Results 21 to 30 of about 393,254 (286)
Noise Tolerance under Risk Minimization [PDF]
, 2012 In this paper we explore noise tolerant learning of classifiers. We formulate the problem as follows. We assume that there is an ${\bf unobservable}$ training set which is noise-free.
Manwani, Naresh, Sastry, P. S.
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Minimizing Blood Loss in Spine Surgery [PDF]
Global Spine Journal, 2020 Study Design: Broad narrative review. Objective: To review and summarize the current literature on guidelines, outcomes, techniques and indications surrounding multiple modalities of minimizing blood loss in spine surgery. Methods: A thorough review of peer-reviewed literature was performed on the guidelines, outcomes, techniques, and indications for ...
Christopher Mikhail +27 more
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On Coresets for Regularized Loss Minimization
CoRR, 2019 We design and mathematically analyze sampling-based algorithms for regularized loss minimization problems that are implementable in popular computational models for large data, in which the access to the data is restricted in some way. Our main result is that if the regularizer's effect does not become negligible as the norm of the hypothesis scales ...
Ryan R. Curtin +4 more
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Energies, 2022 In the field of marine renewable energies, the extraction of marine currents by the use of tidal current turbines has led to many studies. In contrast to offshore wind turbines, the mass minimization is not necessarily the most important criterion.
Serigne Ousmane Samb +3 more
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Optimal distribution network reconfiguration to minimization power loss [PDF]
E3S Web of Conferences, 2023 With the development of industry, population growth, and suburbanization, load demand is constantly increasing from year to year. Overload demand has greatly strained the distribution network (DN), resulting in increased power losses due to the high ...
Khasanov Mansur +5 more
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LC compensators based on transmission loss minimization for nonlinear loads [PDF]
, 2004 This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted.
Aziz, A, Zobaa, AF
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Accelerated Proximal Stochastic Dual Coordinate Ascent for Regularized Loss Minimization [PDF]
, 2013 We introduce a proximal version of the stochastic dual coordinate ascent method and show how to accelerate the method using an inner-outer iteration procedure. We analyze the runtime of the framework and obtain rates that improve state-of-the-art results
Shalev-Shwartz, Shai, Zhang, Tong
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Large losses–-probability minimizing approach [PDF]
Applicationes Mathematicae, 2004 The probability minimizing problem of large losses of portfolio in discrete and continuous time models is studied. This gives a generalization of quantile hedging presented in [3].
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Energies, 2022 The optimum penetration of distributed generations into the distribution grid provides several technical and economic benefits. However, the computational time required to solve the constrained optimization problems increases with the increasing network ...
Soheil Younesi +3 more
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Robust 1-Bit Compressed Sensing via Hinge Loss Minimization
, 2020 This work theoretically studies the problem of estimating a structured high-dimensional signal $x_0 \in \mathbb{R}^n$ from noisy $1$-bit Gaussian measurements.
Genzel, Martin, Stollenwerk, Alexander
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