1 code implementation • 17 Apr 2024 • Shuo Liu, Junhao Shen, Hong Qian, Aimin Zhou
To this end, this paper proposes an inductive cognitive diagnosis model (ICDM) for fast new students' mastery levels inference in WOIESs.
1 code implementation • 30 Dec 2023 • Junhao Shen, Hong Qian, Wei zhang, Aimin Zhou
The SCD framework incorporates the symbolic tree to explicably represent the complicated student-exercise interaction function, and utilizes gradient-based optimization methods to effectively learn the student and exercise parameters.
no code implementations • 1 Nov 2023 • You Zhou, Xiujing Lin, Xiang Zhang, Maolin Wang, Gangwei Jiang, Huakang Lu, Yupeng Wu, Kai Zhang, Zhe Yang, Kehang Wang, Yongduo Sui, Fengwei Jia, Zuoli Tang, Yao Zhao, Hongxuan Zhang, Tiannuo Yang, Weibo Chen, Yunong Mao, Yi Li, De Bao, Yu Li, Hongrui Liao, Ting Liu, Jingwen Liu, Jinchi Guo, Xiangyu Zhao, Ying WEI, Hong Qian, Qi Liu, Xiang Wang, Wai Kin, Chan, Chenliang Li, Yusen Li, Shiyu Yang, Jining Yan, Chao Mou, Shuai Han, Wuxia Jin, Guannan Zhang, Xiaodong Zeng
To tackle the challenges of computing resources and environmental impact of AI, Green Computing has become a hot research topic.
1 code implementation • 28 Mar 2023 • Yu-Peng Wu, Hong Qian, Rong-Jun Qin, Yi Chen, Aimin Zhou
Then, a many-objective EA is used for optimization in the low-dimensional discrete solution space to obtain a well-spaced Pareto front.
no code implementations • 10 Jan 2023 • Yue Wang, Joseph X. Zhou, Edoardo Pedrini, Irit Rubin, May Khalil, Roberto Taramelli, Hong Qian, Sui Huang
Recent studies at individual cell resolution have revealed phenotypic heterogeneity in nominally clonal tumor cell populations.
no code implementations • 19 Aug 2022 • Rong-Jun Qin, Fan-Ming Luo, Hong Qian, Yang Yu
This paper addresses policy learning in non-stationary environments and games with continuous actions.
1 code implementation • 23 May 2022 • Tianxiang Sun, Zhengfu He, Hong Qian, Yunhua Zhou, Xuanjing Huang, Xipeng Qiu
By contrast, gradient-free methods only require the forward computation of the PTM to tune the prompt, retaining the benefits of efficient tuning and deployment.
2 code implementations • 10 Jan 2022 • Tianxiang Sun, Yunfan Shao, Hong Qian, Xuanjing Huang, Xipeng Qiu
In such a scenario, which we call Language-Model-as-a-Service (LMaaS), the gradients of PTMs are usually unavailable.
no code implementations • 11 Mar 2021 • Qingli Jing, Hong Qian, Peng Xu
In this work, we apply the Monte Carlo wave packet method to study the ultrafast nuclear dynamics following inner-shell photoionization of N2 exposed to an ultrashort intense X-ray pulse.
Atomic Physics Atomic and Molecular Clusters
no code implementations • 10 Feb 2021 • Hong Qian, Yang Yu
In this article, we summarize methods of derivative-free reinforcement learning to date, and organize the methods in aspects including parameter updating, model selection, exploration, and parallel/distributed methods.
no code implementations • 21 Sep 2019 • Chen Jia, Hong Qian, Michael Q. Zhang
In our model, oscillations tend to occur when the protein is relatively stable and when gene switching is relatively slow.
3 code implementations • 31 Dec 2017 • Yu-Ren Liu, Yi-Qi Hu, Hong Qian, Chao Qian, Yang Yu
Recent advances in derivative-free optimization allow efficient approximation of the global-optimal solutions of sophisticated functions, such as functions with many local optima, non-differentiable and non-continuous functions.
no code implementations • 17 Oct 2017 • Felix X. -F. Ye, Yi-An Ma, Hong Qian
Inference in hidden Markov model has been challenging in terms of scalability due to dependencies in the observation data.
no code implementations • 24 Jan 2014 • Yang Yu, Hong Qian
By summarizing a large range of EAs into the sampling-and-learning framework, we show that the framework directly admits a general analysis on the probable-absolute-approximate (PAA) query complexity.