Achlioptas, Dimitris. 2003.
βDatabase-Friendly Random Projections: Johnson-Lindenstrauss with Binary Coins.β Journal of Computer and System Sciences, Special Issue on PODS 2001, 66 (4): 671β87.
Ailon, Nir, and Bernard Chazelle. 2009.
βThe Fast JohnsonβLindenstrauss Transform and Approximate Nearest Neighbors.β SIAM Journal on Computing 39 (1): 302β22.
Alaoui, Ahmed El, and Michael W. Mahoney. 2014.
βFast Randomized Kernel Methods With Statistical Guarantees.β arXiv:1411.0306 [Cs, Stat], November.
Andoni, A., and P. Indyk. 2006.
βNear-Optimal Hashing Algorithms for Approximate Nearest Neighbor in High Dimensions.β In
47th Annual IEEE Symposium on Foundations of Computer Science, 2006. FOCS β06, 51:459β68.
Andoni, Alexandr, Piotr Indyk, Huy L. Nguyen, and Ilya Razenshteyn. 2013.
βBeyond Locality-Sensitive Hashing.β arXiv:1306.1547 [Cs], June.
Andoni, Alexandr, and Ilya Razenshteyn. 2015.
βOptimal Data-Dependent Hashing for Approximate Near Neighbors.β arXiv:1501.01062 [Cs], January.
Auvolat, Alex, and Pascal Vincent. 2015.
βClustering Is Efficient for Approximate Maximum Inner Product Search.β arXiv:1507.05910 [Cs, Stat], July.
Baraniuk, Richard, Mark Davenport, Ronald DeVore, and Michael Wakin. 2008.
βA Simple Proof of the Restricted Isometry Property for Random Matrices.β Constructive Approximation 28 (3): 253β63.
Bingham, Ella, and Heikki Mannila. 2001.
βRandom Projection in Dimensionality Reduction: Applications to Image and Text Data.β In
Proceedings of the Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 245β50. KDD β01. New York, NY, USA: ACM.
Brault, Romain, Florence dβAlchΓ©-Buc, and Markus Heinonen. 2016.
βRandom Fourier Features for Operator-Valued Kernels.β In
Proceedings of The 8th Asian Conference on Machine Learning, 110β25.
Candès, Emmanuel J., and Terence Tao. 2006.
βNear-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?β IEEE Transactions on Information Theory 52 (12): 5406β25.
Casey, M., C. Rhodes, and M. Slaney. 2008.
βAnalysis of Minimum Distances in High-Dimensional Musical Spaces.β IEEE Transactions on Audio, Speech, and Language Processing 16 (5): 1015β28.
Choromanski, Krzysztof, Mark Rowland, and Adrian Weller. 2017.
βThe Unreasonable Effectiveness of Random Orthogonal Embeddings.β arXiv:1703.00864 [Stat], March.
Coleman, Benjamin, Richard G. Baraniuk, and Anshumali Shrivastava. 2020.
βSub-Linear Memory Sketches for Near Neighbor Search on Streaming Data.β arXiv:1902.06687 [Cs, Eess, Stat], September.
Dasgupta, Sanjoy. 2000.
βExperiments with Random Projection.β In
Proceedings of the Sixteenth Conference on Uncertainty in Artificial Intelligence, 143β51. UAIβ00. San Francisco, CA, USA: Morgan Kaufmann Publishers Inc.
Dasgupta, Sanjoy, and Anupam Gupta. 2003.
βAn Elementary Proof of a Theorem of Johnson and Lindenstrauss.β Random Structures & Algorithms 22 (1): 60β65.
Datar, Mayur, Nicole Immorlica, Piotr Indyk, and Vahab S. Mirrokni. 2004.
βLocality-Sensitive Hashing Scheme Based on P-Stable Distributions.β In
Proceedings of the Twentieth Annual Symposium on Computational Geometry, 253β62. SCG β04. New York, NY, USA: ACM.
Dezfouli, Amir, and Edwin V. Bonilla. 2015.
βScalable Inference for Gaussian Process Models with Black-Box Likelihoods.β In
Advances in Neural Information Processing Systems 28, 1414β22. NIPSβ15. Cambridge, MA, USA: MIT Press.
Duarte, Marco F., and Richard G. Baraniuk. 2013.
βSpectral Compressive Sensing.β Applied and Computational Harmonic Analysis 35 (1): 111β29.
Eftekhari, Armin, Han Lun Yap, Michael B. Wakin, and Christopher J. Rozell. 2016.
βStabilizing Embedology: Geometry-Preserving Delay-Coordinate Maps.β arXiv:1609.06347 [Nlin, Stat], September.
Freund, Yoav, Sanjoy Dasgupta, Mayank Kabra, and Nakul Verma. 2007.
βLearning the Structure of Manifolds Using Random Projections.β In
Advances in Neural Information Processing Systems, 473β80.
Geurts, Pierre, Damien Ernst, and Louis Wehenkel. 2006.
βExtremely Randomized Trees.β Machine Learning 63 (1): 3β42.
Ghojogh, Benyamin, Ali Ghodsi, Fakhri Karray, and Mark Crowley. 2021.
βJohnson-Lindenstrauss Lemma, Linear and Nonlinear Random Projections, Random Fourier Features, and Random Kitchen Sinks: Tutorial and Survey.β arXiv:2108.04172 [Cs, Math, Stat], August.
Gionis, Aristides, Piotr Indyky, and Rajeev Motwaniz. 1999.
βSimilarity Search in High Dimensions via Hashing.β In.
Giryes, R., G. Sapiro, and A. M. Bronstein. 2016.
βDeep Neural Networks with Random Gaussian Weights: A Universal Classification Strategy?β IEEE Transactions on Signal Processing 64 (13): 3444β57.
