Results 91 to 100 of about 19,600 (195)
Linear Interpolation Method for Adversarial Attack [PDF]
Jisuanji kexueDeep neural networks exhibit significant vulnerability in the face of adversarial examples and are prone to attacks.The construction of adversarial examples can be abstracted as an optimization problem that maximizes the objective function.How-ever ...
CHEN Jun, ZHOU Qiang, BAO Lei, TAO Qing
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A subgradient projection method for quasiconvex minimization
PositivityAbstract In this paper, a subgradient projection method for quasiconvex minimization problems is provided. By using strong subdifferentials, it is proved that the generated sequence of the proposed algorithm converges to the solution of the minimization problem of a proper, lower semicontinuous and strongly quasiconvex function (in the sense of
Juan Choque +2 more
openaire +2 more sources
A Refined Inertial-like Subgradient Method for Split Equality Problems
AppliedMathThis paper presents the convergence analysis of a newly proposed algorithm for approximating solutions to split equality variational inequality and fixed point problems in real Hilbert spaces.
Khushdil Ahmad +2 more
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Nonsmooth Recursive Identification of Sandwich Systems with Backlash-Like Hysteresis
Journal of Applied Mathematics, 2012 A recursive gradient identification algorithm based on the bundle method for sandwich systems with backlash-like hysteresis is presented in this paper.
Ruili Dong +3 more
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Optimal Algorithms for Non-Smooth Distributed Optimization in Networks
, 2018 In this work, we consider the distributed optimization of non-smooth convex functions using a network of computing units. We investigate this problem under two regularity assumptions: (1) the Lipschitz continuity of the global objective function, and (2)
Bach, Francis +4 more
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SUBGRADIENT MINIMIZATION METHOD WITH DESCENT VECTORS CORRECTION BY MEANS OF TRAINING RELATIONS PAIRS
Вестник Кемеровского государственного университета, 2014 The paper introduces a conjugate subgradient method whose descent is corrected by a pair of current training relations. The convergence of the method is proved on strictly convex functions.
V. N. Krutikov, Ya. N. Vershinin
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Diagnosis of Alzheimer's Disease Based on Accelerated Mirror Descent Optimization and a Three-Dimensional Aggregated Residual Network. [PDF]
Sensors (Basel), 2023 Tu Y, Lin S, Qiao J, Zhang P, Hao K.
europepmc +1 more source
Control learning rate for autism facial detection via deep transfer learning. [PDF]
Signal Image Video Process, 2023 El Mouatasim A, Ikermane M.
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Joint channel allocation and power control in femtocell system
Tongxin xuebao, 2014 A joint channel allocation and power control algorithm was proposed, which used convex optimization method to combine channel allocation and power control and limit the range of interference, subgradient method was used to solve the close formula of ...
Shi-yao MU, Qi ZHU
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Tongxin xuebao, 2010 Network lifetime maximization in data-aggregated wireless sensor networks with multiple base stations by using geographic routing scheme was studied.To reduce the transmission overhead and avoid routing loops,home base station set potential descendent ...
TANG Wei, GUO Wei
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