开课单位--加州大学
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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:12
Elena Glassman(加州大学) Human-Centered Clustering and Visualisation of Student Solutions for Personalized Feedback at Scale
热度:12
![](functions/showpic.php?filename=2022111610385374.png)
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:24
Martin J. Wainwright(加州大学) Graphical Models, Variational Methods, and Message-Passing
热度:24
![](functions/showpic.php?filename=2022111305405588.png)
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
Michael I. Jordan(加州大学) Bayesian or Frequentist, Which Are You?
热度:15
![](functions/showpic.php?filename=2022111109133093.png)
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:24
Martin J. Wainwright(加州大学) Graphical Models and message-passing algorithms
热度:24
![](functions/showpic.php?filename=2020111609192499.png)
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:80
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:80
![](functions/showpic.php?filename=2019031208570273.png)
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:106
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:106
![](functions/showpic.php?filename=2021052809272115.png)
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:29
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:29
![](functions/showpic.php?filename=2021052803350252.png)
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:39
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:39
![](functions/showpic.php?filename=2021032709045766.png)
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:35
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:35
![](functions/showpic.php?filename=2021040707283640.png)
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:35
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:35