Mirza Mohtashim Alam
Orcid: 0000-0002-7047-0791
According to our database1,
Mirza Mohtashim Alam
authored at least 20 papers
between 2018 and 2024.
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Bibliography
2024
Empowering Smart Aging: Insights into the Technical Architecture of the e-VITA Virtual Coaching System for Older Adults.
Sensors, January, 2024
2023
IEEE Trans. Pattern Anal. Mach. Intell., June, 2023
Integrating Knowledge Graph Embeddings and Pre-trained Language Models in Hypercomplex Spaces.
Proceedings of the Semantic Web - ISWC 2023, 2023
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023
Knowledge Graph Embeddings using Neural Ito Process: From Multiple Walks to Stochastic Trajectories.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023
2022
Integrating Knowledge Graph embedding and pretrained Language Models in Hypercomplex Spaces.
CoRR, 2022
Proceedings of the Semantic Web - 19th International Conference, 2022
2021
Loss-Aware Pattern Inference: A Correction on the Wrongly Claimed Limitations of Embedding Models.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2021
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021
Proceedings of the Advances in Information Retrieval, 2021
2020
IEEE Access, 2020
Proceedings of the Workshop on Deep Learning for Knowledge Graphs (DL4KG2020) co-located with the 17th Extended Semantic Web Conference 2020 (ESWC 2020), Heraklion, Greece, June 02, 2020, 2020
Proceedings of the International Workshop on Knowledge Representation and Representation Learning co-located with the 24th European Conference on Artificial Intelligence (ECAI 2020), 2020
2019
Statistical Analysis and Identification of Important Factors of Liver Disease using Machine Learning and Deep Learning Architecture.
Proceedings of the ICIAI 2019: The 3rd International Conference on Innovation in Artificial Intelligence, 2019
2018
Proceedings of the Eleventh International Conference on Machine Vision, 2018
Proceedings of the Advances in Computing and Data Sciences, 2018
An Adaptive Feature Dimensionality Reduction Technique Based on Random Forest on Employee Turnover Prediction Model.
Proceedings of the Advances in Computing and Data Science, 2018