Journal ArticleDOI
Pattern Recognition and Machine Learning
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TLDR
This book covers a broad range of topics for regular factorial designs and presents all of the material in very mathematical fashion and will surely become an invaluable resource for researchers and graduate students doing research in the design of factorial experiments.Abstract:
(2007). Pattern Recognition and Machine Learning. Technometrics: Vol. 49, No. 3, pp. 366-366.read more
Citations
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Journal ArticleDOI
Training restricted Boltzmann machines
Asja Fischer,Christian Igel +1 more
TL;DR: This tutorial introduces RBMs from the viewpoint of Markov random fields, starting with the required concepts of undirected graphical models and reviewing the state-of-the-art in training restricted Boltzmann machines from the perspective of graphical models.
Journal ArticleDOI
Computational anatomy with the SPM software.
TL;DR: An overview of computational procedures for examining neuroanatomical variability is presented, and volumetry is discussed, with an emphasis on voxel-based morphometry, and the pre-processing steps involved using the SPM software.
Book
Handbook of Functional MRI Data Analysis
TL;DR: This book provides background about the methods employed by common data analysis packages including FSL, SPM and AFNI, and some of the newest cutting-edge techniques, including pattern classification analysis, connectivity modeling and resting state network analysis.
Posted Content
Deep Learning of Representations: Looking Forward
TL;DR: In this paper, the authors examine some of the challenges of scaling deep learning algorithms to much larger models and datasets, reducing optimization difficulties due to ill-conditioning or local minima, designing more efficient and powerful inference and sampling procedures, and learning to disentangle the factors of variation underlying the observed data.
Proceedings ArticleDOI
A dirichlet multinomial mixture model-based approach for short text clustering
Jianhua Yin,Jianyong Wang +1 more
TL;DR: This paper proposed a collapsed Gibbs Sampling algorithm for the Dirichlet Multinomial Mixture model for short text clustering and found that GSDMM can infer the number of clusters automatically with a good balance between the completeness and homogeneity of the clustering results, and is fast to converge.