Space-Efficient Feature Maps for String Alignment Kernels

Autor: Yasuo Tabei, Yoshihiro Yamanishi, Rasmus Pagh

Publikováno v: Data Science and Engineering, Vol 5, Iss 2, Pp 168-179 (2020)

Abstract String kernels are attractive data analysis tools for analyzing string data. Among them, alignment kernels are known for their high prediction accuracies in string classifications when tested in combination with SVM in various applications.

Externí odkaz: https://doaj.org/article/f5e65c357c814ecfa6d6b5538afb5dae

Representing Sparse Vectors with Differential Privacy, Low Error, Optimal Space, and Fast Access

Autor: Martin Aumüller, Christian Janos Lebeda, Rasmus Pagh

Publikováno v: Aumüller, M, Lebeda, C J & Pagh, R 2022, ' Representing Sparse Vectors with Differential Privacy, Low Error, Optimal Space, and Fast Access ', Journal of Privacy and Confidentiality, vol. 12, no. 2 . https://doi.org/10.29012/jpc.809

Representing a sparse histogram, or more generally a sparse vector, is a fundamental task in differential privacy. An ideal solution would use space close to information-theoretical lower bounds, have an error distribution that depends optimally on t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3942c4f8076bbec6d356196066922384
https://doi.org/10.29012/jpc.809

CountSketches, Feature Hashing and the Median of Three

Autor: Kasper Green Larsen, Rasmus Pagh, Jakub Tetek

Publikováno v: Larsen, K G, Pagh, R & Tetek, J 2021, CountSketches, Feature Hashing and the Median of Three . in M Meila & T Zhang (eds), Proceedings of the 38th International Conference on Machine Learning, ICML 2021, 18-24 July 2021, Virtual Event . Proceedings of Machine Learning Research, vol. 139, pp. 6011-6020, International Conference on Machine Learning, 18-24 July 2021, Virtual, 18/07/2021 . < http://proceedings.mlr.press/v139/larsen21a.html >
Larsen, K G, Pagh, R & Tetek, J 2021, CountSketches, Feature Hashing and the Median of Three . in M Meila & T Zhang (eds), Proceedings of the 38 th International Conference on Machine Learning . PMLR, Proceedings of Machine Learning Research, vol. 139, pp. 6011-6020, 38th International Conference on Machine Learning (ICML), Virtual, 18/07/2021 . < https://proceedings.mlr.press/v139/ >
University of Copenhagen

In this paper, we revisit the classic CountSketch method, which is a sparse, random projection that transforms a (high-dimensional) Euclidean vector $v$ to a vector of dimension $(2t-1) s$, where $t, s > 0$ are integer parameters. It is known that ev

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f28cf13f4e4642f3e34b22680076b0d1
https://pure.au.dk/portal/da/publications/countsketches-feature-hashing-and-the-median-of-three(993c82ad-30f6-470a-bea1-75885c3ca97b).html

On the Power of Multiple Anonymous Messages: Frequency Estimation and Selection in the Shuffle Model of Differential Privacy

Autor: Badih Ghazi, Noah Golowich, Ravi Kumar, Ameya Velingker, Rasmus Pagh

Publikováno v: Lecture Notes in Computer Science ISBN: 9783030778828
EUROCRYPT (3)

It is well-known that general secure multi-party computation can in principle be applied to implement differentially private mechanisms over distributed data with utility matching the curator (a.k.a. central) model. In this paper we study the power o

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::f8cb5abcaf87a806ddbdda0b0678d78d
https://doi.org/10.1007/978-3-030-77883-5_16

Sampling a Near Neighbor in High Dimensions -- Who is the Fairest of Them All?

Autor: Martin Aumüller, Sariel Har-Peled, Sepideh Mahabadi, Rasmus Pagh, Francesco Silvestri

Publikováno v: Aumüller, M, Har-Peled, S, Mahabadi, S, Pagh, R & Silvestri, F 2022, ' Sampling a Near Neighbor in High Dimensions-Who is the Fairest of Them All? ', ACM Transactions on Database Systems, vol. 47, no. 1, 4, pp. 1-40 . https://doi.org/10.1145/3502867
Aumüller, M, Pagh, R, Silvestri, F, Har-Peled, S & Mahabadi, S 2022, ' Sampling a Near Neighbor in High Dimensions — Who is the Fairest of Them All? ', ACM Transactions on Database Systems, vol. 47, no. 1, 4, pp. 1-40 . < https://dl.acm.org/doi/10.1145/3502867 >

Similarity search is a fundamental algorithmic primitive, widely used in many computer science disciplines. Given a set of points $S$ and a radius parameter $r>0$, the $r$-near neighbor ($r$-NN) problem asks for a data structure that, given any query

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5d944be8c42abfa2800f31a557187342