Proximal Methods for Sparse Optimal Scoring and Discriminant Analysis
DOI10.48550/arXiv.1705.07194arXiv1705.07194OpenAlexW2617985792MaRDI QIDQ97534
Summer Atkins, Gudmundur Einarsson, Brendan Ames, Line Clemmensen, Line Clemmensen, Gudmundur Einarsson, Summer Atkins, Brendan P. W. Ames
Publication date: 19 May 2017
Published in: Advances in Data Analysis and Classification. ADAC (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1705.07194
alternating direction method of multipliersproximal gradient methodoptimal scoringsparse discriminant analysis
Classification and discrimination; cluster analysis (statistical aspects) (62H30) Generalized linear models (logistic models) (62J12) Nonconvex programming, global optimization (90C26)
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Cites Work
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- Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
- Alternating direction method of multipliers for penalized zero-variance discriminant analysis
- Smooth minimization of non-smooth functions
- A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
- Gradient methods for minimizing composite functions
- Fast alternating linearization methods for minimizing the sum of two convex functions
- Sparse linear discriminant analysis by thresholding for high dimensional data
- High-dimensional classification using features annealed independence rules
- Spatial variation. 2nd ed
- Class prediction by nearest shrunken centroids, with applications to DNA microarrays.
- Least angle regression. (With discussion)
- Penalized discriminant analysis
- Adaptive restart for accelerated gradient schemes
- On the global and linear convergence of the generalized alternating direction method of multipliers
- On the $O(1/n)$ Convergence Rate of the Douglas–Rachford Alternating Direction Method
- Penalized Classification using Fisher’s Linear Discriminant
- A direct approach to sparse discriminant analysis in ultra-high dimensions
- A Direct Estimation Approach to Sparse Linear Discriminant Analysis
- Analysis and Design of Optimization Algorithms via Integral Quadratic Constraints
- Flexible Discriminant Analysis by Optimal Scoring
- First-Order Methods in Optimization
- Multiclass Sparse Discriminant Analysis
- Linear Coupling: An Ultimate Unification of Gradient and Mirror Descent
- Regularization and Variable Selection Via the Elastic Net
- The elements of statistical learning. Data mining, inference, and prediction
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