Miscellaneous22 [2023-2] 전상완 - Alternate Loss Functions for Classification and Robust Regression Can Improve the Accuracy of Artificial Neural Networks Alternate Loss Functions for Classification and Robust Regression Can Improve the Accuracy of Artificial Neural Networks All machine learning algorithms use a loss, cost, utility or reward function to encode the learning objective and oversee the learning process. This function that supervises learning is a frequently unrecognized hyperparameter that determines how incorrect arxiv.org 개념 설명 더보기 .. 2023. 12. 2. [2023-2] 염제원 - Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks We propose an algorithm for meta-learning that is model-agnostic, in the sense that it is compatible with any model trained with gradient descent and applicable to a variety of different learning problems, including classification, regression, and reinforc arxiv.org Abstract Model-Agnostic한 Meta-Learning 알고리즘 (MAML)을 제시함 Gradient .. 2023. 11. 24. 이전 1 ··· 3 4 5 6 다음
