
RecSys
Yi Su, Minmin Chen
2023 A conf
Online Matching: A Real-time Bandit System for Large-scale Recommendations.
RecSys
Xinyang Yi, Shao-Chuan Wang, Ruining He, Hariharan Chandrasekaran, Charles Wu, Lukasz Heldt, Lichan Hong, Minmin Chen, Ed H. Chi
2023 J jnl
Online Matching: A Real-time Bandit System for Large-scale Recommendations.
CoRR
Xinyang Yi, Shao-Chuan Wang, Ruining He, Hariharan Chandrasekaran, Charles Wu, Lukasz Heldt, Lichan Hong, Minmin Chen, Ed H. Chi
2023 J jnl
Prompt Tuning Large Language Models on Personalized Aspect Extraction for Recommendations.
CoRR
Pan Li, Yuyan Wang, Ed H. Chi, Minmin Chen
2023 A conf
Towards Companion Recommenders Assisting Users' Long-Term Journeys.
RecSys
Konstantina Christakopoulou, Minmin Chen
2023 J jnl
Value of Exploration: Measurements, Findings and Algorithms.
CoRR
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
2022 A conf
Exploration in Recommender Systems.
WSDM
Minmin Chen
2022 J jnl
Incentivized self-rebalancing fleet in electric vehicle sharing.
IISE Trans.
Yuguang Wu, Minmin Chen, Xin Wang
2022 J jnl
Latent User Intent Modeling for Sequential Recommenders.
CoRR
Bo Chang, Alexandros Karatzoglou, Yuyan Wang, Can Xu, Ed H. Chi, Minmin Chen
2022 A* conf
Learning to Augment for Casual User Recommendation.
WWW
Jianling Wang, Ya Le, Bo Chang, Yuyan Wang, Ed H. Chi, Minmin Chen
2022 J jnl
Learning to Augment for Casual User Recommendation.
CoRR
Jianling Wang, Ya Le, Bo Chang, Yuyan Wang, Ed H. Chi, Minmin Chen
2022 A conf
Off-Policy Actor-critic for Recommender Systems.
RecSys
Minmin Chen, Can Xu, Vince Gatto, Devanshu Jain, Aviral Kumar, Ed H. Chi
2022 J jnl
Recency Dropout for Recurrent Recommender Systems.
CoRR
Bo Chang, Can Xu, Matthieu Lê, Jingchen Feng, Ya Le, Sriraj Badam, Ed H. Chi, Minmin Chen
2022 J jnl
Reward Shaping for User Satisfaction in a REINFORCE Recommender.
CoRR
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
2022 A* conf
Surrogate for Long-Term User Experience in Recommender Systems.
KDD
Yuyan Wang, Mohit Sharma, Can Xu, Sriraj Badam, Qian Sun, Lee Richardson, Lisa Chung, Ed H. Chi, Minmin Chen
2021 A* conf
Batch Reinforcement Learning Through Continuation Method.
ICLR
Yijie Guo, Shengyu Feng, Nicolas Le Roux, Ed H. Chi, Honglak Lee, Minmin Chen
2021 A conf
Exploration in Recommender Systems.
RecSys
Minmin Chen
2021 A* conf
Towards Content Provider Aware Recommender Systems: A Simulation Study on the Interplay between User and Provider Utilities.
WWW
Ruohan Zhan, Konstantina Christakopoulou, Ya Le, Jayden Ooi, Martin Mladenov, Alex Beutel, Craig Boutilier, Ed H. Chi, Minmin Chen
2021 J jnl
Towards Content Provider Aware Recommender Systems: A Simulation Study on the Interplay between User and Provider Utilities.
CoRR
Ruohan Zhan, Konstantina Christakopoulou, Ya Le, Jayden Ooi, Martin Mladenov, Alex Beutel, Craig Boutilier, Ed H. Chi, Minmin Chen
2021 A conf
User Response Models to Improve a REINFORCE Recommender System.
WSDM
Minmin Chen, Bo Chang, Can Xu, Ed H. Chi
2021 A conf
Values of User Exploration in Recommender Systems.
RecSys
Minmin Chen, Yuyan Wang, Can Xu, Ya Le, Mohit Sharma, Lee Richardson, Su-Lin Wu, Ed H. Chi
2020 A conf
Deconfounding User Satisfaction Estimation from Response Rate Bias.
