Zobrazeno 1 - 10
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pro vyhledávání: '"Candelieri A."'
Autor:
Sabbatella, Antonio, Ponti, Andrea, Candelieri, Antonio, Giordani, Ilaria, Archetti, Francesco
A prompt is a sequence of symbol or tokens, selected from a vocabulary according to some rule, which is prepended/concatenated to a textual query. A key problem is how to select the sequence of tokens: in this paper we formulate it as a combinatorial
Externí odkaz:
http://arxiv.org/abs/2312.00471
Autor:
Candelieri, Antonio
Gaussian Process based Bayesian Optimization is a well-known sample efficient sequential strategy for globally optimizing black-box, expensive, and multi-extremal functions. The role of the Gaussian Process is to provide a probabilistic approximation
Externí odkaz:
http://arxiv.org/abs/2305.08624
Gaussian Process regression is a kernel method successfully adopted in many real-life applications. Recently, there is a growing interest on extending this method to non-Euclidean input spaces, like the one considered in this paper, consisting of pro
Externí odkaz:
http://arxiv.org/abs/2212.01310
Optimal resource allocation is gaining a renewed interest due its relevance as a core problem in managing, over time, cloud and high-performance computing facilities. Semi-Bandit Feedback (SBF) is the reference method for efficiently solving this pro
Externí odkaz:
http://arxiv.org/abs/2210.05977
There is a consensus that focusing only on accuracy in searching for optimal machine learning models amplifies biases contained in the data, leading to unfair predictions and decision supports. Recently, multi-objective hyperparameter optimization ha
Externí odkaz:
http://arxiv.org/abs/2205.08835
The main objective of this paper is to outline a theoretical framework to characterise humans' decision-making strategies under uncertainty, in particular active learning in a black-box optimization task and trading-off between information gathering
Externí odkaz:
http://arxiv.org/abs/2112.06292
Automated driving systems (ADS) have undergone a significant improvement in the last years. ADS and more precisely self-driving cars technologies will change the way we perceive and know the world of transportation systems in terms of user experience
Externí odkaz:
http://arxiv.org/abs/2110.13629
Autor:
Candelieri Irene
Publikováno v:
Gestalt Theory, Vol 45, Iss 3, Pp 235-257 (2023)
During his prolific career, the German Jewish scientist Franz Boas (Minden, 1858 - New York, 1942) recognized as the founding father of American Cultural Anthropology – maintained assiduous contacts with the European scientific community, in a priv
Externí odkaz:
https://doaj.org/article/101cfc33d55a41d885b5646d8ca74133
Optimal sensor placement (SP) usually minimizes an impact measure, such as the amount of contaminated water or the number of inhabitants affected before detection. The common choice is to minimize the minimum detection time (MDT) averaged over a set
Externí odkaz:
http://arxiv.org/abs/2103.04862
This paper addresses black-box optimization over multiple information sources whose both fidelity and query cost change over the search space, that is they are location dependent. The approach uses: (i) an Augmented Gaussian Process, recently propose
Externí odkaz:
http://arxiv.org/abs/2102.04951