ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1208.3145
  4. Cited By
Metric distances derived from cosine similarity and Pearson and Spearman
  correlations

Metric distances derived from cosine similarity and Pearson and Spearman correlations

14 August 2012
S. Dongen
Anton J. Enright
ArXiv (abs)PDFHTML

Papers citing "Metric distances derived from cosine similarity and Pearson and Spearman correlations"

7 / 7 papers shown
Revisiting Cosine Similarity via Normalized ICA-transformed Embeddings
Revisiting Cosine Similarity via Normalized ICA-transformed Embeddings
Hiroaki Yamagiwa
Momose Oyama
Hidetoshi Shimodaira
LLMSV
307
6
0
16 Jun 2024
Self-Attention Message Passing for Contrastive Few-Shot Learning
Self-Attention Message Passing for Contrastive Few-Shot LearningIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2022
Ojas Kishorkumar Shirekar
Ashutosh Kumar Singh
Hadi Jamali Rad
314
7
0
12 Oct 2022
Correlation-based sparse inverse Cholesky factorization for fast
  Gaussian-process inference
Correlation-based sparse inverse Cholesky factorization for fast Gaussian-process inferenceStatistics and computing (Stat Comput), 2021
Myeong K. Kang
Matthias Katzfuss
338
32
0
29 Dec 2021
The Impact of Preprocessing on Deep Representations for Iris Recognition
  on Unconstrained Environments
The Impact of Preprocessing on Deep Representations for Iris Recognition on Unconstrained Environments
L. A. Zanlorensi
Eduardo José da S. Luz
Rayson Laroca
A. Britto
Luiz Eduardo Soares de Oliveira
David Menotti
CVBM
156
25
0
29 Aug 2018
Learning Audio - Sheet Music Correspondences for Score Identification
  and Offline Alignment
Learning Audio - Sheet Music Correspondences for Score Identification and Offline Alignment
Matthias Dorfer
A. Arzt
Gerhard Widmer
190
43
0
31 Jul 2017
Maximum Likelihood Latent Space Embedding of Logistic Random Dot Product
  Graphs
Maximum Likelihood Latent Space Embedding of Logistic Random Dot Product Graphs
Luke O'Connor
Muriel Médard
Soheil Feizi
BDL
161
2
0
03 Oct 2015
Permutation Search Methods are Efficient, Yet Faster Search is Possible
Permutation Search Methods are Efficient, Yet Faster Search is PossibleProceedings of the VLDB Endowment (PVLDB), 2015
Bilegsaikhan Naidan
Leonid Boytsov
Eric Nyberg
283
59
0
10 Jun 2015
1
Page 1 of 1