图 书 馆开课单位--赫尔辛基大学
21
22
23
24
25
26
27
28
29
30
21Independent Component Analysis[独立成分分析]
Aapo Hyvärinen(赫尔辛基大学) In independent component analysis (ICA), the purpose is to linearly decompose a multidimensional data vector into components that are as statistically...
热度：132
Aapo Hyvärinen(赫尔辛基大学) In independent component analysis (ICA), the purpose is to linearly decompose a multidimensional data vector into components that are as statistically...
热度：132
22Efficient Multiple-Click Models in Web Search[网络搜索中的高效多点击模型]
Chao Liu, Fan Guo, Yi-Min Wang(赫尔辛基大学)
热度：40
Chao Liu, Fan Guo, Yi-Min Wang(赫尔辛基大学)
热度：40
2324Causal Modelling Combining Instantaneous and Lagged Effects: an Identifiable Model Based on Non-Gaussianity[因果模型结合瞬时和滞后效应：基于非高斯的识别模型]
Aapo Hyvärinen(赫尔辛基大学) Causal analysis of continuous-valued variables typically uses either autoregressive models or linear Gaussian Bayesian networks with instantaneous eff...
热度：29
Aapo Hyvärinen(赫尔辛基大学) Causal analysis of continuous-valued variables typically uses either autoregressive models or linear Gaussian Bayesian networks with instantaneous eff...
热度：29
25Efficient max-margin Markov learning via conditional gradient and probabilistic inference[基于条件梯度和概率推理的马尔可夫学习效率最大化]
Juho Rousu(赫尔辛基大学) We present a general and efficient optimisation methodology for for max-margin sructured classification tasks. The efficiency of the method relies on ...
热度：31
Juho Rousu(赫尔辛基大学) We present a general and efficient optimisation methodology for for max-margin sructured classification tasks. The efficiency of the method relies on ...
热度：31
26Estimation of human endogeneous retrovirus activities from expressed sequence databases[表达序列数据库内的人类内源性逆转录病毒活性的估计]
Merja Oja(赫尔辛基大学) Human endogenous retroviruses (HERVs) are remnants of ancient retrovirus infections and now reside within the human DNA. Recently HERV expression has ...
热度：42
Merja Oja(赫尔辛基大学) Human endogenous retroviruses (HERVs) are remnants of ancient retrovirus infections and now reside within the human DNA. Recently HERV expression has ...
热度：42
27Multilabel prediction of drug activity[药物活性的多标签预测]
Juho Rousu(赫尔辛基大学) Machine learning has become increasingly important in drug discovery where viable molecular structures are searched or designed for therapeutic effica...
热度：38
Juho Rousu(赫尔辛基大学) Machine learning has become increasingly important in drug discovery where viable molecular structures are searched or designed for therapeutic effica...
热度：38
28Sigma point and particle approximations of stochastic differential equations in optimal filtering[Σ最优滤波中的随机微分方程的Σ点和近似粒子]
Simo Särkkä(赫尔辛基大学) The unscented transform (UT) is a relatively recent method for approximating non-linear transformations of random variables. Instead of the classical ...
热度：51
Simo Särkkä(赫尔辛基大学) The unscented transform (UT) is a relatively recent method for approximating non-linear transformations of random variables. Instead of the classical ...
热度：51
29Randomization Methods in Data Mining[数据挖掘中的随机化方法]
Heikki Mannila(赫尔辛基大学) Data mining research has developed many algorithms for various analysis tasks on large and complex datasets. However, assessing the significance of da...
热度：53
Heikki Mannila(赫尔辛基大学) Data mining research has developed many algorithms for various analysis tasks on large and complex datasets. However, assessing the significance of da...
热度：53
30Structured Output Prediction of Enzyme Function via Reaction Kernels[通过反应核实现酶功能的结构化输出预测]
Juho Rousu(赫尔辛基大学) Enzyme function prediction is an important problem in post-genomic bioinformatics. There are two general methods for solving the problem: transfer of ...
热度：44
Juho Rousu(赫尔辛基大学) Enzyme function prediction is an important problem in post-genomic bioinformatics. There are two general methods for solving the problem: transfer of ...
热度：44