A Comparative Study of Pairwise Learning Methods Based on Kernel Ridge Regression
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Publication:5157226
DOI10.1162/neco_a_01096zbMath1472.68158arXiv1803.01575OpenAlexW2963091287WikidataQ64124254 ScholiaQ64124254MaRDI QIDQ5157226
Michiel Stock, Bernard De Baets, Willem Waegeman, Antti Airola, Tapio Pahikkala
Publication date: 12 October 2021
Published in: Neural Computation (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1803.01575
Nonparametric regression and quantile regression (62G08) Ridge regression; shrinkage estimators (Lasso) (62J07) Learning and adaptive systems in artificial intelligence (68T05)
Related Items (3)
Generalized vec trick for fast learning of pairwise kernel models ⋮ \textsf{StreaMRAK} a streaming multi-resolution adaptive kernel algorithm ⋮ Improving Generalization via Attribute Selection on Out-of-the-Box Data
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Cites Work
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- Multi-output learning via spectral filtering
- An alternative two stage least squares \((2SLS)\) estimator for latent variable equations
- On regularization algorithms in learning theory
- Learning intransitive reciprocal relations with kernel methods
- The ubiquitous Kronecker product
- Efficient regularized least-squares algorithms for conditional ranking on relational data
- Exact matrix completion via convex optimization
- 10.1162/153244302760185252
- Kernels for Vector-Valued Functions: A Review
- Randomized Algorithms for Matrices and Data
- Spectral Algorithms for Supervised Learning
- Graph-Based Semi-Supervised Learning and Spectral Kernel Design
- Shifted Kronecker Product Systems
- Machine Learning: ECML 2004
- Low-rank matrix completion using alternating minimization
- The elements of statistical learning. Data mining, inference, and prediction
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