RecSys
Konstantina Christakopoulou, Madeleine Traverse, Trevor Potter, Emma Marriott, Daniel Li, Chris Haulk, Ed H. Chi, Minmin Chen
2020 A* conf
Off-policy Learning in Two-stage Recommender Systems.
WWW
Jiaqi Ma, Zhe Zhao, Xinyang Yi, Ji Yang, Minmin Chen, Jiaxi Tang, Lichan Hong, Ed H. Chi
2019 — conf
AntisymmetricRNN: A Dynamical System View on Recurrent Neural Networks.
ICLR (Poster)
Bo Chang, Minmin Chen, Eldad Haber, Ed H. Chi
2019 J jnl
AntisymmetricRNN: A Dynamical System View on Recurrent Neural Networks.
CoRR
Bo Chang, Minmin Chen, Eldad Haber, Ed H. Chi
2019 J jnl
Dynamical Isometry and a Mean Field Theory of LSTMs and GRUs.
CoRR
Dar Gilboa, Bo Chang, Minmin Chen, Greg Yang, Samuel S. Schoenholz, Ed H. Chi, Jeffrey Pennington
2019 A conf
EstImAgg: A Learning Framework for Groupwise Aggregated Data.
SDM
Avradeep Bhowmik, Minmin Chen, Zhengming Xing, Suju Rajan
2019 A* conf
Quantifying Long Range Dependence in Language and User Behavior to improve RNNs.
KDD
Francois Belletti, Minmin Chen, Ed H. Chi
2019 J jnl
Quantifying Long Range Dependence in Language and User Behavior to improve RNNs.
CoRR
Francois Belletti, Minmin Chen, Ed H. Chi
2019 A* conf
Surrogate Objectives for Batch Policy Optimization in One-step Decision Making.
NeurIPS
Minmin Chen, Ramki Gummadi, Chris Harris, Dale Schuurmans
2019 A conf
Top-K Off-Policy Correction for a REINFORCE Recommender System.
WSDM
Minmin Chen, Alex Beutel, Paul Covington, Sagar Jain, Francois Belletti, Ed H. Chi
2019 A* conf
Towards Neural Mixture Recommender for Long Range Dependent User Sequences.
WWW
Jiaxi Tang, Francois Belletti, Sagar Jain, Minmin Chen, Alex Beutel, Can Xu, Ed H. Chi
2019 J jnl
Towards Neural Mixture Recommender for Long Range Dependent User Sequences.
CoRR
Jiaxi Tang, Francois Belletti, Sagar Jain, Minmin Chen, Alex Beutel, Can Xu, Ed H. Chi
2018 A conf
Categorical-attributes-based item classification for recommender systems.
RecSys
Qian Zhao, Jilin Chen, Minmin Chen, Sagar Jain, Alex Beutel, Francois Belletti, Ed H. Chi
2018 A* conf
Dynamical Isometry and a Mean Field Theory of RNNs: Gating Enables Signal Propagation in Recurrent Neural Networks.
ICML
Minmin Chen, Jeffrey Pennington, Samuel S. Schoenholz
2018 J jnl
Dynamical Isometry and a Mean Field Theory of RNNs: Gating Enables Signal Propagation in Recurrent Neural Networks.
CoRR
Minmin Chen, Jeffrey Pennington, Samuel S. Schoenholz
2018 J jnl
Top-K Off-Policy Correction for a REINFORCE Recommender System.
CoRR
Minmin Chen, Alex Beutel, Paul Covington, Sagar Jain, Francois Belletti, Ed H. Chi
2017 — conf
Efficient Vector Representation for Documents through Corruption.
ICLR (Poster)
Minmin Chen
2017 J jnl
Efficient Vector Representation for Documents through Corruption.
CoRR
Minmin Chen
2017 J jnl
MinimalRNN: Toward More Interpretable and Trainable Recurrent Neural Networks.
CoRR
Minmin Chen
2015 A* conf
Marginalized Denoising for Link Prediction and Multi-Label Learning.
AAAI
Zheng Chen, Minmin Chen, Kilian Q. Weinberger, Weixiong Zhang
2015 J jnl
Marginalizing stacked linear denoising autoencoders.
