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
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Journal ArticleDOI
Computational Fact Checking from Knowledge Networks
Giovanni Luca Ciampaglia,Prashant Shiralkar,Luis M. Rocha,Luis M. Rocha,Johan Bollen,Filippo Menczer,Alessandro Flammini +6 more
TL;DR: It is shown that the complexities of human fact checking can be approximated quite well by finding the shortest path between concept nodes under properly defined semantic proximity metrics on knowledge graphs.
Journal ArticleDOI
A Survey of Urban Reconstruction
Przemyslaw Musialski,Przemyslaw Musialski,Peter Wonka,Peter Wonka,Daniel G. Aliaga,Michael Wimmer,Luc Van Gool,Luc Van Gool,Werner Purgathofer +8 more
TL;DR: The goal is to provide a survey that will help researchers to better position their own work in the context of existing solutions, and to help newcomers and practitioners in computer graphics to quickly gain an overview of this vast field.
Journal ArticleDOI
An Overview on Application of Machine Learning Techniques in Optical Networks
Francesco Musumeci,Cristina Rottondi,Avishek Nag,Irene Macaluso,Darko Zibar,Marco Ruffini,Massimo Tornatore +6 more
TL;DR: An overview of the application of ML to optical communications and networking is provided, relevant literature is classified and surveyed, and an introductory tutorial on ML is provided for researchers and practitioners interested in this field.
Proceedings ArticleDOI
On-line LDA: Adaptive Topic Models for Mining Text Streams with Applications to Topic Detection and Tracking
TL;DR: A topic model that automatically captures the thematic patterns and identifies emerging topics of text streams and their changes over time and is comparable to, and sometimes better than, the original LDA in predicting the likelihood of unseen documents.
Journal ArticleDOI
Using control genes to correct for unwanted variation in microarray data
TL;DR: A new method, intended for use in differential expression studies, that attempts to overcome the problem of unwanted variation by restricting the factor analysis to negative control genes, and finds that RUV-2 performs as well or better than other methods.