large-scale classification

DataFunSummit

Mar 9, 2024 · Artificial Intelligence

OPPO Advertising Recall Algorithm: Architecture, Model Selection, Offline Evaluation, Sample Optimization, and Future Directions

This article presents OPPO's comprehensive advertising recall system, detailing the transition from the old to the new architecture with ANN support, the selection of main‑road recall models, the construction of offline evaluation metrics, sample optimization techniques, model enhancements, multi‑scenario training strategies, and outlook for future improvements.

Sample Optimizationadvertisingdual-tower model

0 likes · 24 min read

OPPO Advertising Recall Algorithm: Architecture, Model Selection, Offline Evaluation, Sample Optimization, and Future Directions

Sohu Tech Products

Jan 3, 2024 · Artificial Intelligence

OPPO Advertising Recall Algorithm: Architecture, Model Selection, Evaluation, and Optimization

OPPO revamped its advertising recall system by replacing a latency‑prone directional pipeline with an ANN‑based full‑ad personalized architecture, employing a dual‑tower LTR model, multi‑path auxiliary branches, refined offline metrics, price‑sensitive and hard‑negative sampling, and hybrid joint training, which together boosted ARPU by about 15%.

advertisinglarge-scale classificationmachine learning

0 likes · 24 min read

OPPO Advertising Recall Algorithm: Architecture, Model Selection, Evaluation, and Optimization

DataFunTalk

Dec 27, 2022 · Artificial Intelligence

Efficient Training for Very Large‑Scale Face Recognition and the FFC Framework

This article reviews the challenges of ultra‑large‑scale face recognition, presents existing solutions such as metric learning, PFC and VFC, and details the proposed FFC framework with dual loaders, ID groups, probe and gallery networks, plus experimental results showing its cost‑effective performance.

AITraining Efficiencycomputer vision

0 likes · 7 min read

Efficient Training for Very Large‑Scale Face Recognition and the FFC Framework