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Correcting noisy labels via comparative distillation: a domain adaptation approach. [PDF]

Sci Rep
Feng Y, Liu J, Zhong H.
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Adaptive Pruning for Increased Robustness and Reduced Computational Overhead in Gaussian Process Accelerated Saddle Point Searches. [PDF]

Chemphyschem
Goswami R, Jónsson H.
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A machine learning approach to risk based asset allocation in portfolio optimization. [PDF]

Sci Rep
Agal S, Raulji K, Odedra ND.
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Partitioned RIS-Assisted Vehicular Secure Communication Based on Meta-Learning and Reinforcement Learning. [PDF]

Sensors (Basel)
Li H, Wang F, Qian J, Zhu P, Zhou A.
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Fatigue Behavior and Life Prediction of L-PBF Ti64 with Critical Plane Based Small Building Direction Variations Under Non-Proportional and Multiaxial Loading. [PDF]

Materials (Basel)
Ma TH, Wang YX, Chang L, Zhang W, Zhao JP, Zhou CY.   +5 more
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Dynamic Bearing-Angle for Vision-Based UAV Target Motion Analysis. [PDF]

Sensors (Basel)
Luo Y, Fu H, Fu T, Cha H, Tian B, Tang H, Liu F.   +6 more
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Diagonal Acceleration for Covariance Matrix Adaptation Evolution Strategies

Diagonal Acceleration for Covariance Matrix Adaptation Evolution Strategies
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In Vivo Cardiac Biomechanical Model Parameter Estimation from Ultrafast Shear Wave Elastography

Ferrario C, Venet M, Villemain O, Sermesant M.   +3 more
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Toward a Matrix-Free Covariance Matrix Adaptation Evolution Strategy

IEEE Transactions on Evolutionary Computation, 2020
In this paper, we discuss a method for generating new individuals such that their mean vector and the covariance matrix are defined by formulas analogous to the covariance matrix adaptation evolution strategy (CMA-ES). In contrast to CMA-ES, which generates new individuals using multivariate Gaussian distribution with an explicitly defined covariance ...
Jaroslaw Arabas, Dariusz Jagodzinski
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