embedding optimization

DataFunTalk

Feb 27, 2021 · Artificial Intelligence

Optimizing Coarse Ranking Models for Short Video Recommendation: From GBDT to Dual‑Tower DNN and Cascading

This article details the practical upgrades of iQIYI's short‑video recommendation coarse‑ranking pipeline, moving from a GBDT model to a dual‑tower DNN, applying knowledge distillation, embedding compression, inference optimizations, and finally a cascade architecture to align with the fine‑ranking model while reducing resource consumption.

cascading modelcoarse rankingdual-tower DNN

0 likes · 12 min read

Optimizing Coarse Ranking Models for Short Video Recommendation: From GBDT to Dual‑Tower DNN and Cascading

iQIYI Technical Product Team

Feb 26, 2021 · Artificial Intelligence

Optimization of Coarse Ranking Models for Short‑Video Recommendation at iQIYI

iQIYI’s short‑video recommendation team replaced a GBDT coarse‑ranking model with a lightweight dual‑tower DNN, applied knowledge distillation, sparse‑aware embedding optimization, and inference merging, then introduced a cascade MMOE architecture, achieving comparable accuracy with half the memory, ~19 ms latency reduction, and measurable gains in watch time, CTR and engagement.

Online Inferencecascade modelcoarse ranking

0 likes · 15 min read

Optimization of Coarse Ranking Models for Short‑Video Recommendation at iQIYI

360 Tech Engineering

Sep 14, 2020 · Artificial Intelligence

TensorNet: A Distributed Training Framework Optimized for Large-Scale Sparse Feature Models on TensorFlow

TensorNet is a TensorFlow‑based distributed training framework that tackles the challenges of massive data and billions of sparse parameters in advertising and recommendation systems by enabling near‑infinite sparse feature dimensions, drastically reducing synchronization overhead, and delivering up to 35% inference speed improvements.

AI InfrastructureTensorFlowdistributed training

0 likes · 8 min read

TensorNet: A Distributed Training Framework Optimized for Large-Scale Sparse Feature Models on TensorFlow