PTfuzz: Guided Fuzzing With Processor Trace Feedback

Autor: Gen Zhang, Xu Zhou, Yingqi Luo, Xugang Wu, Erxue Min

Publikováno v: IEEE Access, Vol 6, Pp 37302-37313 (2018)

Greybox fuzzing, such as american fuzzy lop (AFL), is very efficient in finding software vulnerability, which makes it the state-of-the-art fuzzing technology. Greybox fuzzing leverages the branch information collected during program running as feedb

Externí odkaz: https://doaj.org/article/4df5315e2540453fb34f832186133b9e

Sentiment-Aware Emoji Insertion Via Sequence Tagging

Autor: Bo Liu, Xingkong Ma, Erxue Min, Yiping Song, Fuqiang Lin

Publikováno v: IEEE MultiMedia. 28:40-48

Due to the booming popularity of online social networks, emojis have been widely used in online communication. As nonverbal language units, emojis help to convey emotions and express feelings. In this article, we focus on the sentiment-aware emoji in

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d1de3bb1eef5364b4ed424885ba014fb
https://doi.org/10.1109/mmul.2021.3075705

Neighbour Interaction based Click-Through Rate Prediction via Graph-masked Transformer

Autor: Erxue Min, Yu Rong, Tingyang Xu, Yatao Bian, Da Luo, Kangyi Lin, Junzhou Huang, Sophia Ananiadou, Peilin Zhao

Publikováno v: Min, E, Rong, Y, Xu, T, Bian, Y, Luo, D, Lin, K, Huang, J, Ananiadou, S & Zhao, P 2022, ' Neighbour Interaction based Click-Through Rate Prediction via Graph-masked Transformer ', Paper presented at SIGIR '22: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, 11/07/22-15/07/22 pp. 353-362 . https://doi.org/10.1145/3477495.3532031

Click-Through Rate (CTR) prediction, which aims to estimate the probability that a user will click an item, is an essential component of online advertising. Existing methods mainly attempt to mine user interests from users' historical behaviours, whi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cf39eee7eadd735c4977cbc8f296e7d7
http://arxiv.org/abs/2201.13311

Analysis of the Variance Reduction in SVRG and a New Acceleration Method

Autor: Jianjing Cui, Erxue Min, Jun Long

Publikováno v: IEEE Access, Vol 6, Pp 16165-16175 (2018)

Stochastic gradient descent is a popular method in large-scale optimization for machine learning but suffers from a slow convergence. In recent years, stochastic variance reduced gradient (SVRG) is proposed to remedy this problem. Although many varia

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::042ffdc466a9fe40fb7d3b6d5e741d6c
https://ieeexplore.ieee.org/document/8319495/

TR-IDS: Anomaly-Based Intrusion Detection through Text-Convolutional Neural Network and Random Forest

Autor: Jianjing Cui, Erxue Min, Qiang Liu, Wei Chen, Jun Long

Publikováno v: Security and Communication Networks, Vol 2018 (2018)

As we head towards the IoT (Internet of Things) era, protecting network infrastructures and information security has become increasingly crucial. In recent years, Anomaly-Based Network Intrusion Detection Systems (ANIDSs) have gained extensive attent

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a0ee2ee5e18ddb1255635eaad138274a