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Simone Ciccolella, Gianluca Della Vedova, Vladimir Filipovic and Mauricio Soto Gomez
Being able to infer the clonal evolution and progression of cancer makes it possible to devise targeted therapies to treat the disease. As discussed in several studies, understanding the history of accumulation and the evolution of mutations during cance...
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Masahito Kumagai, Kazuhiko Komatsu, Masayuki Sato and Hiroaki Kobayashi
Combinatorial clustering based on the Ising model is drawing attention as a high-quality clustering method. However, conventional Ising-based clustering methods using the Euclidean distance cannot handle irregular data. To overcome this problem, this pap...
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Ioannis K. Argyros, Stepan Shakhno, Samundra Regmi and Halyna Yarmola
A plethora of methods are used for solving equations in the finite-dimensional Euclidean space. Higher-order derivatives, on the other hand, are utilized in the calculation of the local convergence order. However, these derivatives are not on the methods...
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Yihao Fang, Mu Niu, Pokman Cheung and Lizhen Lin
We propose an extrinsic Bayesian optimization (eBO) framework for general optimization problems on manifolds. Bayesian optimization algorithms build a surrogate of the objective function by employing Gaussian processes and utilizing the uncertainty in th...
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Sepideh Kilani, Seyedeh Nadia Aghili and Mircea Hulea
A new approach is introduced to address the subject dependency problem in P300-based brain-computer interfaces (BCI) by using transfer learning. The occurrence of P300, an event-related potential, is primarily associated with changes in natural neuron ac...
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Amir Zarringhalam, Saeed Shiry Ghidary, Ali Mohades and Seyed-Ali Sadegh-Zadeh
In this paper, the concept of ultrametric structure is intertwined with the SLAM procedure. A set of pre-existing transformations has been used to create a new simultaneous localization and mapping (SLAM) algorithm. We have developed two new parallel alg...
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Dang-Viet-Anh Nguyen, Jérôme Szewczyk and Kanty Rabenorosoa
We propose a novel algorithm to determine the Euclidean shortest path (ESP) from a given point (source) to another point (destination) inside a tubular space. The method is based on the observation data of a virtual particle (VP) assumed to move along th...
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Haksu Lee, Haojing Shen and Dong-Jun Seo
This paper presents a comparative geometric analysis of the conditional bias (CB)-informed Kalman filter (KF) with the Kalman filter (KF) in the Euclidean space. The CB-informed KFs considered include the CB-penalized KF (CBPKF) and its ensemble extensio...
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Jeba Nadarajan and Rathi Sivanraj
Periodic traffic prediction and analysis is essential for urbanisation and intelligent transportation systems (ITS). However, traffic prediction is challenging due to the nonlinear flow of traffic and its interdependencies on spatiotemporal features. Tra...
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Oleg A. Logachev,Sergey N. Fedorov,Valeriy V. Yashchenko
Pág. 10 - 14
Fixing some ordering on the domain of real-valued functions of n Boolean variables (i. e. pseudo-Boolean functions) we can identify these functions (or rather tables of their values) with vectors in the Euclidean space R 2 n of dimension 2 n . From a per...
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