Zobrazeno 1 - 10
of 2 909
pro vyhledávání: '"BORTOLUSSI, A."'
We introduce Limited Rollout Beam Search (LRBS), a beam search strategy for deep reinforcement learning (DRL) based combinatorial optimization improvement heuristics. Utilizing pre-trained models on the Euclidean Traveling Salesperson Problem, LRBS s
Externí odkaz:
http://arxiv.org/abs/2412.10163
Analog integrated circuit (IC) floorplanning is typically a manual process with the placement of components (devices and modules) planned by a layout engineer. This process is further complicated by the interdependence of floorplanning and routing st
Externí odkaz:
http://arxiv.org/abs/2411.15212
Autor:
Basile, Lorenzo, Maiorca, Valentino, Bortolussi, Luca, Rodolà, Emanuele, Locatello, Francesco
When examined through the lens of their residual streams, a puzzling property emerges in transformer networks: residual contributions (e.g., attention heads) sometimes specialize in specific tasks or input attributes. In this paper, we analyze this p
Externí odkaz:
http://arxiv.org/abs/2411.00246
Timeseria is an object-oriented time series processing library implemented in Python, which aims at making it easier to manipulate time series data and to build statistical and machine learning models on top of it. Unlike common data analysis framewo
Externí odkaz:
http://arxiv.org/abs/2410.09567
Let $ V$ be a braided tensor category and $ C$ a tensor category equipped with a braided tensor functor $G:V\to Z(C)$. For any exact indecomposable $C$-module category $M$, we explicitly construct a right adjoint of the action functor $\rho:Z^V(C)\to
Externí odkaz:
http://arxiv.org/abs/2409.01918
To gain insight into the mechanisms behind machine learning methods, it is crucial to establish connections among the features describing data points. However, these correlations often exhibit a high-dimensional and strongly nonlinear nature, which m
Externí odkaz:
http://arxiv.org/abs/2406.15812
The increase of legislative concerns towards the usage of Artificial Intelligence (AI) has recently led to a series of regulations striving for a more transparent, trustworthy and accountable AI. Along with these proposals, the field of Explainable A
Externí odkaz:
http://arxiv.org/abs/2406.14349
Autor:
Pezzi, Cristina, Morosato, Francesco, Marcaccio, Barbara, Bortolussi, Silva, Ramos, Ricardo Luis, Vercesi, Valerio, Postuma, Ian, Fatemi, Setareh
This work presents a preliminary evaluation of the use of the convolutional neural network nnU-NET to automatically contour the volume of Glioblastoma Multiforme in medical images of patients. The goal is to assist the preparation of the Treatment Pl
Externí odkaz:
http://arxiv.org/abs/2406.04908
This paper presents an artificial intelligence driven methodology to reduce the bottleneck often encountered in the analog ICs layout phase. We frame the floorplanning problem as a Markov Decision Process and leverage reinforcement learning for autom
Externí odkaz:
http://arxiv.org/abs/2405.16951
Integrating symbolic knowledge and data-driven learning algorithms is a longstanding challenge in Artificial Intelligence. Despite the recognized importance of this task, a notable gap exists due to the discreteness of symbolic representations and th
Externí odkaz:
http://arxiv.org/abs/2405.14389