Minmin Chen

According to our database1, Minmin Chen authored at least 57 papers between 2008 and 2024.

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Bibliography

2024
Large Language Models as Data Augmenters for Cold-Start Item Recommendation.
CoRR, 2024

2023
Correction with Backtracking Reduces Hallucination in Summarization.
CoRR, 2023

Hierarchical Reinforcement Learning for Modeling User Novelty-Seeking Intent in Recommender Systems.
CoRR, 2023

Prompt Tuning Large Language Models on Personalized Aspect Extraction for Recommendations.
CoRR, 2023

Large Language Models for User Interest Journeys.
CoRR, 2023

Value of Exploration: Measurements, Findings and Algorithms.
CoRR, 2023

Investigating Action-Space Generalization in Reinforcement Learning for Recommendation Systems.
Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

Latent User Intent Modeling for Sequential Recommenders.
Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

Online Matching: A Real-time Bandit System for Large-scale Recommendations.
Proceedings of the 17th ACM Conference on Recommender Systems, 2023

Nonlinear Bandits Exploration for Recommendations.
Proceedings of the 17th ACM Conference on Recommender Systems, 2023

Towards Companion Recommenders Assisting Users' Long-Term Journeys.
Proceedings of the 17th ACM Conference on Recommender Systems, 2023

Fresh Content Needs More Attention: Multi-funnel Fresh Content Recommendation.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

2022
Incentivized self-rebalancing fleet in electric vehicle sharing.
IISE Trans., 2022

Reward Shaping for User Satisfaction in a REINFORCE Recommender.
CoRR, 2022

Recency Dropout for Recurrent Recommender Systems.
CoRR, 2022

Learning to Augment for Casual User Recommendation.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Off-Policy Actor-critic for Recommender Systems.
Proceedings of the RecSys '22: Sixteenth ACM Conference on Recommender Systems, Seattle, WA, USA, September 18, 2022

Surrogate for Long-Term User Experience in Recommender Systems.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

2021
Towards Content Provider Aware Recommender Systems: A Simulation Study on the Interplay between User and Provider Utilities.
Proceedings of the WWW '21: The Web Conference 2021, 2021

User Response Models to Improve a REINFORCE Recommender System.
Proceedings of the WSDM '21, 2021

Values of User Exploration in Recommender Systems.
Proceedings of the RecSys '21: Fifteenth ACM Conference on Recommender Systems, Amsterdam, The Netherlands, 27 September 2021, 2021

Exploration in Recommender Systems.
Proceedings of the RecSys '21: Fifteenth ACM Conference on Recommender Systems, Amsterdam, The Netherlands, 27 September 2021, 2021

Batch Reinforcement Learning Through Continuation Method.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
Off-policy Learning in Two-stage Recommender Systems.
Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020

Deconfounding User Satisfaction Estimation from Response Rate Bias.
Proceedings of the RecSys 2020: Fourteenth ACM Conference on Recommender Systems, 2020

2019
Dynamical Isometry and a Mean Field Theory of LSTMs and GRUs.
CoRR, 2019

Towards Neural Mixture Recommender for Long Range Dependent User Sequences.
Proceedings of the World Wide Web Conference, 2019

Top-K Off-Policy Correction for a REINFORCE Recommender System.
Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining, 2019

EstImAgg: A Learning Framework for Groupwise Aggregated Data.
Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

Surrogate Objectives for Batch Policy Optimization in One-step Decision Making.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Quantifying Long Range Dependence in Language and User Behavior to improve RNNs.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

AntisymmetricRNN: A Dynamical System View on Recurrent Neural Networks.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
Categorical-attributes-based item classification for recommender systems.
Proceedings of the 12th ACM Conference on Recommender Systems, 2018

Dynamical Isometry and a Mean Field Theory of RNNs: Gating Enables Signal Propagation in Recurrent Neural Networks.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
MinimalRNN: Toward More Interpretable and Trainable Recurrent Neural Networks.
CoRR, 2017

Efficient Vector Representation for Documents through Corruption.
Proceedings of the 5th International Conference on Learning Representations, 2017

2015
Marginalizing stacked linear denoising autoencoders.
J. Mach. Learn. Res., 2015

Marginalized Denoising for Link Prediction and Multi-Label Learning.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
Classifier cascades and trees for minimizing feature evaluation cost.
J. Mach. Learn. Res., 2014

Marginalizing Corrupted Features.
CoRR, 2014

Marginalized Denoising Auto-encoders for Nonlinear Representations.
Proceedings of the 31th International Conference on Machine Learning, 2014

2013
An alternative text representation to TF-IDF and Bag-of-Words
CoRR, 2013

Cost-Sensitive Tree of Classifiers.
Proceedings of the 30th International Conference on Machine Learning, 2013

Learning with Marginalized Corrupted Features.
Proceedings of the 30th International Conference on Machine Learning, 2013

Fast Image Tagging.
Proceedings of the 30th International Conference on Machine Learning, 2013

2012
Classifier Cascade for Minimizing Feature Evaluation Cost.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Marginalized Denoising Autoencoders for Domain Adaptation.
Proceedings of the 29th International Conference on Machine Learning, 2012

From sBoW to dCoT marginalized encoders for text representation.
Proceedings of the 21st ACM International Conference on Information and Knowledge Management, 2012

2011
Early Deterioration Warning for Hospitalized Patients by Mining Clinical Data.
Int. J. Knowl. Discov. Bioinform., 2011

Co-Training for Domain Adaptation.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Automatic Feature Decomposition for Single View Co-training.
Proceedings of the 28th International Conference on Machine Learning, 2011

Medical Data Mining for Early Deterioration Warning in General Hospital Wards.
Proceedings of the Data Mining Workshops (ICDMW), 2011

Improving context-aware query classification via adaptive self-training.
Proceedings of the 20th ACM Conference on Information and Knowledge Management, 2011

2010
Extended duality for nonlinear programming.
Comput. Optim. Appl., 2010

2009
Constrained optimization for validation-guided conditional random field learning.
Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 28, 2009

Gradient-Based Feature Selection for Conditional Random Fields and its Applications in Computational Genetics.
Proceedings of the ICTAI 2009, 2009

2008
CRF-OPT: An Efficient High-Quality Conditional Random Field Solver.
Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 2008


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