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Journal ArticleDOI

Pattern Recognition and Machine Learning

Radford M. Neal
- 01 Aug 2007 - 
- Vol. 49, Iss: 3, pp 366-366
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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.

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Book ChapterDOI

Automatic Localization and Identification of Vertebrae in Arbitrary Field-of-View CT Scans

TL;DR: A new method for automatic localization and identification of vertebrae in arbitrary field-of-view CT scans based on regression forests and probabilistic graphical models, which is more general than previous work while being computationally efficient.
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Smartphone-based construction workers' activity recognition and classification

TL;DR: Smartphones are used in an unobtrusive way to capture body movements by collecting data using embedded accelerometer and gyroscope sensors and results indicate that neural networks outperform other classifiers by offering an accuracy ranging from 87% to 97% for user-dependent and 62% to 96% foruser-independent categories.
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Scalable Semi-Supervised Learning by Efficient Anchor Graph Regularization

TL;DR: A fast local anchor embedding method, which reformulates the optimization of local weights and obtains an analytical solution, and a new adjacency matrix among anchors by considering the commonly linked datapoints, which leads to a more effective normalized graph Laplacian over anchors.
Journal ArticleDOI

Multidimensional Projection for Visual Analytics: Linking Techniques with Distortions, Tasks, and Layout Enrichment

TL;DR: This survey provides detailed analysis and taxonomies as to the organization of MDP techniques according to their main properties and traits, discussing the impact of such properties for visual perception and other human factors and providing future research axes to fill discovered gaps in this domain.