Suchergebnisse - arts subjects::engineering AND technology::computer science::algorithms::numerical algorithms

Asynchronous parallel algorithms for nonconvex optimization von Cannelli, Loris, Facchinei, Francisco, Kungurtsev, Vyacheslav, Scutari, Gesualdo

“… We propose a new asynchronous parallel block-descent algorithmic framework for the minimization of the sum of a smooth nonconvex function and a nonsmooth convex one, subject to both convex and nonconvex constraints …”
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An improved differential evolution algorithm using efficient adapted surrogate model for numerical optimization von Awad, Noor H., Ali, Mostafa Z., Mallipeddi, Rammohan, Suganthan, Ponnuthurai N.

“… Contemporary real-world optimization benchmarks are subject to many constraints and are often high-dimensional problems …”
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Prediction of cutting force via machine learning: state of the art, challenges and potentials von Liu, Meng, Xie, Hui, Pan, Wencheng, Ding, Songlin, Li, Guangxian

“… Accurate prediction of cutting force has been the subject of extensive research in machining technology for decades …”
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SeqSleepNet: End-to-End Hierarchical Recurrent Neural Network for Sequence-to-Sequence Automatic Sleep Staging von Phan, Huy, Andreotti, Fernando, Cooray, Navin, Chen, Oliver Y., De Vos, Maarten

“… Automatic sleep staging has been often treated as a simple classification problem that aims at determining the label of individual target polysomnography …”
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Constrained Kinematic Control in Minimally Invasive Robotic Surgery Subject to Remote Center of Motion Constraint von Sadeghian, Hamid, Zokaei, Fatemeh, Hadian Jazi, Shahram

“… This paper presents kinematic control of surgical robotic systems subject to Remote Center of Motion (RCM …”
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Finite-Bit Quantization for Distributed Algorithms With Linear Convergence von Michelusi, Nicolo, Scutari, Gesualdo, Lee, Chang-Shen

“… This paper studies distributed algorithms for (strongly convex) composite optimization problems over mesh networks, subject to quantized communications …”
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Stationary common spatial patterns for brain-computer interfacing von Samek, Wojciech, Vidaurre, Carmen, Müller, Klaus-Robert, Kawanabe, Motoaki

“… Classifying motion intentions in brain-computer interfacing (BCI) is a demanding task as the recorded EEG signal is not only noisy and has limited spatial resolution but it is also intrinsically non-stationary …”
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Overlap matrix completion for predicting drug-associated indications von Yang, Mengyun, Luo, Huimin, Li, Yaohang, Wu, Fang-Xiang, Wang, Jianxin

“… Identification of potential drug-associated indications is critical for either approved or novel drugs in drug repositioning. Current computational methods …”
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An active-set algorithm for norm constrained quadratic problems von Rontsis, Nikitas, Goulart, Paul J., Nakatsukasa, Yuji

“… We present an algorithm for the minimization of a nonconvex quadratic function subject to linear inequality constraints and a two-sided bound on the 2-norm of its solution …”
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Numerical algorithms for personalized search in self-organizing information networks von Kamvar, Sep, Kamvar, Sep

“… Representing much of the foundational research in this field, the book develops scalable algorithms that exploit the graphlike properties underlying personalized search and reputation management …”
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A Speedy Calibration Method Using Riemannian Geometry Measurement and Other-Subject Samples on A P300 Speller von Qi, Hongzhi, Xue, Yuqi, Xu, Lichao, Cao, Yong, Jiao, Xuejun

“… P300 spellers are among the most popular brain-computer interface paradigms, and they are used for many clinical applications …”
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A Framework for the Generation of Realistic Synthetic Cardiac Ultrasound and Magnetic Resonance Imaging Sequences From the Same Virtual Patients von Zhou, Y., Giffard-Roisin, S., De Craene, M., Camarasu-Pop, S., D'Hooge, J., Alessandrini, M., Friboulet, D., Sermesant, M., Bernard, O.

“… (both cine and tagging) image sequences from the same virtual patient. A state-of-the-art electromechanical (E/M …”
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A modified teaching–learning-based optimization algorithm for numerical function optimization von Niu, Peifeng, Ma, Yunpeng, Yan, Shanshan

“… In this paper, a kind of modified teaching–learning-based optimization algorithm (MTLBO …”
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Deep Learning for Segmentation Using an Open Large-Scale Dataset in 2D Echocardiography von Leclerc, Sarah, Smistad, Erik, Pedrosa, Joao, Ostvik, Andreas, Cervenansky, Frederic, Espinosa, Florian, Espeland, Torvald, Berg, Erik Andreas Rye, Jodoin, Pierre-Marc, Grenier, Thomas, Lartizien, Carole, Dhooge, Jan, Lovstakken, Lasse, Bernard, Olivier

“… Over the past decades, the automation of this task has been the subject of intense research. In this paper, we evaluate how far the state-of-the-art encoder-decoder deep …”
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Automatic 3D Bi-Ventricular Segmentation of Cardiac Images by a Shape-Refined Multi- Task Deep Learning Approach von Duan, Jinming, Bello, Ghalib, Schlemper, Jo, Bai, Wenjia, Dawes, Timothy J. W., Biffi, Carlo, de Marvao, Antonio, Doumoud, Georgia, O'Regan, Declan P., Rueckert, Daniel

“… Deep learning approaches have achieved state-of-the-art performance in cardiac magnetic resonance (CMR) image segmentation …”
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A new framework for assessing subject-specific whole brain circulation and perfusion using MRI-based measurements and a multi-scale continuous flow model von Hodneland, Erlend, Hanson, Erik, Sævareid, Ove, Nævdal, Geir, Lundervold, Arvid, Šoltészová, Veronika, Munthe-Kaas, Antonella Z., Deistung, Andreas, Reichenbach, Jürgen R., Nordbotten, Jan M.

“… A large variety of severe medical conditions involve alterations in microvascular circulation. Hence, measurements or simulation of circulation and perfusion …”
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Visual Simulation of Multiple Fluids in Computer Graphics: A State-of-the-Art Report von Ren, Bo, Yang, Xu-Yun, Lin, Ming C., Thuerey, Nils, Teschner, Matthias, Li, Chenfeng

“… Realistic animation of various interactions between multiple fluids, possibly undergoing phase change, is a challenging task in computer graphics …”
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Effort-aware and just-in-time defect prediction with neural network von Qiao, Lei, Wang, Yan

“… Accurate defect prediction algorithms help to find more defects with limited effort. To improve the accuracy of defect prediction, in this paper, we propose a deep learning based approach for effort-aware just-in-time defect prediction …”
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The generalized trust region subproblem: solution complexity and convex hull results von Wang, Alex L., Kılınç-Karzan, Fatma

“… A lifting of this problem recasts the GTRS as minimizing a linear objective subject to two nonconvex quadratic constraints …”
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Single-Loop Projection-Free and Projected Gradient-Based Algorithms for Nonconvex-Concave Saddle Point Problems with Bilevel Structure von Ahmadi, Mohammad Mahdi, Yazdandoost Hamedani, Erfan

“… and convex constraint sets, subject to a strongly convex lower-level objective function. This class of problems finds wide applicability in machine learning, encompassing robust multi-task learning, adversarial learning, and robust meta-learning …”
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