开课单位--加州大学

11
Human-Centered Clustering and Visualisation of Student Solutions for Personalized Feedback at Scale[面向大规模个性化反馈的以人为中心的聚类和可视化学生解决方案]
  Elena Glassman(加州大学) Human-Centered Clustering and Visualisation of Student Solutions for Personalized Feedback at Scale
热度：11

12
Graphical Models, Variational Methods, and Message-Passing[图形模型、变分方法和消息传递]
  Martin J. Wainwright(加州大学) Graphical Models, Variational Methods, and Message-Passing
热度：21

13
Bayesian or Frequentist, Which Are You?[贝叶斯还是频率主义者，你是哪一个?]
   Michael I. Jordan(加州大学) Bayesian or Frequentist, Which Are You?
热度：15

14
Graphical Models and message-passing algorithms[图形模型和消息传递算法]
  Martin J. Wainwright(加州大学) Graphical Models and message-passing algorithms
热度：20

15
Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials[高斯边势全连通crf的有效推理]
   Philipp Krähenbühl(加州大学) Most state-of-the-art techniques for multi-class image segmentation and labeling use conditional random fields defined over pixels or image regions. W...
热度：78

16
Layered Object Detection for Multi-Class Segmentation[多类分割的分层目标检测]
  Sam Hallman(加州大学) We formulate a layered model for object detection and multi-class segmentation. Our system uses the output of a bank of object detectors in order to d...
热度：104

17
What Helps Where - And Why? Semantic Relatedness for Knowledge Transfer[在哪里有什么帮助？为什么？知识转移中的语义关联]
  Marcus Rohrbach(加州大学) Remarkable performance has been reported to recognize single object classes. Scalability to large numbers of classes however remains an important chal...
热度：27

18
From Practice to Theory in Learning from Massive Data[从大量数据中学习从实践到理论]
  Charles Elkan(加州大学) This talk will discuss examples of how Amazon applies machine learning to large-scale data, and open research questions inspired by these applications...
热度：33

19
Od prvih galaksij do temne snovi: Življenjepis našega vesolja[从第一个星系到暗物质：我们宇宙的传记]
  Maruša Bradač(加州大学) Ljudje smo se od nekdaj spraševali, od kod smo in kam gremo. V tem pogovoru bomo razkrili, kako astronomi vidimo začetke nastanka galaksij in k...
热度：34

20
Do We Need More Training Data or Better Models for Object Detection?[我们需要更多的训练数据还是更好的目标检测模型？]
   Charless C. Fowlkes(加州大学) Datasets for training object recognition systems are steadily growing in size. This paper investigates the question of whether existing detectors will...
热度：31