深度学习——Hinton公开课 Optimization: How to make the learning go faster 深度学习——Hinton公开课 Recurrent neural networks
这节课讲了为什么要综合多个模型,好处与原理、具体做法等。讲解了贝叶斯学习中的神经网络模型混合、马尔科夫蒙特卡洛方法,以及从新角度阐释更高效的Dropout。 综合网络:偏置方差均衡 训练数据少,容易过拟合。综合多个模型可以防止过拟合,特别是当模型做出的预测差别很大的时候。 对回归来讲,平方误差可以分解为偏置与方差两...
neural network designmultiple network combinationgenetic algorithmhandwritten numeral recognitionThe concept of combining neural networks has been recently exploited as a new direction for the development of highly reliable systems in the area of artificial neural networks. This paper presents two useful ...
In this paper, we propose a weakly supervised framework, which combines multiple-instance learning with a hybrid deep neural network and uses-mer encoding to transform DNA sequences, for modelingprotein-DNA binding. Firstly, this framework segments sequences into multiple overlapping instances using a...
Summary: In this paper we present neuro-evolution of neural network controllers for mobile agents in a simulated environment. The controller is obtained through evolution of hypercube encoded weights of recurrent neural networks (HyperNEAT). The simulated agent's goal is to find a target in a shor...
neural networks 12, 181–201 (2001). 19. Agresti, A. Categorical Data Analysis. (Wiley, 2002). 20. Moskvina, V. & Schmidt, K. M. On multiple-testing correction in genome-wide association studies. Genet. Epidemiol. 32, 567–573 (2008). 21. Dickhaus, T. & Stange, J. Multiple ...
关键词: CiteSeerX citations Combining multiple knowledge sources for discourse segmentation D J Litman R J Passonneau 被引量: 196 摘要: We predict discourse segment boundaries from linguistic features of utterances, using a corpus of spoken narratives as data. We present two methods for developing...
A multi-feature and combining multiple classifiers method for facial expression recognition was proposed.First,three features are obtained from pre-processed face images by three different feature extraction methods.Then different classifiers are made based on different features.At last,a model of combinin...
1)使用共有信息mutual information来定义数据分区之间的相似性,进而衡量合并后的聚类(combined partition P*)与原始的聚类集(clustering ensemble)之间的一致性。 2)通过bootstrapsing技术评估EAC算法的鲁棒性。 2.3基于K均值算法的数据分区组合 利用K均值算法,通过改变参数K以初始化聚类集,然后根据EAC算法(EAC与单连接...
Neural networks are one of the widely-used time series forecasting methods in time series applications. Among different neural network architectures and learning algorithms, the most popular choice is the feedforward Multilayer Perceptron (MLP). However, it suffers from some drawbacks such as getting ...