scientific article; zbMATH DE number 7064037

zbMath1489.62189MaRDI QIDQ5381110

Sinno Jialin Pan, Mingkui Tan, Ivor W. Tsang, Joey Tianyi Zhou

Publication date: 7 June 2019

Full work available at URL: http://jmlr.csail.mit.edu/papers/v20/13-580.html

Title: zbMATH Open Web Interface contents unavailable due to conflicting licenses.

zbMATH Keywords

compressed sensingmulti-class classificationheterogeneous domain adaptation

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05)

Uses Software

• LIBLINEAR

Cites Work

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• Non-negative least squares for high-dimensional linear models: consistency and sparse recovery without regularization
• Asymmetric and category invariant feature transformations for domain adaptation
• The sparsity and bias of the LASSO selection in high-dimensional linear regression
• Convex multi-task feature learning
• A simple proof of the restricted isometry property for random matrices
• Nonnegative-Lasso and application in index tracking
• A theory of learning from different domains
• Counting the faces of randomly-projected hypercubes and orthants, with applications
• \(N\)-ary decomposition for multi-class classification
• 10.1162/15324430152733133
• On the Uniqueness of Nonnegative Sparse Solutions to Underdetermined Systems of Equations
• A Unique “Nonnegative” Solution to an Underdetermined System: From Vectors to Matrices
• Matching Pursuit LASSO Part I: Sparse Recovery Over Big Dictionary
• Matching Pursuit LASSO Part II: Applications and Sparse Recovery Over Batch Signals
• On the Non-Negative Garrotte Estimator
• Stable signal recovery from incomplete and inaccurate measurements
• Compressed sensing

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