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Recent works within machine learning have been tackling inputs of ever-increasing size, with cybersecurity presenting sequence classification problems of particularly extreme lengths.
Explaining Vulnerabilities of Deep Learning to Adversarial Malware Binaries
Demetrio, L.; Biggio, B.; Lagorio, G.; Roli, F.; and Armando, A. 2019 · 1901
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Activation Analysis of a Byte-Based Deep Neural Network for Malware Classification
Coull, S. E.; and Gardner, C. 2019 · 1903
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Algorithm 799: Revolve: An Implementation of Checkpointing for the Reverse or Adjoint Mode of Computational Differentiation
Griewank, A.; and Walther, A. 2000 · 2000
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The Similarity Metric
Li, M.; Chen, X.; Li, X.; Ma, B.; and Vitanyi, P. M. 2004 · 2004
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Automated Classification and Analysis of Internet Malware
Bailey, M.; Oberheide, J.; Andersen, J.; Mao, Z. M.; Jahanian, F.; and Nazario, J. 2007 · 2007
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The Software Similarity Problem in Malware Analysis
Walenstein, A.; and Lakhotia, A. 2007 · 2007
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Analyzing Worms and Network Traffic Using Compression
Wehner, S. 2007 · 2007
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Evaluation of malware phylogeny modelling systems using automated variant generation
Hayes, M.; Walenstein, A.; and Lakhotia, A. 2008 · 2008
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Scalable , Behavior-Based Malware Clustering
Bayer, U.; Comparetti, P. M.; Hlauschek, C.; Kruegel, C.; and Kirda, E. 2009 · 2009
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Powerful SNP-set analysis for case-control genome-wide association studies
Wu, M. C.; Kraft, P.; Epstein, M. P.; Taylor, D. M.; Chanock, S. J.; Hunter, D. J.; and Lin, X. 2010 · 2010
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Trends in CircumventingWeb-Malware Detection
Rajab, M. A.; Ballard, L.; Jagpal, N.; Mavrommatis, P.; Nojiri, D.; Provos, N.; and Schmidt, L. 2011 · 2011
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Virus Share
Roberts, J.-M. 2011 · 2011
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ImageNet Classification with Deep Convolutional Neural Networks
Krizhevsky, A.; Sutskever, I.; and Hinton, G. E. 2012 · 2012
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Approaches to Adversarial Drift
Kantchelian, A.; Afroz, S.; Huang, L.; Islam, A. C.; Miller, B.; Tschantz, M. C.; Greenstadt, R.; Joseph, A. D.; and Tygar, J. D. 2013 · 2013
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Is Anti-virus Really Dead?
Spafford, E. C. 2014 · 2014
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Detecting Malware with Information Complexity
Alshahwan, N.; Barr, E. T.; Clark, D.; and Danezis, G. 2015 · 2015
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On normalized compression distance and large malware
Borbely, R. S. 2015 · 2015
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Neural Machine Translation By Jointly Learning To Align and Translate
Dzmitry Bahdana; Bahdanau, D.; Cho, K.; and Bengio, Y. 2015 · 2015
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Adam: A Method for Stochastic Optimization
Kingma, D. P.; and Ba, J. L. 2015 · 2015
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Effective Approaches to Attention-based Neural Machine Translation
Luong, T.; Pham, H.; and Manning, C. D. 2015 · 2015
Cited alongside, same era.
Training Deep Nets with Sublinear Memory Cost
Chen, T.; Xu, B.; Zhang, C.; and Guestrin, C. 2016 · 2016
Cited alongside, same era.
Memory-Efficient Backpropagation Through Time
Gruslys, A.; Munos, R.; Danihelka, I.; Lanctot, M.; and Graves, A. 2016 · 2016
Cited alongside, same era.
WaveNet: A Generative Model for Raw Audio URL http://arxiv.org/abs/1609.03499
van den Oord, A.; Dieleman, S.; Zen, H.; Simonyan, K.; Vinyals, O.; Graves, A.; Kalchbrenner, N.; Senior, A.; and Kavukcuoglu, K. 2016 · 2016
Cited alongside, same era.
Hierarchical Attention Networks for Document Classification
Yang, Z.; Yang, D.; Dyer, C.; He, X.; Smola, A.; and Hovy, E. 2016 · 2016
Cited alongside, same era.