J. Mach. Learn. Res.
Minmin Chen, Kilian Q. Weinberger, Zhixiang Eddie Xu, Fei Sha
2014 J jnl
Classifier cascades and trees for minimizing feature evaluation cost.
J. Mach. Learn. Res.
Zhixiang Eddie Xu, Matt J. Kusner, Kilian Q. Weinberger, Minmin Chen, Olivier Chapelle
2014 A* conf
Marginalized Denoising Auto-encoders for Nonlinear Representations.
ICML
Minmin Chen, Kilian Q. Weinberger, Fei Sha, Yoshua Bengio
2014 J jnl
Marginalizing Corrupted Features.
CoRR
Laurens van der Maaten, Minmin Chen, Stephen Tyree, Kilian Q. Weinberger
2013 J jnl
An alternative text representation to TF-IDF and Bag-of-Words
CoRR
Zhixiang Eddie Xu, Minmin Chen, Kilian Q. Weinberger, Fei Sha
2013 — conf
Cost-Sensitive Tree of Classifiers.
ICML (1)
Zhixiang Eddie Xu, Matt J. Kusner, Kilian Q. Weinberger, Minmin Chen
2013 — conf
Fast Image Tagging.
ICML (3)
Minmin Chen, Alice X. Zheng, Kilian Q. Weinberger
2013 — conf
Learning with Marginalized Corrupted Features.
ICML (1)
Laurens van der Maaten, Minmin Chen, Stephen Tyree, Kilian Q. Weinberger
2012 A conf
Classifier Cascade for Minimizing Feature Evaluation Cost.
AISTATS
Minmin Chen, Zhixiang Eddie Xu, Kilian Q. Weinberger, Olivier Chapelle, Dor Kedem
2012 J jnl
Cost-Sensitive Tree of Classifiers
CoRR
Zhixiang Eddie Xu, Matt J. Kusner, Kilian Q. Weinberger, Minmin Chen
2012 A conf
From sBoW to dCoT marginalized encoders for text representation.
CIKM
Zhixiang Eddie Xu, Minmin Chen, Kilian Q. Weinberger, Fei Sha
2012 J jnl
Marginalized Denoising Autoencoders for Domain Adaptation
CoRR
Minmin Chen, Zhixiang Eddie Xu, Kilian Q. Weinberger, Fei Sha
2012 A* conf
Marginalized Denoising Autoencoders for Domain Adaptation.
ICML
Minmin Chen, Zhixiang Eddie Xu, Kilian Q. Weinberger, Fei Sha
2011 A* conf
Automatic Feature Decomposition for Single View Co-training.
ICML
Minmin Chen, Kilian Q. Weinberger, Yixin Chen
2011 — conf
Co-Training for Domain Adaptation.
NIPS
Minmin Chen, Kilian Q. Weinberger, John Blitzer
2011 J jnl
Early Deterioration Warning for Hospitalized Patients by Mining Clinical Data.
Int. J. Knowl. Discov. Bioinform.
Yi Mao, Yixin Chen, Gregory Hackmann, Minmin Chen, Chenyang Lu, Marin Kollef, Thomas C. Bailey
2011 A conf
Improving context-aware query classification via adaptive self-training.
CIKM
Minmin Chen, Jian-Tao Sun, Xiaochuan Ni, Yixin Chen
2011 — conf
Medical Data Mining for Early Deterioration Warning in General Hospital Wards.
ICDM Workshops
Yi Mao, Yixin Chen, Gregory Hackmann, Minmin Chen, Chenyang Lu, Marin Kollef, Thomas C. Bailey
2010 J jnl
Extended duality for nonlinear programming.
Comput. Optim. Appl.
Yixin Chen, Minmin Chen
2009 A* conf
Constrained optimization for validation-guided conditional random field learning.
KDD
Minmin Chen, Yixin Chen, Michael R. Brent, Aaron E. Tenney
2009 B conf
Gradient-Based Feature Selection for Conditional Random Fields and its Applications in Computational Genetics.
ICTAI
Minmin Chen, Yixin Chen, Michael R. Brent, Aaron E. Tenney
2008 A* conf
CRF-OPT: An Efficient High-Quality Conditional Random Field Solver.
AAAI
Minmin Chen, Yixin Chen, Michael R. Brent