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Zixin Feng, Teligeng Yun, Yu Zhou, Ruirui Zheng and Jianjun He
Geometric mean metric learning (GMML) algorithm is a novel metric learning approach proposed recently. It has many advantages such as unconstrained convex objective function, closed form solution, faster computational speed, and interpretability over oth...
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Danny D?Agostino, Matteo Diez, Mario Felli and Andrea Serani
This study investigates the underlying mechanisms governing the evolution of tip vortices in the far field of a naval propeller wake. To achieve this, a novel approach utilizing data clustering applied to particle image velocimetry snapshots is employed....
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Yihao Fang, Mu Niu, Pokman Cheung and Lizhen Lin
We propose an extrinsic Bayesian optimization (eBO) framework for general optimization problems on manifolds. Bayesian optimization algorithms build a surrogate of the objective function by employing Gaussian processes and utilizing the uncertainty in th...
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Mei Bie, Huan Xu, Quanle Liu, Yan Gao, Kai Song and Xiangjiu Che
Facial expression recognition (FER) is an important field in computer vision with many practical applications. However, one of the challenges in FER is dealing with small sample data, where the number of samples available for training machine learning al...
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Andrei Konstantinov, Stanislav Kirpichenko and Lev Utkin
A new method for estimating the conditional average treatment effect is proposed in this paper. It is called TNW-CATE (the Trainable Nadaraya?Watson regression for CATE) and based on the assumption that the number of controls is rather large and the numb...
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