Results 41 to 50 of about 1,345 (121)
Geometric approaches to matrix normalization and graph balancing
Forum of Mathematics, SigmaNormal matrices, or matrices which commute with their adjoints, are of fundamental importance in pure and applied mathematics. In this paper, we study a natural functional on the space of square complex matrices whose global minimizers are normal ...
Tom Needham, Clayton Shonkwiler
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Acceleration of Convergence in Dontchev’s Iterative Method for Solving Variational Inclusions [PDF]
, 2003 2000 Mathematics Subject Classification: 47H04, 65K10.In this paper we investigate the existence of a sequence (xk ) satisfying 0 ∈ f (xk )+ ∇f (xk )(xk+1 − xk )+ 1/2 ∇2 f (xk )(xk+1 − xk )^2 + G(xk+1 ) and converging to a solution x∗ of the generalized
Geoffroy, M., Hilout, S., Pietrus, A.
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A hierarchical loss and its problems when classifying non-hierarchically
, 2019 Failing to distinguish between a sheepdog and a skyscraper should be worse and penalized more than failing to distinguish between a sheepdog and a poodle; after all, sheepdogs and poodles are both breeds of dogs.
LeCun, Yann, Tygert, Mark, Wu, Cinna
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String-Averaging Projected Subgradient Methods for Constrained Minimization [PDF]
, 2013 We consider constrained minimization problems and propose to replace the projection onto the entire feasible region, required in the Projected Subgradient Method (PSM), by projections onto the individual sets whose intersection forms the entire feasible ...
Censor, Y., Zaslavski, A. J.
core
Predicting COVID-19 outbreak in India using modified SIRD model
Applied Mathematics in Science and EngineeringIn this paper, the existing Susceptible-Infected-Recovered-Deceased (SIRD) compartmental epidemiologic process model is modified for forecasting the coronavirus effect in India.
Sakshi Shringi +5 more
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European Journal of Applied MathematicsIn deep learning, interval neural networks are used to quantify the uncertainty of a pre-trained neural network. Suppose we are given a computational problem $P$ and a pre-trained neural network $\Phi _P$ that aims to solve $P$ .
Luca Eva Gazdag +2 more
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An MBO method for modularity optimisation based on total variation and signless total variation
European Journal of Applied MathematicsIn network science, one of the significant and challenging subjects is the detection of communities. Modularity [1] is a measure of community structure that compares connectivity in the network with the expected connectivity in a graph sampled from a ...
Zijun Li, Yves van Gennip, Volker John
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A Fixed Point Theorem for Discontinuous Functions [PDF]
AMS classifications: 54H25, 65K10, 49J53, 68W25Fixed point;simplicial subdivision;discontinuity ...
Herings, P.J.J. +3 more
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A smoothing-type algorithm for solving inequalities under the order induced by a symmetric cone
Journal of Inequalities and Applications, 2011 In this article, we consider the numerical method for solving the system of inequalities under the order induced by a symmetric cone with the function involved being monotone. Based on a perturbed smoothing function, the underlying system of inequalities
Zhang Ying, Lu Nan
doaj
Consensus-based optimisation with truncated noise
European Journal of Applied MathematicsConsensus-based optimisation (CBO) is a versatile multi-particle metaheuristic optimisation method suitable for performing non-convex and non-smooth global optimisations in high dimensions.
Massimo Fornasier +3 more
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