Sample Weighting in Machine Learning: From YouTube Playback Duration to Game Recommendation Optimization

This article explains why and how sample weighting is used in machine learning, illustrates YouTube's conversion of video watch time into sample weights to align with its commercial goals, and describes practical weighted‑logistic‑regression techniques applied to improve game recommendation systems.

AIRecommendation SystemsYouTube

0 likes · 8 min read

Sample Weighting in Machine Learning: From YouTube Playback Duration to Game Recommendation Optimization

Alibaba Cloud Developer

Aug 23, 2018 · Artificial Intelligence

Boost Short-Video Recommendations: Multi-Goal Optimization with Weighted Logistic Regression

Alibaba's short‑video recommendation team details how they enhance both click‑through rate and viewing duration by applying sample reweighting, weighted logistic regression, and playback‑completion‑rate normalization, achieving over 6% offline AUC gains and more than 10% increase in average user watch time.

click-through ratemachine learningmulti-objective optimization

0 likes · 10 min read

Boost Short-Video Recommendations: Multi-Goal Optimization with Weighted Logistic Regression

Alibaba Cloud Developer

Aug 22, 2018 · Artificial Intelligence

Boosting Short Video Recommendations with Multi‑Objective Weighted Logistic Regression

This article explains how short‑video platforms enhance recommendation quality by combining click‑through‑rate models with multi‑objective optimization of watch time and completion rate, using sample reweighting and weighted logistic regression to balance perceived and real relevance while improving offline AUC and online user engagement.

CTRmulti-objective optimizationrecommendation

0 likes · 10 min read

Boosting Short Video Recommendations with Multi‑Objective Weighted Logistic Regression