CRF-OPT: An Efficient High-Quality Conditional Random Field Solver. - Minmin Chen; Yixin Chen 001; Michael R. Brent (AAAI, 2008)

Gradient-Based Feature Selection for Conditional Random Fields and its Applications in Computational Genetics. - Minmin Chen; Yixin Chen 001; Michael R. Brent; Aaron E. Tenney (ICTAI, 2009)

Constrained optimization for validation-guided conditional random field learning. - Minmin Chen; Yixin Chen 001; Michael R. Brent; Aaron E. Tenney (KDD, 2009)

Extended duality for nonlinear programming. - Yixin Chen 001; Minmin Chen (Comput. Optim. Appl., 2010)

Improving context-aware query classification via adaptive self-training. - Minmin Chen; Jian-Tao Sun; Xiaochuan Ni 001; Yixin Chen 001 (CIKM, 2011)

Medical Data Mining for Early Deterioration Warning in General Hospital Wards. - Yi Mao; Yixin Chen 001; Gregory Hackmann; Minmin Chen; Chenyang Lu 001; Marin Kollef; Thomas C. Bailey (ICDM Workshops, 2011)

Automatic Feature Decomposition for Single View Co-training. - Minmin Chen; Kilian Q. Weinberger; Yixin Chen 001 (ICML, 2011)

Co-Training for Domain Adaptation. - Minmin Chen; Kilian Q. Weinberger; John Blitzer (NIPS, 2011)

Early Deterioration Warning for Hospitalized Patients by Mining Clinical Data. - Yi Mao; Yixin Chen 001; Gregory Hackmann; Minmin Chen; Chenyang Lu 001; Marin Kollef; Thomas C. Bailey (Int. J. Knowl. Discov. Bioinform., 2011)

From sBoW to dCoT marginalized encoders for text representation. - Zhixiang Eddie Xu; Minmin Chen; Kilian Q. Weinberger; Fei Sha (CIKM, 2012)

Marginalized Denoising Autoencoders for Domain Adaptation. - Minmin Chen; Zhixiang Eddie Xu; Kilian Q. Weinberger; Fei Sha (ICML, 2012)

Classifier Cascade for Minimizing Feature Evaluation Cost. - Minmin Chen; Zhixiang Eddie Xu; Kilian Q. Weinberger; Olivier Chapelle; Dor Kedem (AISTATS, 2012)

Fast Image Tagging. - Minmin Chen; Alice X. Zheng; Kilian Q. Weinberger (ICML (3), 2013)

Learning with Marginalized Corrupted Features. - Laurens van der Maaten; Minmin Chen; Stephen Tyree; Kilian Q. Weinberger (ICML (1), 2013)

Cost-Sensitive Tree of Classifiers. - Zhixiang Eddie Xu; Matt J. Kusner; Kilian Q. Weinberger; Minmin Chen (ICML (1), 2013)

An alternative text representation to TF-IDF and Bag-of-Words - Zhixiang Eddie Xu; Minmin Chen; Kilian Q. Weinberger; Fei Sha (CoRR, 2013)

Marginalized Denoising Auto-encoders for Nonlinear Representations. - Minmin Chen; Kilian Q. Weinberger; Fei Sha; Yoshua Bengio (ICML, 2014)

Marginalizing Corrupted Features. - Laurens van der Maaten; Minmin Chen; Stephen Tyree; Kilian Q. Weinberger (CoRR, 2014)

Classifier cascades and trees for minimizing feature evaluation cost. - Zhixiang Eddie Xu; Matt J. Kusner; Kilian Q. Weinberger; Minmin Chen; Olivier Chapelle (J. Mach. Learn. Res., 2014)

Marginalized Denoising for Link Prediction and Multi-Label Learning. - Zheng Chen; Minmin Chen; Kilian Q. Weinberger; Weixiong Zhang (AAAI, 2015)

Marginalizing stacked linear denoising autoencoders. - Minmin Chen; Kilian Q. Weinberger; Zhixiang Eddie Xu; Fei Sha (J. Mach. Learn. Res., 2015)

Efficient Vector Representation for Documents through Corruption. - Minmin Chen (ICLR (Poster), 2017)

MinimalRNN: Toward More Interpretable and Trainable Recurrent Neural Networks. - Minmin Chen (CoRR, 2017)

Dynamical Isometry and a Mean Field Theory of RNNs: Gating Enables Signal Propagation in Recurrent Neural Networks. - Minmin Chen; Jeffrey Pennington; Samuel S. Schoenholz (ICML, 2018)

Categorical-attributes-based item classification for recommender systems. - Qian Zhao; Jilin Chen; Minmin Chen; Sagar Jain; Alex Beutel; Francois Belletti; Ed H. Chi (RecSys, 2018)

