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Anomaly detection is one of the frequent and important subroutines deployed in large-scale data processing systems.
.879-approximation algorithms for max cut and max 2sat
M. X. Goemans and D. P. Williamson · 1994
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Secure multi-party computation
O. Goldreich · 1998
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Approximate nearest neighbors: towards removing the curse of dimensionality
P. Indyk and R. Motwani · 1998
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Similarity search in high dimensions via hashing
A. Gionis, P. Indyk, R. Motwani, et al · 1999
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Lof: identifying density-based local outliers
M. M. Breunig, H.-P. Kriegel, R. T. Ng, and J. Sander · 2000
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Efficient algorithms for mining outliers from large data sets
S. Ramaswamy, R. Rastogi, and K. Shim · 2000
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Similarity estimation techniques from rounding algorithms
M. S. Charikar · 2002
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Bursty and hierarchical structure in streams
J. Kleinberg · 2002
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Enhancing effectiveness of outlier detections for low density patterns
J. Tang, Z. Chen, A. W.-C. Fu, and D. W. Cheung · 2002
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Outlier detection using k-nearest neighbour graph
V. Hautamaki, I. Karkkainen, and P. Franti · 2004
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Privacy-preserving outlier detection
J. Vaidya and C. Clifton · 2004
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Outlier mining in large high-dimensional data sets
F. Angiulli and C. Pizzuti · 2005
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The amsterdam library of object images
J.-M. Geusebroek, G. J. Burghouts, and A. W. Smeulders · 2005
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Unsupervised anomaly detection in network intrusion detection using clusters
K. Leung and C. Leckie · 2005
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Outlier detection by active learning
N. Abe, B. Zadrozny, and J. Langford · 2006
Cited alongside, same era.
Approximate nearest neighbors and the fast johnson-lindenstrauss transform
N. Ailon and B. Chazelle · 2006
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Ranking outliers using symmetric neighborhood relationship
W. Jin, A. K. Tung, J. Han, and W. Wang · 2006
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Outlier detection with kernel density functions
L. J. Latecki, A. Lazarevic, and D. Pokrajac · 2007
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Privacy: Theory meets practice on the map
A. Machanavajjhala, D. Kifer, J. Abowd, J. Gehrke, and L. Vilhuber · 2008
Cited alongside, same era.
Anomaly detection by combining decision trees and parametric densities
M. Reif, M. Goldstein, A. Stahl, and T. M. Breuel · 2008
Cited alongside, same era.
Fast locality-sensitive hashing
A. Dasgupta, R. Kumar, and T. Sarlós · 2011
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Privacy via the johnson-lindenstrauss transform
K. Kenthapadi, A. Korolova, I. Mironov, and N. Mishra · 2012
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A near-linear time approximation algorithm for angle-based outlier detection in high-dimensional data
N. Pham and R. Pagh · 2012
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On evaluation of outlier rankings and outlier scores
E. Schubert, R. Wojdanowski, A. Zimek, and H.-P. Kriegel · 2012
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Toward supervised anomaly detection
N. Görnitz, M. M. Kloft, K. Rieck, and U. Brefeld · 2013
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Generalized outlier detection with flexible kernel density estimates
E. Schubert, A. Zimek, and H.-P. Kriegel · 2014
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ELKI in time: ELKI 0.2 for the performance evaluation of distance measures for time series
E. Achtert, T. Bernecker, H. Kriegel, E. Schubert, and A. Zimek · 2009
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Anomaly detection: A survey
V. Chandola, A. Banerjee, and V. Kumar · 2009
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Loop: local outlier probabilities
H.-P. Kriegel, P. Kröger, E. Schubert, and A. Zimek · 2009
Cited alongside, same era.
A new local distance-based outlier detection approach for scattered real-world data
K. Zhang, M. Hutter, and H. Jin · 2009
Cited alongside, same era.
Benchmarking algorithms for detecting anomalies in large datasets
U. Carrasquilla · 2010
Cited alongside, same era.
Cache hierarchy and memory subsystem of the amd opteron processor
P. Conway, N. Kalyanasundharam, G. Donley, K. Lepak, and B. Hughes · 2010
Cited alongside, same era.
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Densifying one permutation hashing via rotation for fast near neighbor search
A. Shrivastava and P. Li · 2014
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Improved densification of one permutation hashing
A. Shrivastava and P. Li · 2014
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A bayesian perspective on locality sensitive hashing with extensions for kernel methods
A. Chakrabarti, V. Satuluri, A. Srivathsan, and S. Parthasarathy · 2015
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Simple and efficient weighted minwise hashing
A. Shrivastava · 2016
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Optimal densification for fast and accurate minwise hashing
A. Shrivastava · 2017
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A New Unbiased and Efficient Class of LSH-Based Samplers and Estimators for Partition Function Computation in Log-Linear Models
R. Spring and A. Shrivastava · 2017
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Scalable and sustainable deep learning via randomized hashing
R. Spring and A. Shrivastava · 2017
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