Working with Cross-entropy loss part1(Machine Learning)
1.Effective and Efficient Training for Sequential Recommendation Using Cumulative Cross-Entropy Loss (arXiv) Author : Fangyu Li, Shenbao Yu, Feng Zeng, Fang Yang Abstract : : Increasing research interests focus on sequential recommender systems, aiming to model dynamic sequence representation precisely. However, the most commonly used loss function in state-of-the-art sequential…
Working with Cross-entropy loss part1(Machine Learning) 1.Effective and Efficient Training for Sequential Recommendation Using Cumulative Cross-Entropy Loss (arXiv) Author : Fangyu Li, Shenbao Yu, Feng Zeng, Fang Yang Abstract : : Increasing research interests focus on sequential recommender systems, aiming to model dynamic sequence representation precisely. However, the most commonly used loss function in state-of-the-art sequential… deep-learning
Working Crossentropy loss part1Machine Learning 1Effective Efficient Training Sequential Recommendation Using Cumulative CrossEntropy Loss arXiv Author Fangyu Li Shenbao Yu Feng Zeng Fang Yang Abstract Increasing research interest focus sequential recommender system aiming model dynamic sequence representation precisely However commonly used loss function stateoftheart sequential… deeplearning