Mar 3, 2022 · Artificial Intelligence

How Hierarchical Curriculum Learning Improves Dialogue Response Selection

This article explains how treating negative response candidates with varying difficulty through a hierarchical curriculum learning framework—combining corpus‑level and instance‑level curricula—enhances dialogue response selection models, backed by experiments on Douban, Ubuntu, and E‑Commerce datasets.

curriculum learningdialogue response selectionhierarchical learning

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How Hierarchical Curriculum Learning Improves Dialogue Response Selection

Tencent Cloud Developer

Mar 15, 2018 · Artificial Intelligence

Learning Long-Horizon Surgical Robot Tasks via Transition State Clustering, SWIRL, and DDCO

The article surveys three recent approaches—Transition State Clustering, Sequential Windowed Inverse Reinforcement Learning, and Deep Discovery of Continuous Options—that automatically segment long‑horizon surgical‑robot demonstrations into sub‑tasks, learn hierarchical policies from limited data, and achieve markedly higher success rates on da Vinci cutting, tension, and needle‑picking tasks.

Reinforcement LearningRoboticshierarchical learning

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Learning Long-Horizon Surgical Robot Tasks via Transition State Clustering, SWIRL, and DDCO