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Building a scalable machine learning system for unsupervised anomaly detection via representation learning is highly desirable.
The MNIST database of handwritten digits
Yann LeCun · 1998
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The information bottleneck method
Naftali Tishby, Fernando C Pereira, and William Bialek · 2000
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Estimating the support of a high-dimensional distribution
Bernhard Schölkopf, John C Platt, John Shawe-Taylor, Alex J Smola, and Robert C Williamson · 2001
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Outlier detection using replicator neural networks
Simon Hawkins, Hongxing He, Graham Williams, and Rohan Baxter · 2002
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Rate-distortion theory
Toby Berger · 2003
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Support vector data description
David MJ Tax and Robert PW Duin · 2004
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Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion
Pascal Vincent, Hugo Larochelle, Isabelle Lajoie, Yoshua Bengio, and Pierre-Antoine Manzagol · 2010
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Adaptive subgradient methods for online learning and stochastic optimization
John Duchi, Elad Hazan, and Yoram Singer · 2011
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Stacked convolutional auto-encoders for hierarchical feature extraction
Jonathan Masci, Ueli Meier, Dan Cireşan, and Jürgen Schmidhuber · 2011
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The variance drain and Jensen’s inequality
Robert A Becker · 2012
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Auto-encoding variational Bayes
Diederik P Kingma and Max Welling · 2013
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Anomaly detection using autoencoders with nonlinear dimensionality reduction
Mayu Sakurada and Takehisa Yairi · 2014
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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Dropout: a simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov · 2014
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Anomaly detection using replicator neural networks trained on examples of one class
Hoang Anh Dau, Vic Ciesielski, and Andy Song · 2014
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
Cited alongside, same era.
The CIFAR-10 dataset
Alex Krizhevsky, Vinod Nair, and Geoffrey Hinton · 2014
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Variational autoencoder based anomaly detection using reconstruction probability
Jinwon An and Sungzoon Cho · 2015
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A novel approach for automatic acoustic novelty detection using a denoising autoencoder with bidirectional LSTM neural networks
Erik Marchi, Fabio Vesperini, Florian Eyben, Stefano Squartini, and Björn Schuller · 2015
Cited alongside, same era.
Deep learning and the information bottleneck principle
Unsupervised anomaly detection with generative adversarial networks to guide marker discovery
Thomas Schlegl, Philipp Seeböck, Sebastian M Waldstein, Ursula Schmidt-Erfurth, and Georg Langs · 2017
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Fashion-MNIST: a novel image dataset for benchmarking machine learning algorithms
Han Xiao, Kashif Rasul, and Roland Vollgraf · 2017
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Deep one-class classification
Lukas Ruff, Robert Vandermeulen, Nico Goernitz, Lucas Deecke, Shoaib Ahmed Siddiqui, Alexander Binder, Emmanuel Müller, and Marius Kloft · 2018
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Understanding disentangling in β \beta -VAE
Christopher P Burgess, Irina Higgins, Arka Pal, Loic Matthey, Nick Watters, Guillaume Desjardins, and Alexander Lerchner · 2018
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Hyunjik Kim and Andriy Mnih · 2018
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Naftali Tishby and Noga Zaslavsky · 2015
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Dropout as a Bayesian approximation: Representing model uncertainty in deep learning
Yarin Gal and Zoubin Ghahramani · 2015
Cited alongside, same era.
Alireza Makhzani, Jonathon Shlens, Navdeep Jaitly, Ian Goodfellow, and Brendan Frey · 2015
Cited alongside, same era.
ELBO surgery: yet another way to carve up the variational evidence lower bound
Matthew D Hoffman and Matthew J Johnson · 2016
Cited alongside, same era.
A baseline for detecting misclassified and out-of-distribution examples in neural networks
Dan Hendrycks and Kevin Gimpel · 2016
Cited alongside, same era.
Anomaly detection with robust deep autoencoders
Chong Zhou and Randy C Paffenroth · 2017
Cited alongside, same era.
Alexander A Alemi, Ben Poole, Ian Fischer, Joshua V Dillon, Rif A Saurous, and Kevin Murphy · 2017
Cited alongside, same era.
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Optimization methods for large-scale machine learning
Léon Bottou, Frank E Curtis, and Jorge Nocedal · 2018
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Anomaly detection using one-class neural networks
Raghavendra Chalapathy, Aditya Krishna Menon, and Sanjay Chawla · 2018
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Generative probabilistic novelty detection with adversarial autoencoders
Stanislav Pidhorskyi, Ranya Almohsen, and Gianfranco Doretto · 2018
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Sharpening Jensen’s inequality
JG Liao and Arthur Berg · 2019
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OCGAN: One-class novelty detection using GANs with constrained latent representations
Pramuditha Perera, Ramesh Nallapati, and Bing Xiang · 2019
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Exact rate-distortion in autoencoders via echo noise
Rob Brekelmans, Daniel Moyer, Aram Galstyan, and Greg Ver Steeg · 2019
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Rethinking lossy compression: The rate-distortion-perception tradeoff
Yochai Blau and Tomer Michaeli · 2019
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Information theoretic lower bounds on negative log likelihood
Luis A Lastras · 2019
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Combining stochastic adaptive cubic regularization with negative curvature for nonconvex optimization
Seonho Park, Seung Hyun Jung, and Panos M Pardalos · 2020
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