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Brian Hutchinson

Researcher at Western Washington University

Publications -  58
Citations -  1328

Brian Hutchinson is an academic researcher from Western Washington University. The author has contributed to research in topics: Deep learning & Language model. The author has an hindex of 15, co-authored 54 publications receiving 1032 citations. Previous affiliations of Brian Hutchinson include Microsoft & Pacific Northwest National Laboratory.

Papers
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Journal ArticleDOI

Tensor Deep Stacking Networks

Brian Hutchinson, +2 more
- 01 Aug 2013 - 
TL;DR: A sufficient depth of the T-DSN, a symmetry in the two hidden layers structure in each T- DSN block, the model parameter learning algorithm, and a softmax layer on top of T-DsN are shown to have all contributed to the low error rates observed in the experiments for all three tasks.
Proceedings ArticleDOI

Recurrent Neural Network Attention Mechanisms for Interpretable System Log Anomaly Detection

Andy Brown, +3 more
TL;DR: Recurrent neural network language models augmented with attention for anomaly detection in system logs are presented, creating opportunities for model introspection and analysis without sacrificing state-of-the art performance.
Posted Content

Deep Learning for Unsupervised Insider Threat Detection in Structured Cybersecurity Data Streams

Aaron Tuor, +4 more
- 02 Oct 2017 - 
TL;DR: In this paper, an online unsupervised deep learning approach is presented to detect anomalous network activity from system logs in real time, decomposing anomaly scores into the contributions of individual user behavior features for increased interpretability to aid analysts reviewing potential cases of insider threat.
Journal ArticleDOI

Deep Learning for Semantic Segmentation of Defects in Advanced STEM Images of Steels

Graham Roberts, +7 more
- 04 Sep 2019 - 
TL;DR: DefectSegNet - a new convolutional neural network architecture that performs semantic segmentation of three common crystallographic defects in structural alloys: dislocation lines, precipitates and voids is introduced, presenting a promising new workflow for fast and statistically meaningful quantification of materials defects.

Annotating Social Acts: Authority Claims and Alignment Moves in Wikipedia Talk Pages

Emily M. Bender, +7 more
TL;DR: The AAWD corpus, a collection of 365 discussions drawn from Wikipedia talk pages and annotated with labels capturing two kinds of social acts: alignment moves and authority claims, is presented.