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Indexes are models: a B-Tree-Index can be seen as a model to map a key to the position of a record within a sorted array, a Hash-Index as a model to map a key to a position of a record within an unsorted array, and a BitMap-Index as a model to indicate if a data record exists or not.
Asymptotic minimax character of the sample distribution function and of the classical multinomial estimator
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J. Rao and K. A. Ross · 2000
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B-tree indexes and CPU caches
G. Graefe and P. A. Larson · 2001
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Compressed bloom filters
M. Mitzenmacher · 2001
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High-order entropy-compressed text indexes
R. Grossi, A. Gupta, and J. S. Vitter · 2003
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Network applications of bloom filters: A survey
A. Broder and M. Mitzenmacher · 2004
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Cuckoo hashing
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Bigtable: A distributed storage system for structured data (awarded best paper!)
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An introduction to roc analysis
T. Fawcett · 2006
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B-tree indexes, interpolation search, and skew
G. Graefe · 2006
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A comparison of machine learning techniques for phishing detection
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Detection of phishing attacks: A machine learning approach
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Building a database on S3
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RDF-3X: A RISC-style Engine for RDF
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SCADS: scale-independent storage for social computing applications
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Discriminative learning under covariate shift
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http://databasearchitects.blogspot.com/2015/09/trying-to-speed-up-binary-search.html
Trying to speed up binary search · 2015
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An architecture for compiling udf-centric workflows
A. Crotty, A. Galakatos, K. Dursun, T. Kraska, C. Binnig, U. Çetintemel, and S. Zdonik · 2015
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CNN based hashing for image retrieval
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S. Richter, V. Alvarez, and J. Dittrich · 2015
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Tensorflow: A system for large-scale machine learning
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Fast: Fast architecture sensitive tree search on modern cpus and gpus
C. Kim, J. Chhugani, N. Satish, E. Sedlar, A. D. Nguyen, T. Kaldewey, V. W. Lee, S. A. Brandt, and P. Dubey · 2010
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Efficient in-memory indexing with generalized prefix trees
M. Böhm, B. Schlegel, P. B. Volk, U. Fischer, D. Habich, and W. Lehner · 2011
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Adaptive subgradient methods for online learning and stochastic optimization
J. Duchi, E. Hazan, and Y. Singer · 2011
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Cumulative distribution networks and the derivative-sum-product algorithm: Models and inference for cumulative distribution functions on graphs
J. C. Huang and B. J. Frey · 2011
Cited alongside, same era.
The wavelet trie: Maintaining an indexed sequence of strings in compressed space
R. Grossi and G. Ottaviano · 2012
Cited alongside, same era.
B + -Tree Optimized for GPGPU
K. Kaczmarski · 2012
Cited alongside, same era.
M. Gupta, A. Cotter, J. Pfeifer, K. Voevodski, K. Canini, A. Mangylov, W. Moczydlowski, and A. Van Esbroeck · 2016
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A hybrid b+-tree as solution for in-memory indexing on cpu-gpu heterogeneous computing platforms
A. Shahvarani and H.-A. Jacobsen · 2016
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Hash function generation by neural network
M. Turcanik and M. Javurek · 2016
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Learning to hash for indexing big data;a survey
J. Wang, W. Liu, S. Kumar, and S. F. Chang · 2016
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Google’s neural machine translation system: Bridging the gap between human and machine translation
Y. Wu, M. Schuster, Z. Chen, Q. V. Le, M. Norouzi, W. Macherey, M. Krikun, Y. Cao, Q. Gao, K. Macherey, et al · 2016
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Two Birds, One Stone: A Fast, Yet Lightweight, Indexing Scheme for Modern Database Systems
J. Yu and M. Sarwat · 2016
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Reducing the storage overhead of main-memory OLTP databases with hybrid indexes
H. Zhang, D. G. Andersen, A. Pavlo, M. Kaminsky, L. Ma, and R. Shen · 2016
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http://databasearchitects.blogspot.de/2017/12/the-case-for-b-tree-index-structures.html
Database architects blog: The case for b-tree index structures · 2017
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https://cloud.google.com/blog/big-data/2017/05/an-in-depth-look-at-googles-first-tensor-processing-unit-tpu
An in-depth look at google’s first tensor processing unit (tpu) · 2017
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https://dirtyhandscoding.wordpress.com/2017/08/25/performance-comparison-linear-search-vs-binary-search/
Performance comparison: linear search vs binary search · 2017
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Outrageously large neural networks: The sparsely-gated mixture-of-experts layer
N. Shazeer, A. Mirhoseini, K. Maziarz, A. Davis, Q. Le, G. Hinton, and J. Dean · 2017
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Ensemble adversarial training: Attacks and defenses
F. Tramèr, A. Kurakin, N. Papernot, D. Boneh, and P. McDaniel · 2017
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Deep lattice networks and partial monotonic functions
S. You, D. Ding, K. Canini, J. Pfeifer, and M. Gupta · 2017
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Y. You, Z. Zhang, C. Hsieh, J. Demmel, and K. Keutzer · 2017
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The end of a myth: Distributed transaction can scale
E. Zamanian, C. Binnig, T. Kraska, and T. Harris · 2017
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A-tree: A bounded approximate index structure
A. Galakatos, M. Markovitch, C. Binnig, R. Fonseca, and T. Kraska · 2018
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A model for learned bloom filters and related structures
M. Mitzenmacher · 2018
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https://www.nextbigfuture.com/2017/06/moore-law-is-dead-but-gpu-will-get-1000x-faster-by-2025.html
Moore Law is Dead but GPU will get 1000X faster by 2025 · 2025
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