(18)[ICML12] Building High-level Features Using Large Scale Unsupervised Learning
計劃完成深度學習入門的126篇論文第十八篇，Andrew Y. Ng和Jeff Dean合做研究使用大量數據模型的無監督學習方式。 ABSTRACT&INTRODUCTION 摘要 咱們考慮僅從未標記的數據構建高級的、特定於類的特徵檢測器的問題。例如，是否能夠只使用未標記的圖像來學習人臉檢測器？爲了解決這個問題，咱們訓練了一個9層局部鏈接的稀疏自動編碼器，它具備對一個大的圖像數據集(模型有10億個
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相關文章
- 1. Large-Scale Volumetric Scene Reconstruction using LiDAR
- 2. Large-scale Distance Metric Learning with Uncertainty
- 3. Large Scale Image Classification
- 4. 論文筆記之：Large Scale Distributed Semi-Supervised Learning Using Streaming Approximation
- 5. Deep Temporal Clustering: Fully unsupervised learning of time-domain features
- 6. [解讀] Deep Clustering for Unsupervised Learning of Visual Features
- 7. Building a Book Recommender System using Restricted Boltzmann Machines
- 8. 學習筆記-Large scale machine learning
- 9. TensorFlow: A System for Large-Scale Machine Learning
- 10. Large Scale Metric Learning from Equivalence Constraints (KISSME)