Social learning in repeated cooperation games in uncertain environments
Journal Article
Andras, P. (2018)
Social learning in repeated cooperation games in uncertain environments. Cognitive Systems Research, 51, 24-39. https://doi.org/10.1016/j.cogsys.2018.04.013
Cooperation and social learning are fundamental mechanisms that maintain social organisation among animals and humans. Social institutions can be conceptualised abstractly as ...
Reproducibility in machine Learning-Based studies: An example of text mining
Conference Proceeding
Olorisade, B. K., Brereton, P., & Andras, P. (2017)
Reproducibility in machine Learning-Based studies: An example of text mining. In ICML 2017 RML Workshop: Reproducibility in Machine Learning
Reproducibility is an essential requirement for computational studies including those based on machine learning techniques. However, many machine learning studies are either n...
A robust data-driven approach to the decoding of pyloric neuron activity
Conference Proceeding
dos Santos, F., Andras, P., Collins, D., & Lam, K. (2017)
A robust data-driven approach to the decoding of pyloric neuron activity. In 2017 IEEE International Workshop on Signal Processing Systems (SiPS). https://doi.org/10.1109/SiPS.2017.8110017
The combination of intra and extra-cellular recording of small neuronal circuits such as stomatogastric nervous systems of the crab (Cancer borealis) is well documented and ro...
Towards an Accurate Identification of Pyloric Neuron Activity with VSDi
Conference Proceeding
dos Santos, F., Andras, P., & Lam, K. (2017)
Towards an Accurate Identification of Pyloric Neuron Activity with VSDi. In Artificial Neural Networks and Machine Learning – ICANN 2017 (121-128). https://doi.org/10.1007/978-3-319-68600-4_15
Voltage-sensitive dye imaging (VSDi) which enables simultaneous optical recording of many neurons in the pyloric circuit of the stomatogastric ganglion is an important techniq...
A multiresolution approach to the extraction of the pyloric rhythm
Conference Proceeding
dos Santos, F., Andras, P., & Lam, K. (2017)
A multiresolution approach to the extraction of the pyloric rhythm. In 2017 40th International Conference on Telecommunications and Signal Processing (TSP) (403-406). https://doi.org/10.1109/TSP.2017.8076015
This paper describes our work toward the development of a computationally robust methodology to identify the pyloric neurons in the stomatogastric ganglion of Cancer pagurus u...
Locally Excited State–Charge Transfer State Coupled Dyes as Optically Responsive Neuron Firing Probes
Journal Article
Sirbu, D., Butcher, J. B., Waddell, P. G., Andras, P., & Benniston, A. C. (2017)
Locally Excited State–Charge Transfer State Coupled Dyes as Optically Responsive Neuron Firing Probes. Chemistry - A European Journal, 23(58), 14639-14649. https://doi.org/10.1002/chem.201703366
A selection of NIR-optically responsive neuron probes was produced comprising of a donor julolidyl group connected to a BODIPY core and several different styryl and vinylpyrid...
Open-ended evolution in cellular automata worlds
Conference Proceeding
Andras, P. (2017)
Open-ended evolution in cellular automata worlds. In ECAL 2017, the Fourteenth European Conference on Artificial Life (438-445). https://doi.org/10.1162/isal_a_073
Open-ended evolution is a fundamental issue in artificial life research. We consider biological and social systems as a flux of interacting components that transiently partici...
A systematic mapping study of empirical studies on software cloud testing methods
Conference Proceeding
Ahmad, A. A., Brereton, P., & Andras, P. (2017)
A systematic mapping study of empirical studies on software cloud testing methods. In 2017 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C) (555-562). https://doi.org/10.1109/QRS-C.2017.94
Context: Software has become more complicated, dynamic, and asynchronous than ever, making testing more challenging. With the increasing interest in the development of cloud c...
Using supervised machine learning algorithms to detect suspicious URLs in online social networks
Conference Proceeding
Al-Janabi, M., Quincey, E. D., & Andras, P. (2017)
Using supervised machine learning algorithms to detect suspicious URLs in online social networks. In ASONAM '17: Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017 (1104-1111). https://doi.org/10.1145/3110025.3116201
The increasing volume of malicious content in social networks requires automated methods to detect and eliminate such content. This paper describes a supervised machine learni...
A systematic analysis of random forest based social media spam classification
Conference Proceeding
Al-Janabi, M., & Andras, P. (2017)
A systematic analysis of random forest based social media spam classification. In Network and System Security: 11th International Conference, NSS 2017, Helsinki, Finland, August 21–23, 2017, Proceedings (427-438). https://doi.org/10.1007/978-3-319-64701-2_31
Recently random forest classification became a popular choice machine learning applications aimed to detect spam content in online social networks. In this paper, we report a ...