Zobrazeno 1 - 10
of 76
pro vyhledávání: '"SUN Tiezhu"'
Publikováno v:
Xi'an Gongcheng Daxue xuebao, Vol 37, Iss 1, Pp 38-45 (2023)
To address the question of whether cold capture can store cold in different regions in winter, and to realize the energy-saving concept of capturing winter cold storage for summer use, the mathematical modeling and experimental demonstration of the c
Externí odkaz:
https://doaj.org/article/9d15e7d545b44177b13eb73491da1dae
Autor:
SUN Tiezhu, MA Jie
Publikováno v:
Xi'an Gongcheng Daxue xuebao, Vol 36, Iss 4, Pp 98-103 (2022)
The dryness of inlet air directly affects the temperature of cold air and chilled water made by evaporative cooling equipment. To solve the problem of high humidity exhaust air during the operation of chiller units and improve the performance of the
Externí odkaz:
https://doaj.org/article/4750c58e71934dfebc1db59bee2697eb
Autor:
Sun, Tiezhu, Daoudi, Nadia, Kim, Kisub, Allix, Kevin, Bissyandé, Tegawendé F., Klein, Jacques
Recent advancements in ML and DL have significantly improved Android malware detection, yet many methodologies still rely on basic static analysis, bytecode, or function call graphs that often fail to capture complex malicious behaviors. DexBERT, a p
Externí odkaz:
http://arxiv.org/abs/2408.16353
Autor:
Sun, Tiezhu, Pian, Weiguo, Daoudi, Nadia, Allix, Kevin, Bissyandé, Tegawendé F., Klein, Jacques
Transfomer-based models have significantly advanced natural language processing, in particular the performance in text classification tasks. Nevertheless, these models face challenges in processing large files, primarily due to their input constraint
Externí odkaz:
http://arxiv.org/abs/2308.01413
Autor:
Sun, Tiezhu, Allix, Kevin, Kim, Kisub, Zhou, Xin, Kim, Dongsun, Lo, David, Bissyandé, Tegawendé F., Klein, Jacques
The automation of a large number of software engineering tasks is becoming possible thanks to Machine Learning (ML). Central to applying ML to software artifacts (like source or executable code) is converting them into forms suitable for learning. Tr
Externí odkaz:
http://arxiv.org/abs/2212.05976
Recently, language representation techniques have achieved great performances in text classification. However, most existing representation models are specifically designed for English materials, which may fail in Chinese because of the huge differen
Externí odkaz:
http://arxiv.org/abs/2212.08105
Recently, neural language representation models pre-trained on large corpus can capture rich co-occurrence information and be fine-tuned in downstream tasks to improve the performance. As a result, they have achieved state-of-the-art results in a lar
Externí odkaz:
http://arxiv.org/abs/2212.04909
Autor:
Li, Yinghua, Dang, Xueqi, Tian, Haoye, Sun, Tiezhu, Wang, Zhijie, Ma, Lei, Klein, Jacques, Bissyandé, Tegawendé F.
The integration of artificial intelligence (AI) into mobile applications has significantly transformed various domains, enhancing user experiences and providing personalized services through advanced machine learning (ML) and deep learning (DL) techn
Externí odkaz:
http://arxiv.org/abs/2212.01635
Autor:
Li, Yinghua, Dang, Xueqi, Tian, Haoye, Sun, Tiezhu, Wang, Zhijie, Ma, Lei, Klein, Jacques, Bissyandé, Tegawendé F.
Publikováno v:
In The Journal of Systems & Software January 2025 219
Autor:
Pian, Weiguo, Peng, Hanyu, Tang, Xunzhu, Sun, Tiezhu, Tian, Haoye, Habib, Andrew, Klein, Jacques, Bissyandé, Tegawendé F.
Representation learning of source code is essential for applying machine learning to software engineering tasks. Learning code representation from a multilingual source code dataset has been shown to be more effective than learning from single-langua
Externí odkaz:
http://arxiv.org/abs/2206.06460