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Profil

DALLE LUCCA TOSI Mauro

Main Referenced Co-authors
THEOBALD, Martin  (8)
ELLAMPALLIL VENUGOPAL, Vinu  (3)
dos Reis, Julio Cesar (2)
Reis, Julio Cesar Dos (2)
Ellampallil Venugopal, Vinu (1)
Main Referenced Keywords
Neural Networks (4); ASGD (2); Online Learning (2); asynchronous (1); Asynchronous Stochastic Gradient Descent (1);
Main Referenced Unit & Research Centers
ULHPC - University of Luxembourg: High Performance Computing (2)
Main Referenced Disciplines
Computer science (14)

Publications (total 14)

The most downloaded
12 downloads
Goulart, H. X., Dalle Lucca Tosi, M., Goncalves, D., Maia, R. F., & Wachs-Lopes, G. A. (2018). Hybrid model for word prediction using naive bayes and latent information. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/52024. https://hdl.handle.net/10993/52024

The most cited

12 citations (WOS)

Dalle Lucca Tosi, M., & dos Reis, J. C. (2022). Understanding the evolution of a scientific field by clustering and visualizing knowledge graphs. Journal of Information Science, 48 (1), 71--89. doi:10.1177/0165551520937915 https://hdl.handle.net/10993/52019

DALLE LUCCA TOSI, M., Venugopal, V. E., & THEOBALD, M. (2024). TensAIR: Real-Time Training of Neural Networks from Data-streams. In ICMLSC '24: Proceedings of the 2024 8th International Conference on Machine Learning and Soft Computing (pp. 73-82). Association for Computing Machinery. doi:10.1145/3647750.3647762
Peer reviewed

DALLE LUCCA TOSI, M. (2024). Online Learning Using Distributed Neural Networks [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/60837

Dalle Lucca Tosi, M., & Theobald, M. (2023). Convergence Analysis of Decentralized ASGD. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/56001.

Dalle Lucca Tosi, M., & Theobald, M. (2023). OPTWIN: Drift identification with optimal sub-windows. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/55440.

Temperoni, A., Dalle Lucca Tosi, M., & Theobald, M. (2023). Efficient Hessian-based DNN Optimization via Chain-Rule Approximation. In Proceedings of the 6th Joint International Conference on Data Science Management of Data (10th ACM IKDD CODS and 28th COMAD) (pp. 297--298).
Peer reviewed

Dalle Lucca Tosi, M., Ellampallil Venugopal, V., & Theobald, M. (2022). CONVERGENCE TIME ANALYSIS OF ASYNCHRONOUS DISTRIBUTED ARTIFICIAL NEURAL NETWORKS [Poster presentation]. 5th Joint International Conference on Data Science Management of Data (9th ACM IKDD CODS and 27th COMAD).
Peer reviewed

Dalle Lucca Tosi, M., Ellampallil Venugopal, V., & Theobald, M. (2022). Convergence time analysis of Asynchronous Distributed Artificial Neural Networks. In 5th Joint International Conference on Data Science Management of Data (9th ACM IKDD CODS and 27th COMAD) (pp. 314--315).
Peer reviewed

Dalle Lucca Tosi, M., & dos Reis, J. C. (2022). Understanding the evolution of a scientific field by clustering and visualizing knowledge graphs. Journal of Information Science, 48 (1), 71--89. doi:10.1177/0165551520937915
Peer reviewed

Dalle Lucca Tosi, M., Ellampallil Venugopal, V., & Theobald, M. (2022). TensAIR: Real-Time Training of Neural Networks from Data-streams. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/54534.

Dalle Lucca Tosi, M., Theobald, M., & Ellampallil Venugopal, V. (21 May 2021). Online Learning using Distributed Neural Networks [Poster presentation]. DTU DRIVEN Colloquium, Luxembourg.

Dalle Lucca Tosi, M., & dos Reis, J. C. (2021). SciKGraph: A knowledge graph approach to structure a scientific field. Journal of Informetrics, 15 (1), 101109.
Peer reviewed

Dalle Lucca Tosi, M., & Reis, J. C. D. (2021). Keyphrase extraction from single textual documents based on semantically defined background knowledge and co-occurrence graphs. International Journal of Metadata, Semantics and Ontologies, 15 (2), 121--132.
Peer reviewed

Dalle Lucca Tosi, M., & Reis, J. C. D. (2019). C-rank: a concept linking approach to unsupervised keyphrase extraction. In Research Conference on Metadata and Semantics Research (pp. 236--247).
Peer reviewed

Goulart, H. X., Dalle Lucca Tosi, M., Goncalves, D., Maia, R. F., & Wachs-Lopes, G. A. (2018). Hybrid model for word prediction using naive bayes and latent information. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/52024.

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