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Found 4 papers, 1 papers with code
A Bi-level Nonlinear Eigenvector Algorithm for Wasserstein Discriminant Analysis
Much like the classical Fisher linear discriminant analysis (LDA), the recently proposed Wasserstein discriminant analysis (WDA) is a linear dimensionality reduction method that seeks a projection matrix to maximize the dispersion of different data classes and minimize the dispersion of same data classes via a bi-level optimization.
Scalable Spectral Clustering with Group Fairness Constraints
In this paper, we present a scalable algorithm for spectral clustering (SC) with group fairness constraints.
Linear Constrained Rayleigh Quotient Optimization: Theory and Algorithms
We start by equivalently transforming CRQopt into an optimization problem, called LGopt, of minimizing the Lagrangian multiplier of CRQopt, and then an problem, called QEPmin, of finding the smallest eigenvalue of a quadratic eigenvalue problem.
A Self-consistent-field Iteration for Orthogonal Canonical Correlation Analysis
In this paper, we propose an alternating numerical scheme whose core is the sub-maximization problem in the trace-fractional form with an orthogonal constraint.