AntisymmetricRNN: A Dynamical System View on Recurrent Neural Networks. - Bo Chang 002; Minmin Chen; Eldad Haber; Ed H. Chi (ICLR (Poster), 2019)

Quantifying Long Range Dependence in Language and User Behavior to improve RNNs. - Francois Belletti; Minmin Chen; Ed H. Chi (KDD, 2019)

Surrogate Objectives for Batch Policy Optimization in One-step Decision Making. - Minmin Chen; Ramki Gummadi; Chris Harris 001; Dale Schuurmans (NeurIPS, 2019)

EstImAgg: A Learning Framework for Groupwise Aggregated Data. - Avradeep Bhowmik; Minmin Chen; Zhengming Xing; Suju Rajan (SDM, 2019)

Top-K Off-Policy Correction for a REINFORCE Recommender System. - Minmin Chen; Alex Beutel; Paul Covington; Sagar Jain; Francois Belletti; Ed H. Chi (WSDM, 2019)

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 (WWW, 2019)

Dynamical Isometry and a Mean Field Theory of LSTMs and GRUs. - Dar Gilboa; Bo Chang 002; Minmin Chen; Greg Yang; Samuel S. Schoenholz; Ed H. Chi; Jeffrey Pennington (CoRR, 2019)

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 (RecSys, 2020)

Off-policy Learning in Two-stage Recommender Systems. - Jiaqi Ma 001; Zhe Zhao 001; Xinyang Yi; Ji Yang; Minmin Chen; Jiaxi Tang; Lichan Hong; Ed H. Chi (WWW, 2020)

Batch Reinforcement Learning Through Continuation Method. - Yijie Guo; Shengyu Feng; Nicolas Le Roux; Ed H. Chi; Honglak Lee; Minmin Chen (ICLR, 2021)

Exploration in Recommender Systems. - Minmin Chen (RecSys, 2021)

Values of User Exploration in Recommender Systems. - Minmin Chen; Yuyan Wang; Can Xu; Ya Le; Mohit Sharma 002; Lee Richardson; Su-Lin Wu; Ed H. Chi (RecSys, 2021)

User Response Models to Improve a REINFORCE Recommender System. - Minmin Chen; Bo Chang 002; Can Xu; Ed H. Chi (WSDM, 2021)

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 (WWW, 2021)

Surrogate for Long-Term User Experience in Recommender Systems. - Yuyan Wang; Mohit Sharma 002; Can Xu; Sriraj Badam; Qian Sun 005; Lee Richardson; Lisa Chung; Ed H. Chi; Minmin Chen (KDD, 2022)

Off-Policy Actor-critic for Recommender Systems. - Minmin Chen; Can Xu; Vince Gatto; Devanshu Jain; Aviral Kumar; Ed H. Chi (RecSys, 2022)

Learning to Augment for Casual User Recommendation. - Jianling Wang; Ya Le; Bo Chang 002; Yuyan Wang; Ed H. Chi; Minmin Chen (WWW, 2022)

Recency Dropout for Recurrent Recommender Systems. - Bo Chang 002; Can Xu; Matthieu Lê; Jingchen Feng; Ya Le; Sriraj Badam; Ed H. Chi; Minmin Chen (CoRR, 2022)

Reward Shaping for User Satisfaction in a REINFORCE Recommender. - 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; et al. (CoRR, 2022)

Incentivized self-rebalancing fleet in electric vehicle sharing. - Yuguang Wu; Minmin Chen; Xin Wang (IISE Trans., 2022)

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; et al. (KDD, 2023)

Towards Companion Recommenders Assisting Users' Long-Term Journeys. - Konstantina Christakopoulou; Minmin Chen (RecSys, 2023)

Nonlinear Bandits Exploration for Recommendations. - Yi Su 008; Minmin Chen (RecSys, 2023)

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 (RecSys, 2023)

Latent User Intent Modeling for Sequential Recommenders. - Bo Chang 002; Alexandros Karatzoglou; Yuyan Wang; Can Xu; Ed H. Chi; Minmin Chen (WWW (Companion Volume), 2023)

Investigating Action-Space Generalization in Reinforcement Learning for Recommendation Systems. - Abhishek Naik; Bo Chang 002; Alexandros Karatzoglou; Martin Mladenov; Ed H. Chi; Minmin Chen (WWW (Companion Volume), 2023)

Value of Exploration: Measurements, Findings and Algorithms. - Yi Su 008; Xiangyu Wang; Elaine Ya Le; Liang Liu 017; Yuening Li; Haokai Lu; Benjamin Lipshitz; Sriraj Badam; Lukasz Heldt; Shuchao Bi; Ed H. Chi; Cristos Goodrow; et al. (CoRR, 2023)

