Zobrazeno 1 - 10
of 8 488
pro vyhledávání: '"A, Tonin"'
Large vision-language models (VLLMs) exhibit promising capabilities for processing multi-modal tasks across various application scenarios. However, their emergence also raises significant data security concerns, given the potential inclusion of sensi
Externí odkaz:
http://arxiv.org/abs/2411.02902
Autor:
Rahman, Muhammad Rameez ur, Simonetto, Piero, Polato, Anna, Pasti, Francesco, Tonin, Luca, Vascon, Sebastiano
Open vocabulary 3D object detection (OV3D) allows precise and extensible object recognition crucial for adapting to diverse environments encountered in assistive robotics. This paper presents OpenNav, a zero-shot 3D object detection pipeline based on
Externí odkaz:
http://arxiv.org/abs/2408.13936
Affective polarization and increasing social divisions affect social mixing and the spread of information across online and physical spaces, reinforcing social and electoral cleavages and influencing political outcomes. Here, using aggregated and de-
Externí odkaz:
http://arxiv.org/abs/2407.12146
Autor:
Tao, Qinghua, Tonin, Francesco, Lambert, Alex, Chen, Yingyi, Patrinos, Panagiotis, Suykens, Johan A. K.
Publikováno v:
the 41st International Conference on Machine Learning (ICML), 2024
In contrast with Mercer kernel-based approaches as used e.g., in Kernel Principal Component Analysis (KPCA), it was previously shown that Singular Value Decomposition (SVD) inherently relates to asymmetric kernels and Asymmetric Kernel Singular Value
Externí odkaz:
http://arxiv.org/abs/2406.08748
Clustering nodes in heterophilous graphs presents unique challenges due to the asymmetric relationships often overlooked by traditional methods, which moreover assume that good clustering corresponds to high intra-cluster and low inter-cluster connec
Externí odkaz:
http://arxiv.org/abs/2405.17050
In recent years, human mobility research has discovered universal patterns capable of describing how people move. These regularities have been shown to partly depend on individual and environmental characteristics (e.g., gender, rural/urban, country)
Externí odkaz:
http://arxiv.org/abs/2403.10276
While the great capability of Transformers significantly boosts prediction accuracy, it could also yield overconfident predictions and require calibrated uncertainty estimation, which can be commonly tackled by Gaussian processes (GPs). Existing work
Externí odkaz:
http://arxiv.org/abs/2402.01476
Autor:
Tonin Beatriz Cristina Biz, Castro-Silva Carolina de Sousa, Slack Frank John, Jasiulionis Miriam Galvonas
Publikováno v:
RNA Biology, Vol 21, Iss 1, Pp 1158-1170 (2024)
Long non-coding RNAs (lncRNAs) have received growing attention due to their diverse regulatory roles in cancer, including in melanoma, an aggressive type of skin cancer. The plasticity and phenotypic adaptability of melanoma cells are crucial factors
Externí odkaz:
https://doaj.org/article/e6226fab6642425eb55d54f5d21471f9
Asymmetric data naturally exist in real life, such as directed graphs. Different from the common kernel methods requiring Mercer kernels, this paper tackles the asymmetric kernel-based learning problem. We describe a nonlinear extension of the matrix
Externí odkaz:
http://arxiv.org/abs/2306.07040
In the context of deep learning with kernel machines, the deep Restricted Kernel Machine (DRKM) framework allows multiple levels of kernel PCA (KPCA) and Least-Squares Support Vector Machines (LSSVM) to be combined into a deep architecture using visi
Externí odkaz:
http://arxiv.org/abs/2306.07015