Home »
Academic Articles & Research Papers
Showing 20 of 84 academic articles
Kaixuan Chen, Dalin Zhang, Lina Yao, Bin Guo et al. • ACM Computing Surveys
(2021)
The vast proliferation of sensor devices and Internet of Things enables the applications of sensor-based activity recognition. However, there exist substantial challenges that could influence the performance of the recognition system in pra...
OPENALEX
public-domain
DOI: https://doi.org/10.1145/3447744
Zahra Zamanzadeh Darban, Geoffrey I. Webb, Shirui Pan, Charų C. Aggarwal et al. • ACM Computing Surveys
(2024)
Time series anomaly detection is important for a wide range of research fields and applications, including financial markets, economics, earth sciences, manufacturing, and healthcare. The presence of anomalies can indicate novel or unexpect...
OPENALEX
cc-by
DOI: https://doi.org/10.1145/3691338
Xiaoxiao Ma, Jia Xin Wu, Shan Xue, Jian Yu Yang et al. • IEEE Transactions on Knowledge and Data Engineering
(2021)
Anomalies are rare observations (e.g., data records or events) that deviate significantly from the others in the sample. Over the past few decades, research on anomaly mining has received increasing interests due to the implications of thes...
OPENALEX
Open Access
DOI: https://doi.org/10.1109/tkde.2021.3118815
Gianni Brauwers, Flavius Frăsincar • IEEE Transactions on Knowledge and Data Engineering
(2021)
Attention is an important mechanism that can be employed for a variety of deep learning models across many different domains and tasks. This survey provides an overview of the most important attention mechanisms proposed in the literature. ...
OPENALEX
Open Access
DOI: https://doi.org/10.1109/tkde.2021.3126456
Li Deng • APSIPA Transactions on Signal and Information Processing
(2014)
In this invited paper, my overview material on the same topic as presented in the plenary overview session of APSIPA-2011 and the tutorial material presented in the same conference [1] are expanded and updated to include more recent develop...
OPENALEX
cc-by
DOI: https://doi.org/10.1017/atsip.2013.9
Xing Su, Shan Xue, Fanzhen Liu, Jia Wu et al. • IEEE Transactions on Neural Networks and Learning Systems
(2022)
Detecting a community in a network is a matter of discerning the distinct features and connections of a group of members that are different from those in other communities. The ability to do this is of great significance in network analysis...
OPENALEX
Open Access
DOI: https://doi.org/10.1109/tnnls.2021.3137396
Usman Manzo Gidado, Haruna Chiroma, Nahla Aljojo, Saidu Abubakar et al. • IEEE Access
(2020)
Steering angle prediction is critical in the control of Autonomous Vehicles (AVs) and has attracted the attention of researchers, manufacturers, and insurance companies in the automotive industry. Different Deep Learning (DL) architectures ...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2020.3017883
Massimiliano Luca, Gianni Barlacchi, Bruno Lepri, Luca Pappalardo • ACM Computing Surveys
(2021)
The study of human mobility is crucial due to its impact on several aspects of our society, such as disease spreading, urban planning, well-being, pollution, and more. The proliferation of digital mobility data, such as phone records, GPS t...
OPENALEX
Open Access
DOI: https://doi.org/10.1145/3485125
Tracy W. Smith, Susan A. Colby • The Clearing House A Journal of Educational Strategies Issues and Ideas
(2007)
The authors have been engaged in research focused on students' depth of learning as well as teachers' efforts to foster deep learning. Findings from a study examining the teaching practices and student learning outcomes of sixtyfour teacher...
OPENALEX
DOI: https://doi.org/10.3200/tchs.80.5.205-210
Jing Li, Aixin Sun, Jianglei Han, Chenliang Li • IEEE Transactions on Knowledge and Data Engineering
(2020)
Named entity recognition (NER) is the task to identify mentions of rigid designators from text belonging to predefined semantic types such as person, location, organization etc. NER always serves as the foundation for many natural language ...
