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TEMPERONI Alessandro

Main Referenced Co-authors
THEOBALD, Martin  (3)
Skorski, Maciej (2)
Capitanescu, Stefan (1)
DALLE LUCCA TOSI, Mauro  (1)
FRANCK, Christian  (1)
Main Referenced Keywords
Artificial Intelligence (1); Arts (1); Chess (1);
Main Referenced Disciplines
Computer science (5)

Publications (total 5)

The most downloaded
29 downloads
TEMPERONI, A. (2023). Enhancing Deep Learning Performance with Second-order Methods, Random Embeddings, and Relation Extraction [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/55612 https://hdl.handle.net/10993/55612

The most cited

16 citations (Scopus®)

Skorski, M., TEMPERONI, A., & THEOBALD, M. (2021). Revisiting Weight Initialization of Deep Neural Networks. In Proceedings of Machine Learning Research (pp. 1192-1207). PMLR. https://hdl.handle.net/10993/53910

TEMPERONI, A. (2023). Enhancing Deep Learning Performance with Second-order Methods, Random Embeddings, and Relation Extraction [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/55612

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

Capitanescu, S., TEMPERONI, A., & FRANCK, C. (30 November 2022). "The Origins Of Chess" A Digital 3D Chess Artwork with Physics & AI [Paper presentation]. AIFA 2022 - Artificial Intelligence and the Future of Art, Luxembourg.

Skorski, M., TEMPERONI, A., & THEOBALD, M. (2022). Robust and Provable Guarantees for Sparse Random Embeddings. In Advances in Knowledge Discovery and Data Mining - 26th Pacific-Asia Conference, PAKDD 2022, Chengdu, China, May 16-19, 2022, Proceedings, Part II (pp. 211-223). Springer. doi:10.1007/978-3-031-05936-0\_17
Peer reviewed

Skorski, M., TEMPERONI, A., & THEOBALD, M. (2021). Revisiting Weight Initialization of Deep Neural Networks. In Proceedings of Machine Learning Research (pp. 1192-1207). PMLR.
Peer reviewed

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