开课单位--马克斯普朗克研究所

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Opening of the 9th Machine Learning Summer School[第九机器学习的暑期学校开放]
  Bernhard Schölkopf(马克斯普朗克研究所) Top » Computer Science » Machine Learning  
热度:92

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Fast projections onto l1,q-norm balls for grouped feature selection[快速预测到L1范数,Q球组合特征选择]
  Suvrit Sra(马克斯普朗克研究所) Joint sparsity is widely acknowledged as a powerful structural cue for performing feature selection in setups where variables are expected to demonstr...
热度:96

53
Testing Complexity Measures on Symbolic Dynamics of Coupled Tent Maps[对耦合帐篷映射的符号动力学测试的复杂性措施]
  Thomas Kahle(马克斯普朗克研究所) We evaluate new complexity measures on the symbolic dynamics of coupled tent maps. These measures embody the idea to quantify complexity in terms of k...
热度:40

54
Lectures on Clustering[关于聚类的讲座]
  Ulrike von Luxburg(马克斯普朗克研究所) These lectures give an introduction to data clustering: we discuss a few algorithms, but also look at theoretical questions related to clustering. \\*...
热度:136

55
Throttling Poisson Processes[节流泊松过程]
  Uwe Dick(马克斯普朗克研究所) We study a setting in which Poisson processes generate sequences of decision-making events. The optimization goal is allowed to depend on the rate of ...
热度:26

56
SOFIE: Self-Organizing Flexible Information Extraction[SOFIE:自组织柔性信息抽取]
  Mauro Sozio, Fabian M. Suchanek, Gerhard Weikum(马克斯普朗克研究所) This paper presents SOFIE, a system that can extend an existing ontology by new facts. SOFIE provides a integrative framework, in which information ex...
热度:67

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Deep sequencing and systems biology: steps on the way to an individualised treatment of cancer patients[深度测序和系统生物学:对癌症患者的个性化治疗的方法步骤]
  Hans Lehrach(马克斯普朗克研究所) Biological processes are driven by complex networks of interactions between molecular and cellular components. Predicting the outcome of potential dis...
热度:47

58
Introduction to Boosting[介绍了提高]
  Gunnar Rätsch(马克斯普朗克研究所) This course provides an introduction to theoretical and practical aspects of Boosting and Ensemble Learning. I will begin with a short description of ...
热度:40

59
Introduction by the Organizer[主办单位介绍]
  Philipp Hennig(马克斯普朗克研究所) Probabilistic Numerics: 1.Numerical Analysis is Inference. Being uncertain about deterministic problems 2.Example. 3.Numerical Analysis is no...
热度:25

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Evaluation of the Topological and Morphological Characteristics of the LSS During Evolution Process by Means of Minkowski Functionals[在进化过程中用闵可夫斯基函数对低边驱动器的拓扑和形态特征进行评价]
  Irina Sidorenko(马克斯普朗克研究所) We study the topology of the cosmic Large-Scale Structures (LSS) produced by Millennium simulations (Springel , V. et al., 2005, Nature 432, 629) by m...
热度:57