Gorban, Alexander N., Ivan Yu Tyukin, and Ilya Romanenko. 2016.
βThe Blessing of Dimensionality: Separation Theorems in the Thermodynamic Limit.β arXiv:1610.00494 [Cs, Stat], October.
Hall, Peter, and Ker-Chau Li. 1993.
βOn Almost Linearity of Low Dimensional Projections from High Dimensional Data.β The Annals of Statistics 21 (2): 867β89.
Kammonen, Aku, Jonas Kiessling, Petr PlechΓ‘Δ, Mattias Sandberg, and Anders Szepessy. 2020.
βAdaptive Random Fourier Features with Metropolis Sampling.β arXiv:2007.10683 [Cs, Math], November.
Kane, Daniel M., and Jelani Nelson. 2014.
βSparser Johnson-Lindenstrauss Transforms.β Journal of the ACM 61 (1): 1β23.
Kar, Purushottam, and Harish Karnick. 2012.
βRandom Feature Maps for Dot Product Kernels.β In
Artificial Intelligence and Statistics, 583β91. PMLR.
Koltchinskii, Vladimir, and Evarist GinΓ©. 2000.
βRandom Matrix Approximation of Spectra of Integral Operators.β Bernoulli 6 (1): 113β67.
Koppel, Alec, Garrett Warnell, Ethan Stump, and Alejandro Ribeiro. 2016.
βParsimonious Online Learning with Kernels via Sparse Projections in Function Space.β arXiv:1612.04111 [Cs, Stat], December.
Krummenacher, Gabriel, Brian McWilliams, Yannic Kilcher, Joachim M Buhmann, and Nicolai Meinshausen. 2016.
βScalable Adaptive Stochastic Optimization Using Random Projections.β In
Advances in Neural Information Processing Systems 29, edited by D. D. Lee, M. Sugiyama, U. V. Luxburg, I. Guyon, and R. Garnett, 1750β58. Curran Associates, Inc.
Kulis, Brian, and Kristen Grauman. 2012.
βKernelized Locality-Sensitive Hashing.β IEEE Transactions on Pattern Analysis and Machine Intelligence 34 (6): 1092β1104.
Landweber, Peter S., Emanuel A. Lazar, and Neel Patel. 2016.
βOn Fiber Diameters of Continuous Maps.β American Mathematical Monthly 123 (4): 392β97.
Li, Ping, Trevor J. Hastie, and Kenneth W. Church. 2006.
βVery Sparse Random Projections.β In
Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 287β96. KDD β06. New York, NY, USA: ACM.
Li, Zhu, Jean-FranΓ§ois Ton, Dino Oglic, and Dino Sejdinovic. 2019. βTowards a Uniο¬ed Analysis of Random Fourier Features.β In, 10.
McWilliams, Brian, David Balduzzi, and Joachim M Buhmann. 2013.
βCorrelated Random Features for Fast Semi-Supervised Learning.β In
Advances in Neural Information Processing Systems 26, edited by C. J. C. Burges, L. Bottou, M. Welling, Z. Ghahramani, and K. Q. Weinberger, 1050:440β48. Curran Associates, Inc.
Moosmann, Frank, Bill Triggs, and Frederic Jurie. 2006.
βFast Discriminative Visual Codebooks Using Randomized Clustering Forests.β In
Advances in Neural Information Processing Systems, 985β92.
Oveneke, Meshia CΓ©dric, Mitchel Aliosha-Perez, Yong Zhao, Dongmei Jiang, and Hichem Sahli. 2016.
βEfficient Convolutional Auto-Encoding via Random Convexification and Frequency-Domain Minimization.β In
Advances in Neural Information Processing Systems 29.
Oymak, Samet, and Joel A. Tropp. 2015.
βUniversality Laws for Randomized Dimension Reduction, with Applications.β arXiv:1511.09433 [Cs, Math, Stat], November.
Rahimi, Ali, and Benjamin Recht. 2007.
βRandom Features for Large-Scale Kernel Machines.β In
Advances in Neural Information Processing Systems, 1177β84. Curran Associates, Inc.
Scardapane, Simone, and Dianhui Wang. 2017.
βRandomness in Neural Networks: An Overview.β Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 7 (2).
Sinha, Aman, and John C Duchi. 2016.
βLearning Kernels with Random Features.β In
Advances in Neural Information Processing Systems 29, edited by D. D. Lee, M. Sugiyama, U. V. Luxburg, I. Guyon, and R. Garnett, 1298β1306. Curran Associates, Inc.
Sterge, Nicholas, and Bharath Sriperumbudur. 2021.
βStatistical Optimality and Computational Efficiency of NystrΓΆm Kernel PCA.β arXiv:2105.08875 [Cs, Math, Stat], May.
Tang, Minh, Avanti Athreya, Daniel L. Sussman, Vince Lyzinski, and Carey E. Priebe. 2014.
βA Nonparametric Two-Sample Hypothesis Testing Problem for Random Dot Product Graphs.β arXiv:1409.2344 [Math, Stat], September.
Weinberger, Kilian, Anirban Dasgupta, John Langford, Alex Smola, and Josh Attenberg. 2009.
βFeature Hashing for Large Scale Multitask Learning.β In
Proceedings of the 26th Annual International Conference on Machine Learning, 1113β20. ICML β09. New York, NY, USA: ACM.
Zhang, Dell, Jun Wang, Deng Cai, and Jinsong Lu. 2010.
βSelf-Taught Hashing for Fast Similarity Search.β In
Proceedings of the 33rd International ACM SIGIR Conference on Research and Development in Information Retrieval, 18β25. SIGIR β10. New York, NY, USA: ACM.
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