Qingyun Wu

Orcid: 0000-0003-1008-516X

According to our database1, Qingyun Wu authored at least 46 papers between 2016 and 2024.

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Bibliography

2024
Embodied LLM Agents Learn to Cooperate in Organized Teams.
CoRR, 2024

StateFlow: Enhancing LLM Task-Solving through State-Driven Workflows.
CoRR, 2024

AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks.
CoRR, 2024

Training Language Model Agents without Modifying Language Models.
CoRR, 2024

Towards better Human-Agent Alignment: Assessing Task Utility in LLM-Powered Applications.
CoRR, 2024

2023
Coreset Selection with Prioritized Multiple Objectives.
CoRR, 2023

IDEAL: Influence-Driven Selective Annotations Empower In-Context Learners in Large Language Models.
CoRR, 2023

Adversarial Attacks on Combinatorial Multi-Armed Bandits.
CoRR, 2023

AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation Framework.
CoRR, 2023

An Empirical Study on Challenging Math Problem Solving with GPT-4.
CoRR, 2023

HyperTime: Hyperparameter Optimization for Combating Temporal Distribution Shifts.
CoRR, 2023

Unified Off-Policy Learning to Rank: a Reinforcement Learning Perspective.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Multi-Fidelity Multi-Armed Bandits Revisited.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Targeted Hyperparameter Optimization with Lexicographic Preferences Over Multiple Objectives.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Forbidden Transactions and Black Markets.
Math. Oper. Res., November, 2022

Dynamic matching with teams.
Oper. Res. Lett., 2022

Provably Efficient Reinforcement Learning for Online Adaptive Influence Maximization.
CoRR, 2022

Automated Machine Learning & Tuning with FLAML.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

2021
Seamlessly Unifying Attributes and Items: Conversational Recommendation for Cold-start Users.
ACM Trans. Inf. Syst., 2021

Fair AutoML.
CoRR, 2021

When and Whom to Collaborate with in a Changing Environment: A Collaborative Dynamic Bandit Solution.
Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

FLAML: A Fast and Lightweight AutoML Library.
Proceedings of Machine Learning and Systems 2021, 2021

ChaCha for Online AutoML.
Proceedings of the 38th International Conference on Machine Learning, 2021

Economic Hyperparameter Optimization with Blended Search Strategy.
Proceedings of the 9th International Conference on Learning Representations, 2021

Unifying Clustered and Non-stationary Bandits.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Frugal Optimization for Cost-related Hyperparameters.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Entering classes in the college admissions model.
Games Econ. Behav., 2020

Fast Distributed Bandits for Online Recommendation Systems.
CoRR, 2020

Cost Effective Optimization for Cost-related Hyperparameters.
CoRR, 2020

Estimation-Action-Reflection: Towards Deep Interaction Between Conversational and Recommender Systems.
Proceedings of the WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, 2020

Global and Local Differential Privacy for Collaborative Bandits.
Proceedings of the RecSys 2020: Fourteenth ACM Conference on Recommender Systems, 2020

Learning by Exploration: New Challenges in Real-World Environments.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Fast distributed bandits for online recommendation systems.
Proceedings of the ICS '20: 2020 International Conference on Supercomputing, 2020

2019
FLO: Fast and Lightweight Hyperparameter Optimization for AutoML.
CoRR, 2019

The data analysis of roughness extraction of target topography using minimum median plane fitting method.
Clust. Comput., 2019

Dynamic Ensemble of Contextual Bandits to Satisfy Users' Changing Interests.
Proceedings of the World Wide Web Conference, 2019

Variance Reduction in Gradient Exploration for Online Learning to Rank.
Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2019

Factorization Bandits for Online Influence Maximization.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

2018
Three-Dimensional Reconstruction of Target Self-Calibrating System with Nonlinear Optimization Technique.
Int. J. Pattern Recognit. Artif. Intell., 2018

The lattice of envy-free matchings.
Games Econ. Behav., 2018

Learning Contextual Bandits in a Non-stationary Environment.
Proceedings of the 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, 2018

Bandit Learning with Implicit Feedback.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017
Returning is Believing: Optimizing Long-term User Engagement in Recommender Systems.
Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017

Factorization Bandits for Interactive Recommendation.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Contextual Bandits in a Collaborative Environment.
Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval, 2016

Learning Hidden Features for Contextual Bandits.
Proceedings of the 25th ACM International Conference on Information and Knowledge Management, 2016


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