Fetching the paper…
Reading the bibliography…
Nearest neighbor is a popular nonparametric method for classification and regression with many appealing properties.
Feller, W. (1942), “Some geometric inequalities,” Duke Math. J
1942
Earlier work this paper cites.
Fix, E. and Hodges Jr, J. L. (1951), “Discriminatory analysis-nonparametric discrimination: consistency properties,” Tech. rep., California Univ Berkeley
1951
Earlier work this paper cites.
Hoare, C. A. (1961), “Algorithm 65: find,” Communications of the ACM
1961
Earlier work this paper cites.
Cover, T. and Hart, P. (1967), “Nearest neighbor pattern classification,” IEEE transactions on information theory
1967
Earlier work this paper cites.
Devroye, L., Gyorfi, L., Krzyzak, A., and Lugosi, G. (1994), “On the strong universal consistency of nearest neighbor regression function estimates,” The Annals of Statistics
1994
Earlier work this paper cites.
Dietterich, T. G., Jain, A. N., Lathrop, R. H., and Lozano-Perez, T. (1994), “A comparison of dynamic reposing and tangent distance for drug activity prediction,” in Advances in Neural Information Processing Systems
1994
Earlier work this paper cites.
Dietterich, T. G., Lathrop, R. H., and Lozano-Pérez, T. (1997), “Solving the multiple instance problem with axis-parallel rectangles,” Artificial intelligence
1997
Earlier work this paper cites.
Kleinberg, J. M. (1997), “Two algorithms for nearest-neighbor search in high dimensions,” in Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
1997
Earlier work this paper cites.
Indyk, P. and Motwani, R. (1998), “Approximate nearest neighbors: towards removing the curse of dimensionality,” in Proceedings of the thirtieth annual ACM symposium on Theory of computing
1998
Earlier work this paper cites.
Dietterich, T. G. (2000), “Ensemble methods in machine learning,” in International workshop on multiple classifier systems
2000
Earlier work this paper cites.
Bühlmann, P. and Yu, B. (2002), “Analyzing bagging,” The Annals of Statistics
2002
Earlier work this paper cites.
Guyon, I., Gunn, S., Ben-Hur, A., and Dror, G. (2005), “Result analysis of the NIPS 2003 feature selection challenge,” in Advances in neural information processing systems
2003
Earlier work this paper cites.
Gray, A. (2004), Tubes
2004
Earlier work this paper cites.
Lehmann, E. L. (2004), Elements of large-sample theory
2004
Earlier work this paper cites.
Hall, P. and Samworth, R. J. (2005), “Properties of bagged nearest neighbour classifiers,” Journal of the Royal Statistical Society: Series B (Statistical Methodology)
2005
Earlier work this paper cites.
Liu, T., Moore, A. W., Yang, K., and Gray, A. G. (2005), “An investigation of practical approximate nearest neighbor algorithms,” in Advances in neural information processing systems
2005
Earlier work this paper cites.
Dasgupta, S. and Freund, Y. (2008), “Random projection trees and low dimensional manifolds,” in Proceedings of the fortieth annual ACM symposium on Theory of computing
2008
Cited alongside, same era.
Yeh, I.-C. and Lien, C.-h. (2009), “The comparisons of data mining techniques for the predictive accuracy of probability of default of credit card clients,” Expert Systems with Applications
2009
Cited alongside, same era.
Biau, G., Cérou, F., and Guyader, A. (2010), “On the rate of convergence of the bagged nearest neighbor estimate,” Journal of Machine Learning Research
2010
Cited alongside, same era.
Grigor’eva, M. and Popov, S. (2012), “An upper bound for the absolute constant in the nonuniform version of the Berry-Esseen inequalities for nonidentically distributed summands,” in Doklady Mathematics
2012
Cited alongside, same era.
Muja, M. and Lowe, D. G. (2014), “Scalable nearest neighbor algorithms for high dimensional data,” IEEE Transactions on Pattern Analysis and Machine Intelligence
2014
Later among the works it cites.
2015
Later among the works it cites.
Maillo, J., Triguero, I., and Herrera, F. (2015), “A mapreduce-based k-nearest neighbor approach for big data classification,” in Trustcom/BigDataSE/ISPA, 2015 IEEE
2015
Later among the works it cites.
Mathy, C., Derbinsky, N., Bento, J., Rosenthal, J., and Yedidia, J. S. (2015), “The Boundary Forest Algorithm for Online Supervised and Unsupervised Learning.” in AAAI
2015
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2012
Cited alongside, same era.
Dasgupta, S. and Sinha, K. (2013), “Randomized partition trees for exact nearest neighbor search,” in Conference on Learning Theory
2013
Cited alongside, same era.
Lichman, M. (2013), “Uci machine learning repository. university of california, irvine, school of information and computer sciences,”
2013
Cited alongside, same era.
2013
Cited alongside, same era.
Yu, B. (2013), “Stability,” Bernoulli
2013
Cited alongside, same era.
Zhang, Y., Duchi, J., and Wainwright, M. (2013), “Divide and conquer kernel ridge regression,” in Conference on Learning Theory
2013
Cited alongside, same era.
Anchalia, P. P. and Roy, K. (2014), “The k-nearest neighbor algorithm using MapReduce paradigm,” in Intelligent Systems, Modelling and Simulation (ISMS), 2014 5th International Conference on
2014
Cited alongside, same era.
Baldi, P., Sadowski, P., and Whiteson, D. (2014), “Searching for exotic particles in high-energy physics with deep learning,” Nature communications
2014
Cited alongside, same era.
Candanedo, L. M. and Feldheim, V. (2016), “Accurate occupancy detection of an office room from light, temperature, humidity and CO2 measurements using statistical learning models,” Energy and Buildings
2016
Later among the works it cites.
Gadat, S., Klein, T., and Marteau, C. (2016), “Classification in general finite dimensional spaces with the K-nearest neighbor rule,” The Annals of Statistics
2016
Later among the works it cites.
Lyon, R., Stappers, B., Cooper, S., Brooke, J., and Knowles, J. (2016), “Fifty years of pulsar candidate selection: from simple filters to a new principled real-time classification approach,” Monthly Notices of the Royal Astronomical Society
2016
Later among the works it cites.
Papernot, N., McDaniel, P., Jha, S., Fredrikson, M., Celik, Z. B., and Swami, A. (2016), “The limitations of deep learning in adversarial settings,” in Security and Privacy (EuroS&P), 2016 IEEE European Symposium on
2016
Later among the works it cites.
Sun, W. W., Qiao, X., and Cheng, G. (2016), “Stabilized Nearest Neighbor Classifier and its Statistical Properties,” Journal of the American Statistical Association
2016
Later among the works it cites.
2016
Later among the works it cites.
2017
Later among the works it cites.
Lee, J. D., Liu, Q., Sun, Y., and Taylor, J. E. (2017), “Communication-efficient Sparse Regression,” Journal of Machine Learning Research
2017
Later among the works it cites.
Shang, Z. and Cheng, G. (2017), “Computational limits of a distributed algorithm for smoothing spline,” The Journal of Machine Learning Research
2017
Later among the works it cites.
2017
Later among the works it cites.
Biau, G., Devroye, L., and Lugosi, G. (2008), “Consistency of random forests and other averaging classifiers,” Journal of Machine Learning Research
2033
Closest in time.