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pro vyhledávání: '"Arroyo, Alvaro"'
Time-series data in real-world settings typically exhibit long-range dependencies and are observed at non-uniform intervals. In these settings, traditional sequence-based recurrent models struggle. To overcome this, researchers often replace recurren
Externí odkaz:
http://arxiv.org/abs/2405.20799
Time-series data in real-world medical settings typically exhibit long-range dependencies and are observed at non-uniform intervals. In such contexts, traditional sequence-based recurrent models struggle. To overcome this, researchers replace recurre
Externí odkaz:
http://arxiv.org/abs/2403.10288
Recent research indicates that the performance of machine learning models can be improved by aligning the geometry of the latent space with the underlying data structure. Rather than relying solely on Euclidean space, researchers have proposed using
Externí odkaz:
http://arxiv.org/abs/2309.04810
Recent studies propose enhancing machine learning models by aligning the geometric characteristics of the latent space with the underlying data structure. Instead of relying solely on Euclidean space, researchers have suggested using hyperbolic and s
Externí odkaz:
http://arxiv.org/abs/2309.05678
One of the key decisions in execution strategies is the choice between a passive (liquidity providing) or an aggressive (liquidity taking) order to execute a trade in a limit order book (LOB). Essential to this choice is the fill probability of a pas
Externí odkaz:
http://arxiv.org/abs/2306.05479
Graph Neural Networks leverage the connectivity structure of graphs as an inductive bias. Latent graph inference focuses on learning an adequate graph structure to diffuse information on and improve the downstream performance of the model. In this wo
Externí odkaz:
http://arxiv.org/abs/2303.11754
Stock market returns are typically analyzed using standard regression, yet they reside on irregular domains which is a natural scenario for graph signal processing. To this end, we consider a market graph as an intuitive way to represent the relation
Externí odkaz:
http://arxiv.org/abs/2106.03417
Classical portfolio optimization methods typically determine an optimal capital allocation through the implicit, yet critical, assumption of statistical time-invariance. Such models are inadequate for real-world markets as they employ standard time-a
Externí odkaz:
http://arxiv.org/abs/2102.00477
Autor:
Ares, Gastón, Bove, Isabel, Vidal, Leticia, Brunet, Gerónimo, Fuletti, Darío, Arroyo, Álvaro, Blanc, María Victoria
Publikováno v:
In Children and Youth Services Review February 2021 121
Akademický článek
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