Výsledky vyhledávání - "Huang, Huifang"

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Efficient Privacy-Preserving Convolutional Spiking Neural Networks with FHE

Autor: Li, Pengbo, Huang, Huifang, Gao, Ting, Guo, Jin, Duan, Jinqiao

With the rapid development of AI technology, we have witnessed numerous innovations and conveniences. However, along with these advancements come privacy threats and risks. Fully Homomorphic Encryption (FHE) emerges as a key technology for privacy-pr

Externí odkaz: http://arxiv.org/abs/2309.09025

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Privacy-Preserving Discretized Spiking Neural Networks

Autor: Li, Pengbo, Gao, Ting, Huang, Huifang, Cheng, Jiani, Gao, Shuhong, Zeng, Zhigang, Duan, Jinqiao

The rapid development of artificial intelligence has brought considerable convenience, yet also introduces significant security risks. One of the research hotspots is to balance data privacy and utility in the real world of artificial intelligence. T

Externí odkaz: http://arxiv.org/abs/2308.12529

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Model Based Reinforcement Learning with Non-Gaussian Environment Dynamics and its Application to Portfolio Optimization

Autor: Huang, Huifang, Gao, Ting, Li, Pengbo, Guo, Jin, Zhang, Peng, Du, Nan

With the fast development of quantitative portfolio optimization in financial engineering, lots of AI-based algorithmic trading strategies have demonstrated promising results, among which reinforcement learning begins to manifest competitive advantag

Externí odkaz: http://arxiv.org/abs/2301.09297

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Stock Trading Optimization through Model-based Reinforcement Learning with Resistance Support Relative Strength

Autor: Huang, Huifang, Gao, Ting, Gui, Yi, Guo, Jin, Zhang, Peng

Reinforcement learning (RL) is gaining attention by more and more researchers in quantitative finance as the agent-environment interaction framework is aligned with decision making process in many business problems. Most of the current financial appl

Externí odkaz: http://arxiv.org/abs/2205.15056

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Cross-Language Binary-Source Code Matching with Intermediate Representations

Autor: Gui, Yi, Wan, Yao, Zhang, Hongyu, Huang, Huifang, Sui, Yulei, Xu, Guandong, Shao, Zhiyuan, Jin, Hai

Binary-source code matching plays an important role in many security and software engineering related tasks such as malware detection, reverse engineering and vulnerability assessment. Currently, several approaches have been proposed for binary-sourc

Externí odkaz: http://arxiv.org/abs/2201.07420

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