Zobrazeno 1 - 10
of 93
pro vyhledávání: '"Bricalli, P"'
We study the problem of the irreducibility of the Hessian variety $\mathcal{H}_f$ associated with a smooth cubic hypersurface $V(f)\subset \mathbb{P}^n$. We prove that when $n\leq5$, $\mathcal{H}_f$ is normal and irreducible if and only if $f$ is not
Externí odkaz:
http://arxiv.org/abs/2406.12024
Autor:
Padberg, Henriette, Regev, Amir, Piccolboni, Giuseppe, Bricalli, Alessandro, Molas, Gabriel, Nodin, Jean Francois, Kvatinsky, Shahar
Publikováno v:
IEEE Transactions on Circuits and Systems II: Express Briefs (2023), pages 1-1
Processing-in-memory (PIM) is attractive to overcome the limitations of modern computing systems. Numerous PIM systems exist, varying by the technologies and logic techniques used. Successful operation of specific logic functions is crucial for effec
Externí odkaz:
http://arxiv.org/abs/2310.16843
Publikováno v:
International Mathematics Research Notices, Volume 2024, Issue 10, May 2024, Pages 8672--8694
In this paper, we analyze the Hessian locus associated to a general cubic hypersurface, by describing for every $n$ its singular locus and its desingularization. The strategy is based on strong connections between the Hessian and the quadrics defined
Externí odkaz:
http://arxiv.org/abs/2305.10871
Autor:
Kingra, Sandeep Kaur, Parmar, Vivek, Verma, Deepak, Bricalli, Alessandro, Piccolboni, Giuseppe, Molas, Gabriel, Regev, Amir, Suri, Manan
In this work, we propose a fully-binarized XOR-based IMSS (In-Memory Similarity Search) using RRAM (Resistive Random Access Memory) arrays. XOR (Exclusive OR) operation is realized using 2T-2R bitcells arranged along the column in an array. This enab
Externí odkaz:
http://arxiv.org/abs/2208.02651
Autor:
Bricalli, Davide, Favale, Filippo F.
Publikováno v:
Collectanea Mathematica (2022)
In this paper, we exploit some geometric-differential techniques to prove the strong Lefschetz property in degree $1$ for a complete intersection standard Artinian Gorenstein algebra of codimension $6$ presented by quadrics. We prove also some strong
Externí odkaz:
http://arxiv.org/abs/2204.09361
Publikováno v:
Selecta Mathematica (2023)
Gordan and Noether proved in their fundamental theorem that an hypersurface $X=V(F)\subseteq \mathbb{P}^n$ with $n\leq 3$ is a cone if and only if $F$ has vanishing hessian (i.e. the determinant of the Hessian matrix). They also showed that the state
Externí odkaz:
http://arxiv.org/abs/2201.07550
Publikováno v:
Advanced Intelligent Systems (2020)
In-memory computing with crosspoint resistive memory arrays has gained enormous attention to accelerate the matrix-vector multiplication in the computation of data-centric applications. By combining a crosspoint array and feedback amplifiers, it is p
Externí odkaz:
http://arxiv.org/abs/2005.04531
Autor:
Sun, Zhong, Pedretti, Giacomo, Mannocci, Piergiulio, Ambrosi, Elia, Bricalli, Alessandro, Ielmini, Daniele
Publikováno v:
IEEE Trans. Electron Devices (2020)
In-memory computing with crosspoint resistive memory arrays has been shown to accelerate data-centric computations such as the training and inference of deep neural networks, thanks to the high parallelism endowed by physical rules in the electrical
Externí odkaz:
http://arxiv.org/abs/2005.04530
Publikováno v:
Science Advances: Vol. 6, no. 5, eaay2378 (2020)
Machine learning has been getting a large attention in the recent years, as a tool to process big data generated by ubiquitous sensors in our daily life. High speed, low energy computing machines are in demand to enable real-time artificial intellige
Externí odkaz:
http://arxiv.org/abs/2005.01988
Autor:
S. Bianchi, I. Muñoz-Martin, E. Covi, A. Bricalli, G. Piccolboni, A. Regev, G. Molas, J. F. Nodin, F. Andrieu, D. Ielmini
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-14 (2023)
A big challenge for artificial intelligence is to gain the ability of learning by experience like biological systems. Here Bianchi et al. propose a hardware neural network based on resistive-switching synaptic arrays which dynamically adapt to the en
Externí odkaz:
https://doaj.org/article/1fd89242574943b3ba52bdec76007f2c
