no code implementations • 13 Feb 2018 • Ling Pan, Qingpeng Cai, Zhixuan Fang, Pingzhong Tang, Longbo Huang
Different from existing methods that often ignore spatial information and rely heavily on accurate prediction, HRP captures both spatial and temporal dependencies using a divide-and-conquer structure with an embedded localized module.
no code implementations • NeurIPS 2021 • Yihan Du, Siwei Wang, Zhixuan Fang, Longbo Huang
To the best of our knowledge, this is the first work that considers option correlation in risk-aware bandits and explicitly quantifies how arbitrary covariance structures impact the learning performance.
no code implementations • 15 Nov 2021 • Qingsong Liu, Wenfei Wu, Longbo Huang, Zhixuan Fang
In this paper, we develop a novel virtual-queue-based online algorithm for online convex optimization (OCO) problems with long-term and time-varying constraints and conduct a performance analysis with respect to the dynamic regret and constraint violations.
1 code implementation • 30 Aug 2022 • Pihe Hu, Ling Pan, Yu Chen, Zhixuan Fang, Longbo Huang
Multi-user delay constrained scheduling is important in many real-world applications including wireless communication, live streaming, and cloud computing.
no code implementations • 11 May 2023 • Yujie Wang, Chao Huang, Liner Yang, Zhixuan Fang, Yaping Huang, Yang Liu, Erhong Yang
The SES method is designed specifically for sequence labeling tasks.
no code implementations • 14 Dec 2023 • Rongwu Xu, Brian S. Lin, Shujian Yang, Tianqi Zhang, Weiyan Shi, Tianwei Zhang, Zhixuan Fang, Wei Xu, Han Qiu
Therefore, in this study, we delve into LLMs' susceptibility to persuasive conversations, particularly on factual questions that they can answer correctly.
no code implementations • 21 Jan 2024 • Rongwu Xu, Zhixuan Fang
This paper presents Tempo, the first cloud-based deep learning system that cooperates with TEE and distributed GPUs for efficient DNN training with model confidentiality preserved.
no code implementations • 7 Mar 2024 • Boning Li, Zhixuan Fang, Longbo Huang
Effective action abstraction is crucial in tackling challenges associated with large action spaces in Imperfect Information Extensive-Form Games (IIEFGs).