OPENALEX
Open Access
DOI: https://doi.org/10.1109/tkde.2020.2981314
Jan Kukačka, Vladimir Golkov, Daniel Cremers • arXiv (Cornell University)
(2017)
Regularization is one of the crucial ingredients of deep learning, yet the term regularization has various definitions, and regularization methods are often studied separately from each other. In our work we present a systematic, unifying t...
OPENALEX
Open Access
DOI: https://doi.org/10.48550/arxiv.1710.10686
Shuai Zhang, Lina Yao, Aixin Sun, Yi Tay • ACM Computing Surveys
(2019)
With the growing volume of online information, recommender systems have been an effective strategy to overcome information overload. The utility of recommender systems cannot be overstated, given their widespread adoption in many web applic...
OPENALEX
Open Access
DOI: https://doi.org/10.1145/3285029
Guansong Pang, Chunhua Shen, Longbing Cao, Anton Van Den Hengel • ACM Computing Surveys
(2021)
Anomaly detection, a.k.a. outlier detection or novelty detection, has been a lasting yet active research area in various research communities for several decades. There are still some unique problem complexities and challenges that require ...
OPENALEX
Open Access
DOI: https://doi.org/10.1145/3439950
Luigi Capogrosso, Federico Cunico, Dong Seon Cheng, Franco Fummi et al. • IEEE Access
(2024)
The emergence of Tiny Machine Learning (TinyML) has positively revolutionized the field of Artificial Intelligence by promoting the joint design of resource-constrained IoT hardware devices and their learning-based software architectures. T...
OPENALEX
cc-by
DOI: https://doi.org/10.1109/access.2024.3365349
Hongyu Liu, Bo Lang • Applied Sciences
(2019)
Networks play important roles in modern life, and cyber security has become a vital research area. An intrusion detection system (IDS) which is an important cyber security technique, monitors the state of software and hardware running in th...
OPENALEX
cc-by
DOI: https://doi.org/10.3390/app9204396
Marco Barreno, Blaine A. Nelson, Russell Sears, Anthony D. Joseph et al. • ACM Asia Conference on Computer and Communications Security (ASIA CCS)
(2006)
Machine learning systems offer unparalled flexibility in dealing with evolving input in a variety of applications, such as intrusion detection systems and spam e-mail filtering. However, machine learning algorithms themselves can be a targe...
OPENALEX
DOI: https://doi.org/10.1145/1128817.1128824
Marco Barreno, Blaine A. Nelson, Anthony D. Joseph, J. D. Tygar • Machine Learning
(2010)
Machine learning’s ability to rapidly evolve to changing and complex situations has helped it become a fundamental tool for computer security. That adaptability is also a vulnerability: attackers can exploit machine learning systems. We pre...
OPENALEX
cc-by-nc
DOI: https://doi.org/10.1007/s10994-010-5188-5
El‐Ghazali Talbi • ACM Computing Surveys
(2021)
During the past few years, research in applying machine learning (ML) to design efficient, effective, and robust metaheuristics has become increasingly popular. Many of those machine learning-supported metaheuristics have generated high-qua...
OPENALEX
Open Access
DOI: https://doi.org/10.1145/3459664
Ling Huang, Anthony D. Joseph, Blaine A. Nelson, Benjamin I. P. Rubinstein et al. • ACM Workshop on Artificial Intelligence and Security (AISec)
(2011)
In this paper (expanded from an invited talk at AISEC 2010), we discuss an emerging field of study: adversarial machine learning---the study of effective machine learning techniques against an adversarial opponent. In this paper, we: give a...
OPENALEX
DOI: https://doi.org/10.1145/2046684.2046692
Inese Polaka, Danute Razuka-Ebela, Jin Young Park, Marcis Leja • BioData Mining
(2021)
Abstract Background The amount of available and potentially significant data describing study subjects is ever growing with the introduction and integration of different registries and data banks. The single specific attribute of these data...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s13040-021-00271-w