Meta-Learning and Cross-Domain Recommendation: Industrial Practices at Tencent TRS

This article presents Tencent TRS's industrial practice of applying meta‑learning and cross‑domain recommendation to address personalization challenges, detailing problem definitions, solution architectures, algorithmic choices such as MAML, deployment strategies, and the cost‑effective outcomes achieved across multiple scenarios.

Industrial AIMAMLMeta Learning

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Meta-Learning and Cross-Domain Recommendation: Industrial Practices at Tencent TRS

DataFunTalk

Jul 6, 2023 · Artificial Intelligence

Industrial Practice of Meta‑Learning and Cross‑Domain Recommendation in Tencent TRS

This article presents Tencent TRS's industrial deployment of meta‑learning and cross‑domain recommendation, detailing problem definitions, solution architectures, challenges of industrialization, and practical implementations that achieve personalized modeling and cost‑effective multi‑scene recommendation across various online services.

Industrial AIMAMLRecommendation Systems

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Industrial Practice of Meta‑Learning and Cross‑Domain Recommendation in Tencent TRS

Network Intelligence Research Center (NIRC)

Jul 4, 2023 · Artificial Intelligence

FedMRL: Federated Meta Reinforcement Learning for Cold-Start Slice Resource Management

FedMRL tackles the cold‑start problem of network‑slice resource orchestration by combining federated learning with meta‑reinforcement learning, using a two‑loop training process that preserves SP data privacy and consistently outperforms TUNE, TDSC, and IOSP across diverse 6G network conditions.

6GFederated LearningMAML

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FedMRL: Federated Meta Reinforcement Learning for Cold-Start Slice Resource Management

DataFunTalk

Dec 30, 2020 · Artificial Intelligence

Meta-Dialog System: Using Meta-Learning for Fast Adaptation and Robustness in Task-Oriented Conversational AI

This article presents a meta‑learning based end‑to‑end task‑oriented dialogue system that quickly adapts to new scenarios with limited data and improves robustness through a human‑machine collaboration decision module, validated on extended‑bAbI benchmarks and real‑world Alibaba Cloud customer‑service applications.

Few‑Shot LearningMAMLdialogue system

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Meta-Dialog System: Using Meta-Learning for Fast Adaptation and Robustness in Task-Oriented Conversational AI