开课单位--天普大学
1 1/1

1
Randomization or Condensation? Linear­Cost Matrix Sketching Via Cascaded Compression Sampling[随机化还是压缩？通过级联压缩采样绘制 LinearCost 矩阵草图]
  Kai Zhang(天普大学) Matrix sketching is aimed at finding compact representations of a matrix while simultaneously preserving most of its properties, which is a fundamenta...
热度：19

2
An Object Co-occurrence Assisted Hierarchical Model for Scene Understanding[一个对象共生辅助分层模型的场景理解]
  Xin Li(天普大学) Hierarchical methods have been widely explored for object recognition, which is a critical component of scene understanding. However, few existing wor...
热度：92

3
Improved Nystrom Low-Rank Approximation and Error Analysis[改良Nystrom低秩逼近及其误差分析]
  Kai Zhang(天普大学) Low-rank matrix approximation is an effective tool in alleviating the memory and computational burdens of kernel methods and sampling, as the mainstre...
热度：95

4
Learning from Inconsistent and Unreliable Annotators by a Gaussian Mixture Model and Bayesian Information Criterion[通过高斯混合模型和贝叶斯信息准则从不一致和不可靠的注释者学习]
  Zoran Obradovic(天普大学) Supervised learning from multiple annotators is an increasingly important problem in machine leaning and data mining. This paper develops a probabilis...
热度：65

5
Cross Language Text Classification via Multi-view Subspace Learning[通过多视角的子空间学习跨语言文本分类]
  Yuhong Guo(天普大学) Cross language classification is an important task in multilingual learning, aiming for reducing the labeling cost of training a different classificat...
热度：47

6
Tracking Concept Change with Incremental Boosting by Minimization of the Evolving Exponential Loss[跟踪概念的变化与增量提高的不断变化的指数损失]
  Mihajlo Grbovic(天普大学) Fault localization, i.e., identifying erroneous lines of code in a buggy program, is a tedious process, which often requires considerable manual effor...
热度：34
1 1/1