Journal ArticleDOI
Pattern Recognition and Machine Learning
Reads0
Chats0
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
More filters
Journal ArticleDOI
Functional annotations improve the predictive score of human disease-related mutations in proteins
TL;DR: SNPs&GO is an accurate method that, starting from a protein sequence, can predict whether a mutation is disease related or not by exploiting the protein functional annotation, and outperforms other available predictive methods.
Proceedings ArticleDOI
Improved Deep Embedded Clustering with Local Structure Preservation
TL;DR: The Improved Deep Embedded Clustering (IDEC) algorithm is proposed, which manipulates feature space to scatter data points using a clustering loss as guidance and can jointly optimize cluster labels assignment and learn features that are suitable for clustering with local structure preservation.
Proceedings ArticleDOI
Smart Devices are Different: Assessing and MitigatingMobile Sensing Heterogeneities for Activity Recognition
Allan Stisen,Henrik Blunck,Sourav Bhattacharya,Thor Siiger Prentow,Mikkel Baun Kjærgaard,Anind K. Dey,Tobias Sonne,Mads Møller Jensen +7 more
TL;DR: It is indicated that on-device sensor and sensor handling heterogeneities impair HAR performances significantly and a novel clustering-based mitigation technique suitable for large-scale deployment of HAR is proposed, where heterogeneity of devices and their usage scenarios are intrinsic.
Journal Article
Hubs in Space: Popular Nearest Neighbors in High-Dimensional Data
TL;DR: This paper explores a new aspect of the dimensionality curse, referred to as hubness, that affects the distribution of k-occurrences: the number of times a point appears among the k nearest neighbors of other points in a data set, which becomes considerably skewed as dimensionality increases.
Book ChapterDOI
An Introduction to Restricted Boltzmann Machines
TL;DR: This tutorial introduces RBMs as undirected graphical models as building blocks of multi-layer learning systems called deep belief networks based on Markov chain Monte Carlo methods.