我们调用adaptive loss模块,并初始化α,让它在每个迭代步骤中自适应。 regression = RegressionModel() adaptive = robust_loss_pytorch.adaptive.AdaptiveLossFunction( num_dims = 1, float_dtype=np.float32) params = list(regression.parameters()) + list(adaptive.parameters()) optimizer = torch.optim.Adam...
A General and Adaptive Robust Loss Function 来源:CVPR 2019 文章题目:A General and Adaptive Robust Loss Function 摘要:文章对现有的几种损失函数进行了泛用性的推广。通过引入鲁棒性作为连续参数,该损失函数可以使围绕最小化损… Tinke 论文阅读笔记:A Generalized Loss Function for Crowd Counting and Localizat...
The existence of a category of alleles distinguished by a derived loss of biochemical function has been described by various names: “amorphic” (Muller1932), “loss-of-function” (Jones1972), “nonfunctional” (Nei and Roychoudhury1973), “knockout” (Kulkarni et al.1999),”null” (Engel ...
These proposed methods combine the merits of Flexible Manifold Embedding, non-linear graph based embedding, and adaptive loss function. The adaptive loss function seems to be a good choice for reaching a flexible and adaptive regressor in the sense that the effect of outliers is reduced and the ...
View publication In most machine learning training paradigms a fixed, often handcrafted, loss function is assumed to be a good proxy for an underlying evaluation metric. In this work we assess this assumption by meta-learning an adaptive loss function to directly optimize the evaluation metric. We...
Victims of physical attacks risk death, injury, harm to mates and offspring, loss of resources, and status. Aggression against attacking enemies would be an adaptive solution to...This is a preview of subscription content, log in via an institution to check access. ...
3.3. Network loss Euclidean loss to measure the distance between the estimated density map and the ground truth 引入了一个新的损失函数,侧重于 解决图像中只有几个人的情况估计效果不好的问题 introduce another loss function regarding the head count We notice that most representative approaches perform po...
Physics-informed loss function. The framework employs a physics-informed loss as a soft constraint, which biases the surrogate predictions towards physically consistent solutions. In particular, the employed hybrid strategy, described in Section “Neural operators”, combines data from high-fidelity simula...
Meta-Learning withTask-Adaptive Loss Function(MeTAL)学习一个自适应损失函数,使每个任务得到更好的泛化。具体来说,MeTAL 通过两个元学习器学习任务自适应损失函数:一个元学习器学习损失函数,另一个元学习器生成参数,转换学到的损失函数。我们的任务自适应损失函数被设计得非常灵活,在内环优化期间,有标签的(如支持)...
来源:CVPR 2019 文章题目:A General and Adaptive Robust Loss Function 摘要:文章对现有的几种损失函数进行了泛用性的推广。通过引入鲁棒性作为连续参数,该损失函数可以使围绕最小化损失的算法得以推广,从而…