图 书 馆开课单位--阿尔托大学
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31Detecting similar high-dimensional responses to experimental factors from human and model organism[检测人体和模型生物体对实验因素的类似高维反应 ]
Tommi Suvitaival(阿尔托大学) We present a Bayesian model for analysing the effect of multiple experimental factors in two-species studies without the requirement of a priori known...
热度：32
Tommi Suvitaival(阿尔托大学) We present a Bayesian model for analysing the effect of multiple experimental factors in two-species studies without the requirement of a priori known...
热度：32
32Multi-source Survival analysis[多源生存分析 ]
Ali Faisal(阿尔托大学) Cancers are complex diseases, characterized by genomic changes at multiple levels of regulation. We present an integrative genome-wide approach that c...
热度：58
Ali Faisal(阿尔托大学) Cancers are complex diseases, characterized by genomic changes at multiple levels of regulation. We present an integrative genome-wide approach that c...
热度：58
33Multi-Way, Multi-View Learning[多途径、多视角学习 ]
Ilkka Huopaniemi(阿尔托大学) We extend multi-way, multivariate ANOVA-type analysis to cases where one covariate is the view, with features of each view coming from different, hig...
热度：44
Ilkka Huopaniemi(阿尔托大学) We extend multi-way, multivariate ANOVA-type analysis to cases where one covariate is the view, with features of each view coming from different, hig...
热度：44
34Infinite mixtures for multi-relational categorical data[用于多关系分类数据的无限混合]
Janne Sinkkonen(阿尔托大学) Large relational datasets are prevalent in many fields. We propose an unsupervised component model for relational data, i.e., for heterogeneous c...
热度：43
Janne Sinkkonen(阿尔托大学) Large relational datasets are prevalent in many fields. We propose an unsupervised component model for relational data, i.e., for heterogeneous c...
热度：43
35Learning Shared and Separate Features of Two Related Data Sets using GPLVMs[使用GPLVM学习两个相关数据集的共享和单独特征]
Gayle Leen(阿尔托大学) Dual source learning problems can be formulated as learning a joint representation of the data sources, where the shared information is represented i...
热度：58
Gayle Leen(阿尔托大学) Dual source learning problems can be formulated as learning a joint representation of the data sources, where the shared information is represented i...
热度：58
36Decoding underlying behaviour from destructive time series experiments through Gaussian process models[通过高斯过程模型从破坏性时间序列实验中解码潜在行为 ]
Antti Honkela(阿尔托大学) A major problem for biological time series is that often experiments (such as gene expression measurements using microarrays or RNA-seq) require the o...
热度：54
Antti Honkela(阿尔托大学) A major problem for biological time series is that often experiments (such as gene expression measurements using microarrays or RNA-seq) require the o...
热度：54
37Fast Discriminative Component Analysis for Comparing Examples[比较实例的快速判别成分分析 ]
Jaakko Peltonen(阿尔托大学) Two recent methods, Neighborhood Components Analysis (NCA) and Informative Discriminant Analysis (IDA), search for a class-discriminative subspace or...
热度：83
Jaakko Peltonen(阿尔托大学) Two recent methods, Neighborhood Components Analysis (NCA) and Informative Discriminant Analysis (IDA), search for a class-discriminative subspace or...
热度：83
38Tell Me Something I Don't Know: Randomization Strategies for Iterative Data Mining[告诉我一些我不知道的事情：迭代数据挖掘的随机化策略 ]
Sami Hanhijärvi(阿尔托大学) There is a wide variety of data mining methods available, and it is generally useful in exploratory data analysis to use many different methods for th...
热度：50
Sami Hanhijärvi(阿尔托大学) There is a wide variety of data mining methods available, and it is generally useful in exploratory data analysis to use many different methods for th...
热度：50
39HealthFinland - Finnish Health Information on the Semantic Web[HealthFinland-语义网站上的芬兰的健康信息 ]
Eero Hyvonen(阿尔托大学 ) This talk shows how semantic web techniques can be applied to solving problems of distributed content creation, discovery, linking, aggregation, and r...
热度：33
Eero Hyvonen(阿尔托大学 ) This talk shows how semantic web techniques can be applied to solving problems of distributed content creation, discovery, linking, aggregation, and r...
热度：33
40Dependency Modelling Toolbox[依赖关系建模工具箱]
Leo Lahti(阿尔托大学) Investigation of dependencies between multiple data sources allows the discovery of regularities and interactions that are not seen in individual data...
热度：43
Leo Lahti(阿尔托大学) Investigation of dependencies between multiple data sources allows the discovery of regularities and interactions that are not seen in individual data...
热度：43