Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Mirza Mohtashim Alam"'
Autor:
Riccardo Naccarelli, Francesca D’Agresti, Sonja Dana Roelen, Kristiina Jokinen, Sara Casaccia, Gian Marco Revel, Martino Maggio, Zohre Azimi, Mirza Mohtashim Alam, Qasid Saleem, Abrar Hyder Mohammed, Giulio Napolitano, Florian Szczepaniak, Mossaab Hariz, Gérard Chollet, Christophe Lohr, Jérôme Boudy, Rainer Wieching, Toshimi Ogawa
Publikováno v:
Sensors, Vol 24, Iss 2, p 638 (2024)
With a substantial rise in life expectancy throughout the last century, society faces the imperative of seeking inventive approaches to foster active aging and provide adequate aging care. The e-VITA initiative, jointly funded by the European Union a
Externí odkaz:
https://doaj.org/article/58365bc117874ab0a5a068471c2e9dd8
Autor:
Mirza Mohtashim Alam, Md Rashad Al Hasan Rony, Mojtaba Nayyeri, Karishma Mohiuddin, M. S. T. Mahfuja Akter, Sahar Vahdati, Jens Lehmann
Publikováno v:
IEEE Access, Vol 10, Pp 76008-76020 (2022)
Knowledge graph embedding models have become a popular approach for knowledge graph completion through predicting the plausibility of (potential) triples. This is performed by transforming the entities and relations of the knowledge graph into an emb
Externí odkaz:
https://doaj.org/article/b059c825278f45f99207ea8f7e1a7597
Autor:
Michael McTear, Kristiina Jokinen, Mirza Mohtashim Alam, Qasid Saleem, Giulio Napolitano, Florian Szczepaniak, Mossaab Hariz, Gérard Chollet, Christophe Lohr, Jérôme Boudy, Zohre Azimi, Sonja Dana Roelen, Rainer Wieching
Publikováno v:
Sensors, Vol 23, Iss 5, p 2748 (2023)
Since life expectancy has increased significantly over the past century, society is being forced to discover innovative ways to support active aging and elderly care. The e-VITA project, which receives funding from both the European Union and Japan,
Externí odkaz:
https://doaj.org/article/701484d022194842a3de16d7cdc4d10d
Publikováno v:
IEEE Access, Vol 8, Pp 196459-196471 (2020)
Knowledge Graph Embeddings (KGE) are used for representation learning in Knowledge Graphs (KGs) by measuring the likelihood of a relation between nodes. Rotation-based approaches, specially axis-angle representations, were shown to improve the perfor
Externí odkaz:
https://doaj.org/article/550ac6c55fae4bf4a2354046c2b2473a
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence. 45:7050-7062
Knowledge graph embedding models have gained significant attention in AI research. The aim of knowledge graph embedding is to embed the graphs into a vector space in which the structure of the graph is preserved. Recent works have shown that the incl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7fb9a37115f84da150482f303218d709
https://doi.org/10.1109/tpami.2021.3121646
https://doi.org/10.1109/tpami.2021.3121646
Autor:
Md Rashad Al Hasan Rony, Mirza Mohtashim Alam, Semab Ali, Qasid Saleem, Jens Lehmann, Sahar Vahdati
Knowledge Graph Embedding models have become an important area of machine learning. Those models provide a latent representation of entities and relations of a knowledge graph which can then be used in downstream machine learning tasks such as link p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b72a3c71f4141afa5f8f7da5439d4d03
https://doi.org/10.21203/rs.3.rs-2188328/v1
https://doi.org/10.21203/rs.3.rs-2188328/v1
Autor:
Mojtaba Nayyeri, Sahar Vahdati, Md Tansen Khan, Mirza Mohtashim Alam, Lisa Wenige, Andreas Behrend, Jens Lehmann
Publikováno v:
The Semantic Web ISBN: 9783031069802
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bde8dea037fb0597592e18fa179718cc
https://doi.org/10.1007/978-3-031-06981-9_15
https://doi.org/10.1007/978-3-031-06981-9_15
Autor:
Mirza Mohtashim Alam, Hamed Shariat Yazdi, Chengjin Xu, Sahar Vahdati, Mojtaba Nayyeri, Jens Lehmann, Yadollah Yaghoobzadeh
Publikováno v:
Advances in Knowledge Discovery and Data Mining ISBN: 9783030757670
PAKDD (3)
PAKDD (3)
Knowledge graph embedding models (KGEs) are actively utilized in many of the AI-based tasks, especially link prediction. Despite achieving high performances, one of the crucial aspects of KGEs is their capability of inferring relational patterns, suc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7d7bd3b00fd75b230f9f3a49e0bed94a
https://doi.org/10.1007/978-3-030-75768-7_7
https://doi.org/10.1007/978-3-030-75768-7_7
Autor:
Mojtaba Nayyeri, Mirza Mohtashim Alam, Hamed Shariat Yazdi, Emanuel Sallinger, Jens Lehmann, Sahar Vahdati
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030721121
ECIR (1)
ECIR (1)
Knowledge Graph Embeddings (KGE) have become an important area of Information Retrieval (IR), in particular as they provide one of the state-of-the-art methods for Link Prediction. Recent work in the area of KGEs has shown the importance of relationa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b4966d518138b547ff154dd112c8fe82
https://doi.org/10.1007/978-3-030-72113-8_32
https://doi.org/10.1007/978-3-030-72113-8_32
Autor:
Mohammad Azgar Ali, Hosne Ara Arju, Muhammad Jafar Sadeq, S. Rayhan Kabir, Md. Gazi Salah Uddin, Md. Samaun Hasan, Mizanur Rahman, Rokeya Forhat, Mirza Mohtashim Alam, Rafita Haque, Shaikh Muhammad Allayear, Akhtaruzzaman
Publikováno v:
Proceedings of Fifth International Congress on Information and Communication Technology ISBN: 9789811558559
The Indian subcontinent is a south geographic part of Asia continent which consists of India, Bangladesh, Pakistan, Sri Lanka, Bhutan, Nepal, and Maldives. Different rulers or the empire of different periods have built various buildings and structure
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5b5f15476c0ebd3f3faa337db42cd75b
https://doi.org/10.1007/978-981-15-5856-6_64
https://doi.org/10.1007/978-981-15-5856-6_64