图 书 馆开课单位--伦敦大学学院
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111Exploiting Cluster Structure to Predict The Labeling of a Graph[利用聚类结构预测图的标号]
Mark Herbster(伦敦大学学院) The nearest neighbor and the perceptron algorithms are intuitively motivated by the aims to exploit the "cluster" and "linear separatio...
热度：22
Mark Herbster(伦敦大学学院) The nearest neighbor and the perceptron algorithms are intuitively motivated by the aims to exploit the "cluster" and "linear separatio...
热度：22
112Active Inference and Uncertainty[主动推理和不确定性]
Karl Friston(伦敦大学学院) In this presentation, I will rehearse the free-energy formulation of action and perception, with a special focus on the representation of uncertainty:...
热度：106
Karl Friston(伦敦大学学院) In this presentation, I will rehearse the free-energy formulation of action and perception, with a special focus on the representation of uncertainty:...
热度：106
113Employing The Complete Face in AVSR to Recover from Facial Occlusions[在AVSR中使用完整的面部咬合]
Ben Hall(伦敦大学学院) Existing Audio-Visual Speech Recognition (AVSR) systems visually focus intensely on a small region of the face, centred on the immediate mouth area. T...
热度：67
Ben Hall(伦敦大学学院) Existing Audio-Visual Speech Recognition (AVSR) systems visually focus intensely on a small region of the face, centred on the immediate mouth area. T...
热度：67
114Probabilistic graph partitioning[概率图分区]
David Barber(伦敦大学学院) We consider the problem of Graph Partitioning for applications in Web Mining and Collaborative Filtering. Our approach is based on predicting the pre...
热度：73
David Barber(伦敦大学学院) We consider the problem of Graph Partitioning for applications in Web Mining and Collaborative Filtering. Our approach is based on predicting the pre...
热度：73
115Objective Bayesian Nets for Breast Cancer Prognosis[目的是贝叶斯网络预测乳腺癌 ]
Sylvia Nagl(伦敦大学学院) According to objective Bayesianism, an agent’s degrees of belief should be determined by a probability function, out of all those that satisfy c...
热度：104
Sylvia Nagl(伦敦大学学院) According to objective Bayesianism, an agent’s degrees of belief should be determined by a probability function, out of all those that satisfy c...
热度：104
116Bayesian Inference of Mechanistic Systems Models Using Population MCMC[基于种群mcmc的机械系统模型贝叶斯推理 ]
Ben Calderhead(伦敦大学学院) We demonstrate how Population Markov Chain Monte Carlo techniques may be used to sample from the complex posterior distributions which arise when est...
热度：51
Ben Calderhead(伦敦大学学院) We demonstrate how Population Markov Chain Monte Carlo techniques may be used to sample from the complex posterior distributions which arise when est...
热度：51
117System Identification of Enzymatic Control Processes Using Population Monte Carlo Methods[基于群体蒙特卡罗方法的酶控制过程系统辨识 ]
Ben Calderhead(伦敦大学学院 ) We demonstrate the superiority of Population Monte Carlo techniques over standard Metropolis Markov Chain Monte Carlo (MCMC) methods for inferring opt...
热度：75
Ben Calderhead(伦敦大学学院 ) We demonstrate the superiority of Population Monte Carlo techniques over standard Metropolis Markov Chain Monte Carlo (MCMC) methods for inferring opt...
热度：75
118Dynamic Modelling of Microarray Data[微阵列数据的动态建模 ]
Martino Barenco(伦敦大学学院) We recently released rHVDM (Hidden Variable Dynamic Modelling), an R/Bioconductor package that predicts targets of a known transcription factor using ...
热度：37
Martino Barenco(伦敦大学学院) We recently released rHVDM (Hidden Variable Dynamic Modelling), an R/Bioconductor package that predicts targets of a known transcription factor using ...
热度：37
119Multi Period Information Retrieval and Optimal Relevance Feedback using Dynamic Programming[基于动态规划的多周期信息检索与最优相关反馈 ]
Marc Sloan(伦敦大学学院) In Multi Period Information Retrieval we consider retrieval as a stochastic yet controllable process, the ranking action during the process continuous...
热度：40
Marc Sloan(伦敦大学学院) In Multi Period Information Retrieval we consider retrieval as a stochastic yet controllable process, the ranking action during the process continuous...
热度：40
120Bayesian Online Event Detection[贝叶斯在线事件检测]
David Barber(伦敦大学学院) Distilled sensing is a multistage active learning procedure to detect events scattered across sites. We assume that at each stage the number of sites...
热度：80
David Barber(伦敦大学学院) Distilled sensing is a multistage active learning procedure to detect events scattered across sites. We assume that at each stage the number of sites...
热度：80