Zobrazeno 1 - 10
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pro vyhledávání: '"P Fink"'
Bayesian Optimisation (BO) is a state-of-the-art global optimisation technique for black-box problems where derivative information is unavailable, and sample efficiency is crucial. However, improving the general scalability of BO has proved challengi
Externí odkaz:
http://arxiv.org/abs/2412.09183
Let $R$ be a regular $F$-finite ring of prime characteristic $p$. We prove that the injective dimension of every unit Frobenius module $M$ in the category of unit Frobenius modules is at most $\operatorname{dim}(\operatorname{Supp}_R(M))+1$. We furth
Externí odkaz:
http://arxiv.org/abs/2412.08423
The third author introduced the $g$-polynomial $g_M(t)$ of a matroid, a covaluative matroid statistic which is unchanged under series and parallel extension. The $g$-polynomial of a rank $r$ matroid $M$ has the form $g_1 t + g_2 t^2 + \cdots + g_r t^
Externí odkaz:
http://arxiv.org/abs/2411.19521
We study the classical problem of computing geometric thickness, i.e., finding a straight-line drawing of an input graph and a partition of its edges into as few parts as possible so that each part is crossing-free. Since the problem is NP-hard, we i
Externí odkaz:
http://arxiv.org/abs/2411.15864
Autor:
Zhang, Zepeng, Fink, Olga
Over the last decade, graph neural networks (GNNs) have made significant progress in numerous graph machine learning tasks. In real-world applications, where domain shifts occur and labels are often unavailable for a new target domain, graph domain a
Externí odkaz:
http://arxiv.org/abs/2411.13137
Open-set Domain Adaptation (OSDA) aims to adapt a model from a labeled source domain to an unlabeled target domain, where novel classes - also referred to as target-private unknown classes - are present. Source-free Open-set Domain Adaptation (SF-OSD
Externí odkaz:
http://arxiv.org/abs/2411.12558
Autor:
Wei, Amaury, Fink, Olga
Rigid body interactions are fundamental to numerous scientific disciplines, but remain challenging to simulate due to their abrupt nonlinear nature and sensitivity to complex, often unknown environmental factors. These challenges call for adaptable l
Externí odkaz:
http://arxiv.org/abs/2411.11467
Threat hunting analyzes large, noisy, high-dimensional data to find sparse adversarial behavior. We believe adversarial activities, however they are disguised, are extremely difficult to completely obscure in high dimensional space. In this paper, we
Externí odkaz:
http://arxiv.org/abs/2411.07089
The deployment of affordable Internet of Things (IoT) sensors for air pollution monitoring has increased in recent years due to their scalability and cost-effectiveness. However, accurately calibrating these sensors in uncontrolled environments remai
Externí odkaz:
http://arxiv.org/abs/2411.06917
Building energy modeling plays a vital role in optimizing the operation of building energy systems by providing accurate predictions of the building's real-world conditions. In this context, various techniques have been explored, ranging from traditi
Externí odkaz:
http://arxiv.org/abs/2411.01055