图 书 馆开课单位--马克斯普朗克研究所
1
2
3
4
5
6
7
8
9
10
1Machine Learning Summer Schools[机器学习暑期学校]
Gunnar Rätsch(马克斯普朗克研究所) Machine Learning Summer Schools
热度：27
Gunnar Rätsch(马克斯普朗克研究所) Machine Learning Summer Schools
热度：27
2Online Learning and Bregmann Divergences[在线学习与布雷格曼分歧]
Gunnar Rätsch(马克斯普朗克研究所) Online Learning and Bregmann Divergences
热度：20
Gunnar Rätsch(马克斯普朗克研究所) Online Learning and Bregmann Divergences
热度：20
3CoCo: Coding Cost for Parameter-free Outlier Detection[可可：编码参数的孤立点检测的成本]
Nikola Müller(马克斯普朗克研究所) How can we automatically spot all outstanding observations in a data set? This question arises in a large variety of applications, e.g. in economy, bi...
热度：59
Nikola Müller(马克斯普朗克研究所) How can we automatically spot all outstanding observations in a data set? This question arises in a large variety of applications, e.g. in economy, bi...
热度：59
4Streaming Hierarchical Video Segmentation[流式分层视频分割]
Bernt Schiele; David Forsyth(马克斯普朗克研究所) The use of video segmentation as an early processing step in video analysis lags behind the use of image segmentation for image analysis, despite many...
热度：99
Bernt Schiele; David Forsyth(马克斯普朗克研究所) The use of video segmentation as an early processing step in video analysis lags behind the use of image segmentation for image analysis, despite many...
热度：99
5Probability, Information Theory and Bayesian Inference[概率、信息论与贝叶斯推理]
Joaquin Quiñonero Candela(马克斯普朗克研究所)
热度：43
Joaquin Quiñonero Candela(马克斯普朗克研究所)
热度：43
6Introduction to bioinformatics[ 生物信息学概论 ]
Gunnar Rätsch(马克斯普朗克研究所) I will start by giving a general introduction into Bioinformatics, including basic biology, typical data types (sequences, structures, expression data...
热度：43
Gunnar Rätsch(马克斯普朗克研究所) I will start by giving a general introduction into Bioinformatics, including basic biology, typical data types (sequences, structures, expression data...
热度：43
7Helping doctors and patients make sense of health statistics: towards an evidence-based society[帮助医生和病人理解卫生统计：走向循证社会]
Gerd Gigerenzer(马克斯普朗克研究所) Collective statistical illiteracy is the phenomenon that the majority of people do not understand what health statistics mean, or even consistently dr...
热度：27
Gerd Gigerenzer(马克斯普朗克研究所) Collective statistical illiteracy is the phenomenon that the majority of people do not understand what health statistics mean, or even consistently dr...
热度：27
8Helping doctors and patients make sense of health statistics: towards an evidence-based society[帮助医生和病人理解卫生统计：走向循证社会]
Gerd Gigerenzer(马克斯普朗克研究所) Collective statistical illiteracy is the phenomenon that the majority of people do not understand what health statistics mean, or even consistently dr...
热度：33
Gerd Gigerenzer(马克斯普朗克研究所) Collective statistical illiteracy is the phenomenon that the majority of people do not understand what health statistics mean, or even consistently dr...
热度：33
9Homo heuristicus: Why biased minds make better inferences[人类启发：为什么有偏见的头脑会做出更好的推断]
Gerd Gigerenzer(马克斯普朗克研究所) Heuristics are efficient cognitive processes that ignore information. In contrast to the widely held view that less processing reduces accuracy, the s...
热度：46
Gerd Gigerenzer(马克斯普朗克研究所) Heuristics are efficient cognitive processes that ignore information. In contrast to the widely held view that less processing reduces accuracy, the s...
热度：46
10Phase transition in the family of p-resistances[p电阻族中的相变]
Morteza Alamgir(马克斯普朗克研究所) We study the family of p-resistances on graphs for p ≥ 1. This family generalizes the standard resistance distance. We prove that for any fixed gra...
热度：41
Morteza Alamgir(马克斯普朗克研究所) We study the family of p-resistances on graphs for p ≥ 1. This family generalizes the standard resistance distance. We prove that for any fixed gra...
热度：41