Neural Classification of Malicious Scripts: A study with JavaScript and VBScript
Stokes, J. W.; Agrawal, R.; and McDonald, G. 2018 · 2018
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BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Devlin, J.; Chang, M.-W.; Lee, K.; and Toutanova, K. 2019 · 2019
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Parameter Tuning and Confidence Limits of Malware Clustering
Faridi, H.; Srinivasagopalan, S.; and Verma, R. 2019 · 2019
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Non-Negative Networks Against Adversarial Attacks
Fleshman, W.; Raff, E.; Sylvester, J.; Forsyth, S.; and McLean, M. 2019 · 2019
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What is the Shape of an Executable?
Galinkin, E. 2019 · 2019
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Zhang, Y.; Marshall, I.; and Wallace, B. C. 2016 · 2016
Cited alongside, same era.
Language Modeling with Gated Convolutional Networks
Dauphin, Y. N.; Fan, A.; Auli, M.; and Grangier, D. 2017 · 2017
Cited alongside, same era.
A Structured Self-attentive Sentence Embedding
Lin, Z.; Feng, M.; dos Santos, C. N.; Yu, M.; Xiang, B.; Zhou, B.; and Bengio, Y. 2017 · 2017
Cited alongside, same era.
An Alternative to NCD for Large Sequences, Lempel-Ziv Jaccard Distance
Raff, E.; and Nicholas, C. 2017 · 2017
Cited alongside, same era.
Attention is All you Need
Vaswani, A.; Shazeer, N.; Parmar, N.; Uszkoreit, J.; Jones, L.; Gomez, A. N.; Kaiser, L.; and Polosukhin, I. 2017 · 2017
Cited alongside, same era.
EMBER: An Open Dataset for Training Static PE Malware Machine Learning Models
Anderson, H. S.; and Roth, P. 2018 · 2018
Cited alongside, same era.
Static Malware Detection & Subterfuge: Quantifying the Robustness of Machine Learning and Current Anti-Virus
Fleshman, W.; Raff, E.; Zak, R.; McLean, M.; and Nicholas, C. 2018 · 2018
Cited alongside, same era.
Malware Detection on Byte Streams of PDF Files Using Convolutional Neural Networks
Jeong, Y.-S.; Woo, J.; and Kang, A. R. 2019 · 2019
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Efficient Rematerialization for Deep Networks
Kumar, R.; Purohit, M.; Svitkina, Z.; Vee, E.; and Wang, J. 2019 · 2019
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A Graph Theoretic Framework of Recomputation Algorithms for Memory-Efficient Backpropagation
Kusumoto, M.; Inoue, T.; Watanabe, G.; Akiba, T.; and Koyama, M. 2019 · 2019
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Phenotype Prediction and Genome-Wide Association Study Using Deep Convolutional Neural Network of Soybean
Liu, Y.; Wang, D.; He, F.; Wang, J.; Joshi, T.; and Xu, D. 2019 · 2019
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Decoupled Weight Decay Regularization
Loshchilov, I.; and Hutter, F. 2019 · 2019
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The arms race: Adversarial search defeats entropy used to detect malware
Menéndez, H. D.; Bhattacharya, S.; Clark, D.; and Barr, E. T. 2019 · 2019
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PyLZJD: An Easy to Use Tool for Machine Learning
Raff, E.; Aurelio, J.; and Nicholas, C. 2019 · 2019
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A Survey on Using Kolmogorov Complexity in Cybersecurity
S. Resende, J.; Martins, R.; and Antunes, L. 2019 · 2019
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Legendre Memory Units: Continuous-Time Representation in Recurrent Neural Networks
Voelker, A.; Kajić, I.; and Eliasmith, C. 2019 · 2019
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An Observational Investigation of Reverse Engineers ’ Processes
Votipka, D.; Rabin, S. M.; Micinski, K.; Foster, J. S.; and Mazurek, M. M. 2019 · 2019
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Optimal memory-aware backpropagation of deep join networks
Beaumont, O.; Herrmann, J.; Pallez (Aupy), G.; and Shilova, A. 2020 · 2020
Closest in time.
Reformer: The Efficient Transformer
Kitaev, N.; Kaiser, L.; and Levskaya, A. 2020 · 2020
Closest in time.
A New Burrows Wheeler Transform Markov Distance
Raff, E.; Nicholas, C.; and McLean, M. 2020 · 2020
Closest in time.