() # 定义损失函数和优化器 criterion = torch.nn.CrossEntropyLoss() optimizer = torch.optim.Adam(model.parameters(), lr=0.001) # 微调预训练模型 for epoch in range(10): # 假设训练 10 个周期 for images, labels in data_loader: optimizer.zero_grad() output = model(images) loss = ...
6.2 Reproducing Kernel Hilbert Spaces In what follows, we use X to indicate domains of functions. In machine learning, this set is often referred to as the input space with its generic element x ∈ X called input location. Sometimes, X is assumed to be a compact metric space, e.g., ...
For larger sequences (of sized > 25), EN regularization becomes intractable in time and space complexity. This is because EN needs to query the DNNp = 2dtimes to form the DNN landscape (exponential time complexity ind) and then find the WH transform of the queried DNN landscape (...
在稀疏Q学习(Sparse Q-Learning, SQL)中,一个关键的参数是α(alpha)。该参数在算法中起着平衡最优化和分布偏移的作用。当α趋近于0时,它近似于在给定x的情况下,y的支持值(in-support values)上的最大化操作。在值函数(value function)变得更优时,值正则化(value regularization)的程度减少,但这同时也会带来...
Pathologists have depended on their visual experience to assess tissue structures in smear images, which was time-consuming, error-prone, and inconsistent. Deep learning, particularly Convolutional Neural Networks (CNNs), offers the ability to automate t
Federated semi-supervised learning (FSSL) target to address the increasing privacy concerns for the practical scenarios, where data holders are limited in labeling capability. Latest FSSL approaches leverage the prediction consistency between the local model and global model to exploit knowledge from parti...
1. What is Overfitting in Machine Learning? Overfitting occurs when a machine learning model learns both the underlying pattern and the noise in the training data to such an extent that it negatively impacts the model's performance on new, unseen data. ...
The method was applied to beam dynamics modeling of the medium energy beam transport (MEBT) section in the China Accelerator Facility for Superheavy Elements (CAFe II). The final results indicate that after training, the network maintains a mismatch, emittance difference, and transmission efficiency...
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To analyze the performance of these methods on the minority classes, the accuracy was further reported on three splits: Many-shot(\(\ge 100\)), Medium-shot(\(20 \sim 100\)), and Few-shot (\(\le 100\)) in addition to the overall accuracy. 4.2 Implementation Details Our models were...