天泽28:CSDN认证博客专家
博客地址:https://blog.csdn.net/u012328159
天泽28:CSDN认证博客专家
博客地址:https://blog.csdn.net/u012328159
推荐系统阿里深度兴趣网络:DIN模型(Deep Interest Network)
推荐系统(十七)双塔模型:微软DSSM模型(Deep Structured Semantic Models)
计算广告Ad Click Prediction: a View from the Trenches工程实践视角下的广告点击率预估
推荐系统(十四)多任务学习:阿里ESMM(完整空间多任务模型)
推荐系统(十六)多任务学习:腾讯PLE模型(Progressive Layered Extraction model)
推荐系统(二十)谷歌YouTubeDNN(Deep Neural Networks for YouTube Recommendations)
推荐系统PNN模型(Product-based Neural Networks)
推荐系统(十三)阿里深度兴趣网络:DSIN模型(Deep Session Interest Network)
推荐系统(十五)多任务学习:谷歌MMoE(Multi-gate Mixture-of-Experts )
推荐系统(十七)双塔模型:微软DSSM模型(Deep Structured Semantic Models)
推荐系统(十五)多任务学习:谷歌MMoE(Multi-gate Mixture-of-Experts )
推荐系统(二十)谷歌YouTubeDNN(Deep Neural Networks for YouTube Recommendations)
推荐系统(十三)阿里深度兴趣网络:DSIN模型(Deep Session Interest Network)
推荐系统(十三)阿里深度兴趣网络:DSIN模型(Deep Session Interest Network)
推荐系统(二十)谷歌YouTubeDNN(Deep Neural Networks for YouTube Recommendations)
推荐系统(十七)双塔模型:微软DSSM模型(Deep Structured Semantic Models)
推荐系统DeepFM模型(A Factorization-Machine based Neural Network)
推荐系统(十九)Gate网络:百度GemNN(Gating-Enhanced Multi-Task Neural Networks)
推荐系统(十五)多任务学习:谷歌MMoE(Multi-gate Mixture-of-Experts )
推荐系统(十六)多任务学习:腾讯PLE模型(Progressive Layered Extraction model)
推荐系统DeepFM模型(A Factorization-Machine based Neural Network)
推荐系统Field-aware Factorization Machines(FFM)
推荐系统(十六)多任务学习:腾讯PLE模型(Progressive Layered Extraction model)
推荐系统Field-aware Factorization Machines(FFM)
推荐系统(十九)Gate网络:百度GemNN(Gating-Enhanced Multi-Task Neural Networks)
推荐系统阿里深度兴趣网络:DIN模型(Deep Interest Network)
推荐系统PNN模型(Product-based Neural Networks)
推荐系统Field-aware Factorization Machines(FFM)
推荐系统(十九)Gate网络:百度GemNN(Gating-Enhanced Multi-Task Neural Networks)
推荐系统Factorization Machines(FM)
计算广告Ad Click Prediction: a View from the Trenches工程实践视角下的广告点击率预估
推荐系统阿里深度兴趣网络:DIEN模型(Deep Interest Evolution Network)
推荐系统(十四)多任务学习:阿里ESMM(完整空间多任务模型)
推荐系统阿里深度兴趣网络:DIEN模型(Deep Interest Evolution Network)