Results 41 to 50 of about 393,254 (286)
Applied Sciences, 2019 Among the grid service applications of high-voltage direct current (HVDC) systems, frequency⁻power droop control for islanded networks is one of the most widely used schemes.
Gyusub Lee, Seungil Moon, Pyeongik Hwang
doaj +1 more source
Zhongguo dianli, 2020 In order to reduce the power losses in power transmission from West to East, an optimal power distribution strategy with minimized losses is studied for the West-to-East power transmission channels based on both theoretical analysis and simulation ...
Gaihong CHENG, Qingchun ZHU, Jing YAN
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Energies, 2023 Transmission line losses are a crucial and essential issue in stable power system operation. Numerous methodologies and techniques prevail for minimizing losses.
Chandu Valuva, Subramani Chinnamuthu
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Robust Loss Functions under Label Noise for Deep Neural Networks
, 2017 In many applications of classifier learning, training data suffers from label noise. Deep networks are learned using huge training data where the problem of noisy labels is particularly relevant. The current techniques proposed for learning deep networks
Ghosh, Aritra +2 more
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Robust regularized singular value decomposition with application to mortality data [PDF]
, 2013 We develop a robust regularized singular value decomposition (RobRSVD) method for analyzing two-way functional data. The research is motivated by the application of modeling human mortality as a smooth two-way function of age group and year.
Huang, Jianhua Z. +2 more
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Objective To evaluate the diagnostic yield and utility of universal paired tumor–normal multigene panel sequencing in newly diagnosed pediatric solid and central nervous system (CNS) tumor patients and to compare the detection of germline pathogenic/likely pathogenic variants (PV/LPVs) against established clinical referral criteria for cancer ...
Natalie Waligorski +9 more
wiley +1 more source
Empirical Risk Minimization with Approximations of Probabilistic Grammars [PDF]
, 2010 Probabilistic grammars are generative statistical models that are useful for compositional and sequential structures. We present a framework, reminiscent of structural risk minimization, for empirical risk minimization of the parameters of a fixed ...
Cohen, S. B., Smith, N. A.
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Learning Supervised PageRank with Gradient-Based and Gradient-Free Optimization Methods
, 2016 In this paper, we consider a non-convex loss-minimization problem of learning Supervised PageRank models, which can account for some properties not considered by classical approaches such as the classical PageRank model.
Bogolubsky, Lev +7 more
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Reliable Multi-label Classification: Prediction with Partial Abstention
, 2020 In contrast to conventional (single-label) classification, the setting of multilabel classification (MLC) allows an instance to belong to several classes simultaneously.
Hüllermeier, Eyke, Nguyen, Vu-Linh
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On the Error Resistance of Hinge Loss Minimization
CoRR, 2020 Commonly used classification algorithms in machine learning, such as support vector machines, minimize a convex surrogate loss on training examples. In practice, these algorithms are surprisingly robust to errors in the training data. In this work, we identify a set of conditions on the data under which such surrogate loss minimization algorithms ...
openaire +3 more sources