(18)[ICML12] Building High-level Features Using Large Scale Unsupervised Learning
计划完成深度学习入门的126篇论文第十八篇，Andrew Y. Ng和Jeff Dean合做研究使用大量数据模型的无监督学习方式。 ABSTRACT&INTRODUCTION 摘要 咱们考虑仅从未标记的数据构建高级的、特定于类的特征检测器的问题。例如，是否能够只使用未标记的图像来学习人脸检测器？为了解决这个问题，咱们训练了一个9层局部链接的稀疏自动编码器，它具备对一个大的图像数据集(模型有10亿个
相关文章
- 1. Large-Scale Volumetric Scene Reconstruction using LiDAR
- 2. Large-scale Distance Metric Learning with Uncertainty
- 3. Large Scale Image Classification
- 4. 论文笔记之：Large Scale Distributed Semi-Supervised Learning Using Streaming Approximation
- 5. Deep Temporal Clustering: Fully unsupervised learning of time-domain features
- 6. [解读] Deep Clustering for Unsupervised Learning of Visual Features
- 7. Building a Book Recommender System using Restricted Boltzmann Machines
- 8. 学习笔记-Large scale machine learning
- 9. TensorFlow: A System for Large-Scale Machine Learning
- 10. Large Scale Metric Learning from Equivalence Constraints (KISSME)
- 更多相关文章...
- • PHP curl_version函数 - PHP参考手册
- • Maven Web 应用 - Maven教程
- • Java Agent入门实战（一）-Instrumentation介绍与使用
- • Java Agent入门实战（三）-JVM Attach原理与使用
相关标签/搜索
每日一句
-
每一个你不满意的现在，都有一个你没有努力的曾经。
最新文章
欢迎关注本站公众号,获取更多信息
相关文章
- 1. Large-Scale Volumetric Scene Reconstruction using LiDAR
- 2. Large-scale Distance Metric Learning with Uncertainty
- 3. Large Scale Image Classification
- 4. 论文笔记之：Large Scale Distributed Semi-Supervised Learning Using Streaming Approximation
- 5. Deep Temporal Clustering: Fully unsupervised learning of time-domain features
- 6. [解读] Deep Clustering for Unsupervised Learning of Visual Features
- 7. Building a Book Recommender System using Restricted Boltzmann Machines
- 8. 学习笔记-Large scale machine learning
- 9. TensorFlow: A System for Large-Scale Machine Learning
- 10. Large Scale Metric Learning from Equivalence Constraints (KISSME)