Zobrazeno 1 - 10
of 104
pro vyhledávání: '"Afsharchi Mohsen"'
Publikováno v:
journal = {Evolutionary Computation}, volume = {30}, number = {2}, year = {2022}
This paper presents a novel method, called Modular Grammatical Evolution (MGE), towards validating the hypothesis that restricting the solution space of NeuroEvolution to modular and simple neural networks enables the efficient generation of smaller
Externí odkaz:
http://arxiv.org/abs/2208.02787
Discovering emerging entities (EEs) is the problem of finding entities before their establishment. These entities can be critical for individuals, companies, and governments. Many of these entities can be discovered on social media platforms, e.g. Tw
Externí odkaz:
http://arxiv.org/abs/2207.02434
Publikováno v:
In Expert Systems With Applications 1 January 2025 259
Recommender Systems (RSs) aim to model and predict the user preference while interacting with items, such as Points of Interest (POIs). These systems face several challenges, such as data sparsity, limiting their effectiveness. In this paper, we addr
Externí odkaz:
http://arxiv.org/abs/2201.03450
Autor:
Rahmani, Hossein A., Aliannejadi, Mohammad, Ahmadian, Sajad, Baratchi, Mitra, Afsharchi, Mohsen, Crestani, Fabio
With the rapid growth of Location-Based Social Networks, personalized Points of Interest (POIs) recommendation has become a critical task to help users explore their surroundings. Due to the scarcity of check-in data, the availability of geographical
Externí odkaz:
http://arxiv.org/abs/1909.06667
Autor:
Rahmani, Hossein A., Aliannejadi, Mohammad, Zadeh, Rasoul Mirzaei, Baratchi, Mitra, Afsharchi, Mohsen, Crestani, Fabio
Recently, Point of interest (POI) recommendation has gained ever-increasing importance in various Location-Based Social Networks (LBSNs). With the recent advances of neural models, much work has sought to leverage neural networks to learn neural embe
Externí odkaz:
http://arxiv.org/abs/1907.13376
Autor:
Khani, Hossein, Afsharchi, Mohsen
Currently the Dempster-Shafer based algorithm and Uniform Random Probability based algorithm are the preferred method of resolving security games, in which defenders are able to identify attackers and only strategy remained ambiguous. However this mo
Externí odkaz:
http://arxiv.org/abs/1508.02035
Autor:
Jamshidpey, Aryo, Afsharchi, Mohsen
In this paper we study multi robot cooperative task allocation issue in a situation where a swarm of robots is deployed in a confined unknown environment where the number of colored spots which represent tasks and the ratios of them are unknown. The
Externí odkaz:
http://arxiv.org/abs/1503.00237
Autor:
Ahmadian, Sajad, Joorabloo, Nima, Jalili, Mahdi, Ren, Yongli, Meghdadi, Majid, Afsharchi, Mohsen
Publikováno v:
In Knowledge-Based Systems 15 March 2020 192
Publikováno v:
In Information Processing and Management July 2018 54(4):707-725