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Outputs (2)

Analysing the predictivity of features to characterise the search space (2022)
Conference Proceeding
Durgut, R., Aydin, M. E., Ihshaish, H., & Rakib, A. (2022). Analysing the predictivity of features to characterise the search space. In E. Pimenidis, P. Angelov, C. Jayne, A. Papaleonidas, & M. Aydin (Eds.), Artificial Neural Networks and Machine Learning – ICANN 2022 31st International Conference on Artificial Neural Networks, Bristol, UK, September 6–9, 2022, Proceedings; Part IV (1-13). https://doi.org/10.1007/978-3-031-15937-4_1

Exploring search spaces is one of the most unpredictable challenges that has attracted the interest of researchers for decades. One way to handle unpredictability is to characterise the search spaces and take actions accordingly. A well-characterised... Read More about Analysing the predictivity of features to characterise the search space.

Memory-constrained context-aware reasoning (2022)
Conference Proceeding
Uddin, I., Rakib, A., Ali, M., & Vinh, P. C. (2022). Memory-constrained context-aware reasoning. In P. Cong Vinh, & A. Rakib (Eds.), Context-Aware Systems and Applications (133-146). https://doi.org/10.1007/978-3-030-93179-7_11

The context-aware computing paradigm introduces environments, known as smart spaces, which can unobtrusively and proactively assist their users. These systems are currently mostly implemented on mobile platforms considering various techniques, includ... Read More about Memory-constrained context-aware reasoning.