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; et al. (CoRR, 2023)

Prompt Tuning Large Language Models on Personalized Aspect Extraction for Recommendations. - Pan Li; Yuyan Wang; Ed H. Chi; Minmin Chen (CoRR, 2023)

Hierarchical Reinforcement Learning for Modeling User Novelty-Seeking Intent in Recommender Systems. - Pan Li; Yuyan Wang; Ed H. Chi; Minmin Chen (CoRR, 2023)

Correction with Backtracking Reduces Hallucination in Summarization. - Zhenzhen Liu; Chao Wan; Varsha Kishore; Jin Peng Zhou; Minmin Chen; Kilian Q. Weinberger (CoRR, 2023)

Exploration: Measurements and Systems. - Minmin Chen (ICTIR, 2024)

TSMO 2024: Two-sided Marketplace Optimization. - Mihajlo Grbovic; Vladan Radosavljevic; Minmin Chen; Katerina Iliakopoulou-Zanos; Thanasis Noulas; Amit Goyal; Fabrizio Silvestri (KDD, 2024)

Multi-Task Neural Linear Bandit for Exploration in Recommender Systems. - Yi Su 008; Haokai Lu; Yuening Li; Liang Liu 017; Shuchao Bi; Ed H. Chi; Minmin Chen (KDD, 2024)

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 (RecSys, 2024)

Long-Term Value of Exploration: Measurements, Findings and Algorithms. - Yi Su 008; Xiangyu Wang; Elaine Ya Le; Liang Liu 017; Yuening Li; Haokai Lu; Benjamin Lipshitz; Sriraj Badam; Lukasz Heldt; Shuchao Bi; Ed H. Chi; Cristos Goodrow; et al. (WSDM, 2024)

Fresh Content Recommendation at Scale: A Multi-funnel Solution and the Potential of LLMs. - Jianling Wang; Haokai Lu; Minmin Chen (WSDM, 2024)

Cluster Anchor Regularization to Alleviate Popularity Bias in Recommender Systems. - Bo Chang 002; Changping Meng; He Ma; Shuo Chang; Yang Gu; Yajun Peng; Jingchen Feng; Yaping Zhang; Shuchao Bi; Ed H. Chi; Minmin Chen (WWW (Companion Volume), 2024)

Large Language Models as Data Augmenters for Cold-Start Item Recommendation. - Jianling Wang; Haokai Lu; James Caverlee; Ed H. Chi; Minmin Chen (WWW (Companion Volume), 2024)

Diversifying by Intent in Recommender Systems. - Yuyan Wang; Cheenar Banerjee; Samer Chucri; Fabio Soldo; Sriraj Badam; Ed H. Chi; Minmin Chen (CoRR, 2024)

LLMs for User Interest Exploration: A Hybrid Approach. - 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 (CoRR, 2024)

NATURAL PLAN: Benchmarking LLMs on Natural Language Planning. - 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 (CoRR, 2024)

EVOLvE: Evaluating and Optimizing LLMs For Exploration. - Allen Nie; Yi Su 008; Bo Chang 002; Jonathan N. Lee; Ed H. Chi; Quoc V. Le; Minmin Chen (CoRR, 2024)

Beyond Item Dissimilarities: Diversifying by Intent in Recommender Systems. - Yuyan Wang; Cheenar Banerjee; Samer Chucri; Fabio Soldo; Sriraj Badam; Ed H. Chi; Minmin Chen (KDD (1), 2025)

The Blessing of Reasoning: LLM-Based Contrastive Explanations in Black-Box Recommender Systems. - Yuyan Wang; Pan Li; Minmin Chen (CoRR, 2025)

Conversational Planning for Personal Plans. - Konstantina Christakopoulou; Iris Qu; John Canny; Andrew Goodridge; Cj Adams; Minmin Chen; Maja J. Mataric (CoRR, 2025)

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; et al. (CoRR, 2025)

Serendipitous Recommendation with Multimodal LLM. - Haoting Wang; Jianling Wang; Hao Li; Fangjun Yi; Mengyu Fu; Youwei Zhang; Yifan Liu; Liang Liu 017; Minmin Chen; Ed H. Chi; Lichan Hong; Haokai Lu (CoRR, 2025)

Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities. - Gheorghe Comanici; Eric Bieber; Mike Schaekermann; Ice Pasupat; Noveen Sachdeva; Inderjit S. Dhillon; Marcel Blistein; Ori Ram; Dan Zhang; Evan Rosen; Luke Marris; Sam Petulla; et al. (CoRR, 2025)