Safe Triplet Screening for Distance Metric Learning

DOI10.1162/neco_a_01240zbMath1494.68234arXiv1802.03923OpenAlexW2980471706WikidataQ90718188 ScholiaQ90718188MaRDI QIDQ5214409

Masayuki Karasuyama, Tomoki Yoshida, Ichiro Takeuchi

Publication date: 7 February 2020

Published in: Neural Computation (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1802.03923

Mathematics Subject Classification ID

Applications of mathematical programming (90C90) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (2)

Unnamed Item ⋮ Distance metric learning for graph structured data

Uses Software

• LIBSVM
• Keras
• FaceNet
• GitHub
• LMNN

Cites Work

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• FaceNet
• Conjugate gradient methods for the Rayleigh quotient minimization of generalized eigenvalue problems
• Deep metric learning using triplet network
• Metric Learning: A Survey
• Two-Point Step Size Gradient Methods
• Gap Safe screening rules for sparsity enforcing penalties
• A Dual Approach to Semidefinite Least-Squares Problems
• Deflation Techniques for an Implicitly Restarted Arnoldi Iteration
• Safe Feature Elimination in Sparse Supervised Learning
• Least-Squares Covariance Matrix Adjustment

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