图 书 馆开课单位--柏林工业大学
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11Probabilistic and Bayesian Modelling I[概率和贝叶斯模型1]
Manfred Opper(柏林工业大学) 有从各种不同的应用程序中的复杂数据的可用性大幅增长。数据分析器的挑战是通过识别有用的形状和结构是突出来提取原始数据的知识。该模块介绍了自适应和概率的方...
热度：39
Manfred Opper(柏林工业大学) 有从各种不同的应用程序中的复杂数据的可用性大幅增长。数据分析器的挑战是通过识别有用的形状和结构是突出来提取原始数据的知识。该模块介绍了自适应和概率的方...
热度：39
12Learning interpretable SVMs for biological sequence classification[支持向量机学习解释为生物序列分类]
Sören Sonnenburg(柏林工业大学) Top » Computer Science » Machine Learning » Kernel Methods » Support Vector Machines
热度：47
Sören Sonnenburg(柏林工业大学) Top » Computer Science » Machine Learning » Kernel Methods » Support Vector Machines
热度：47
13The Machine Learning Approach to Brain-Computer Interfacing - Part 1[脑机接口的机器学习方法1]
Klaus-Robert Müller(柏林工业大学) The Machine Learning Approach to Brain-Computer Interfacing - Part 1
热度：61
Klaus-Robert Müller(柏林工业大学) The Machine Learning Approach to Brain-Computer Interfacing - Part 1
热度：61
14Introduction and overwiew of the Machine Learning Open Source Software workshop[机器学习软件研讨会的介绍和概述]
Sören Sonnenburg(柏林工业大学) We believe that the wide-spread adoption of open source software policies will have a tremendous ipact on the field of machine learning. The goal of t...
热度：72
Sören Sonnenburg(柏林工业大学) We believe that the wide-spread adoption of open source software policies will have a tremendous ipact on the field of machine learning. The goal of t...
热度：72
15Denoising and Dimension Reduction in Feature Space[去噪和降维的特征空间]
Klaus-Robert Müller;Mikio Braun(柏林工业大学) The talk presents recent work that interestingly complements our understanding the VC picture in kernel based learning. Our finding is that the releva...
热度：77
Klaus-Robert Müller;Mikio Braun(柏林工业大学) The talk presents recent work that interestingly complements our understanding the VC picture in kernel based learning. Our finding is that the releva...
热度：77
1617Hierarchical POMDP Controller Optimization by Likelihood Maximization[分层POMDP控制器优化的可能性最大化]
Marc Toussaint(柏林工业大学) Planning can often be simplified by decomposing the task into smaller tasks arranged hierarchically. Charlin et al. recently showed that the hierarchy...
热度：48
Marc Toussaint(柏林工业大学) Planning can often be simplified by decomposing the task into smaller tasks arranged hierarchically. Charlin et al. recently showed that the hierarchy...
热度：48
18Approximate Inference Control [近似推理控制]
Marc Toussaint(柏林工业大学) Approximate Inference Control (AICO) is a method for solving Stochastic Optimal Control (SOC) problems. The general idea is to think of control as the...
热度：33
Marc Toussaint(柏林工业大学) Approximate Inference Control (AICO) is a method for solving Stochastic Optimal Control (SOC) problems. The general idea is to think of control as the...
热度：33
1920Stationary Subspace Analysis[静止的子空间分析]
Klaus-Robert Müller; Paul von Bunau;Frank C. Meinecke(柏林工业大学) Non-stationarities are an ubiquitous phenomenon in real-world data, yet they challenge standard Machine Learning methods: if training and test distrib...
热度：89
Klaus-Robert Müller; Paul von Bunau;Frank C. Meinecke(柏林工业大学) Non-stationarities are an ubiquitous phenomenon in real-world data, yet they challenge standard Machine Learning methods: if training and test distrib...
热度：89