Xutong Liu

Orcid: 0000-0002-8628-5873

Affiliations:
  • Chinese University of Hong Kong, Hong Kong


According to our database1, Xutong Liu authored at least 25 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2024
Conversational Recommendation With Online Learning and Clustering on Misspecified Users.
IEEE Trans. Knowl. Data Eng., December, 2024

Combinatorial Logistic Bandits.
CoRR, 2024

Stochastic Bandits Robust to Adversarial Attacks.
CoRR, 2024

Cost-Effective Online Multi-LLM Selection with Versatile Reward Models.
CoRR, 2024

AxiomVision: Accuracy-Guaranteed Adaptive Visual Model Selection for Perspective-Aware Video Analytics.
Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024

Learning Context-Aware Probabilistic Maximum Coverage Bandits: A Variance-Adaptive Approach.
Proceedings of the IEEE INFOCOM 2024, 2024

Quantum Algorithm for Online Exp-concave Optimization.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Combinatorial Multivariant Multi-Armed Bandits with Applications to Episodic Reinforcement Learning and Beyond.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Federated Contextual Cascading Bandits with Asynchronous Communication and Heterogeneous Users.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Learning With Guarantee Via Constrained Multi-Armed Bandit: Theory and Network Applications.
IEEE Trans. Mob. Comput., September, 2023

Contextual Combinatorial Bandits with Probabilistically Triggered Arms.
CoRR, 2023

Exploration for Free: How Does Reward Heterogeneity Improve Regret in Cooperative Multi-agent Bandits?
Proceedings of the Uncertainty in Artificial Intelligence, 2023

Online Clustering of Bandits with Misspecified User Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Variance-Adaptive Algorithm for Probabilistic Maximum Coverage Bandits with General Feedback.
Proceedings of the IEEE INFOCOM 2023, 2023

Contextual Combinatorial Bandits with Probabilistically Triggered Arms.
Proceedings of the International Conference on Machine Learning, 2023

Achieving Near-Optimal Individual Regret & Low Communications in Multi-Agent Bandits.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

On-Demand Communication for Asynchronous Multi-Agent Bandits.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Efficient Explorative Key-Term Selection Strategies for Conversational Contextual Bandits.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Federated online clustering of bandits.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

Batch-Size Independent Regret Bounds for Combinatorial Semi-Bandits with Probabilistically Triggered Arms or Independent Arms.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Online Competitive Influence Maximization.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Learning to count: A deep learning framework for graphlet count estimation.
Netw. Sci., October, 2021

Multi-layered Network Exploration via Random Walks: From Offline Optimization to Online Learning.
Proceedings of the 38th International Conference on Machine Learning, 2021

2018
Graphlet Count Estimation via Convolutional Neural Networks.
CoRR, 2018

An Online Learning Approach to Network Application Optimization with Guarantee.
Proceedings of the 2018 IEEE Conference on Computer Communications, 2018


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