Fast and Provably Effective Multi-view Classification with Landmark-Based SVM

No abstract is available for this paper.

• Publication year

  2018

• Venue

  ECML/PKDD

• Publication date

  2018-09-10

• Fields of study

  Mathematics, Computer Science

• Identifiers
  DOI 10.1007/978-3-030-10928-8_12
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Multi-view Metric Learning in Vector-valued Kernel Spaces

  2018influential reference
• Multiview Privileged Support Vector Machines

  2018cited by this paper
• Multi-view learning overview: Recent progress and new challenges

  2017cited by this paper
• L3-SVMs: Landmarks-based Linear Local Support Vectors Machines

  2017cited by this paper
• Multi-view kernel completion

  2016cited by this paper
• Bayesian group factor analysis with structured sparsity

  2016cited by this paper
• PAC-Bayesian Analysis for a Two-Step Hierarchical Multiview Learning Approach

  2016cited by this paper
• A Unifying Framework in Vector-valued Reproducing Kernel Hilbert Spaces for Manifold Regularization and Co-Regularized Multi-view Learning

  2014cited by this paper
• The Multi-Task Learning View of Multimodal Data

  2013cited by this paper
• A survey of multi-view machine learning

  2013cited by this paper
• A Survey on Metric Learning for Feature Vectors and Structured Data

  2013cited by this paper
• A unifying framework for vector-valued manifold regularization and multi-view learning

  2013cited by this paper
• A Survey on Multi-view Learning

  2013cited by this paper
• Multiple Kernel Learning Algorithms

  2011cited by this paper
• Multi-view Laplacian Support Vector Machines

  2011cited by this paper
• Locally Linear Support Vector Machines

  2011cited by this paper
• Multiview Clustering with Incomplete Views

  2010influential reference
• Learning from Multiple Partially Observed Views - an Application to Multilingual Text Categorization

  2009cited by this paper
• SGD-QN: Careful Quasi-Newton Stochastic Gradient Descent

  2009cited by this paper
• LIBLINEAR: A Library for Large Linear Classification

  2008cited by this paper
• Distance Metric Learning: A Comprehensive Survey

  2006cited by this paper
• Two view learning: SVM-2K, Theory and Practice

  2005influential reference
• Breaking SVM Complexity with Cross-Training

  2004cited by this paper
• Sparseness of Support Vector Machines

  2003cited by this paper
• On Learning Vector − Valued Functions

  2003cited by this paper
• Stability and Generalization

  2002influential reference
• Using the Nyström Method to Speed Up Kernel Machines

  2000cited by this paper
• Support-Vector Networks

  1995influential reference

• Takagi-Sugeno-Kang Fuzzy System Towards Label-scarce Incomplete Multi-View Data Classification

  2023cites this paper
• TSK Fuzzy System Towards Few Labeled Incomplete Multi-View Data Classification

  2021cites this paper
• Kernel transfer over multiple views for missing data completion

  2019cites this paper
• Learning Landmark-Based Ensembles with Random Fourier Features and Gradient Boosting

  2019cites this paper
• Cross-View kernel transfer

  2019cites this paper
• A Unified View of Local Learning : Theory and Algorithms for Enhancing Linear Models. (Une Vue Unifiée de l'Apprentissage Local : Théorie et Algorithmes pour l'Amélioration de Modèles Linéaires)

  2018cites this paper
• Pseudo-Bayesian Learning with Kernel Fourier Transform as Prior

  2018cites this paper