As governments around the world tighten migration controls, Spain has taken a strikingly different path. In January 2026, the Spanish cabinet approved a decree opening a pathway to legal residency for ...

Weight decay and ℓ2 regularization are crucial in machine learning, especially in limiting network capacity and reducing irrelevant weight components. These techniques align with Occam’s razor ...

Abstract: Hyperparameter estimation is a critical aspect of kernel-based regularization methods (KRMs), alongside kernel design. Empirical Bayes (EB) and Stein's unbiased risk estimator (SURE) are two ...

Reinforcement learning (RL) is a type of learning approach where an agent interacts with an environment to collect experiences and aims to maximize the reward received from the environment. This ...

Abstract: Given the complexity and uncertainty of the underwater environment, it is of great importance to generate realistic and high-quality images. In this paper, we propose six unconditional ...

Have you ever wondered how your streaming service knows just what movie you’d like to watch next? Or how your email filter separates the important messages from the sea of promotional clutter? The ...

In deep neural networks, various forms of noise injection are used as regularization techniques to prevent overfitting and promote generalization on unseen test data. Here, we were interested in ...