Robust Fisher Discriminant Analysis

By Seung-Jean Kim, A. Magnani, Stephen P. Boyd. 2005

135 citations recorded by the source corpus.

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Citations in the corpus

Frank-Wolfe Algorithms for Saddle Point Problems (2016, background): “Robust learning is also often cast as a saddle point minimax problem (Kim et al., 2005).”
Using Machine Teaching to Identify Optimal Training-Set Attacks on Machine Learners (2015, background): “Promising as the name suggests, we point out that robust learning is not an appropriate defense against training-set attacks.”
Nightmare at test time: robust learning by feature deletion (2006, background): “Robust minimax approaches to learning classiflers have recently attracted interest in the machine learning community (Lanckriet et al., 2004; El Ghaoui et al., 2003; Kim et al., 2006 ).”
Convex Adversarial Collective Classification (2013, methodology): “This results in a zero-sum game between the learner and adversary that can be solved using robust minimax methods as in (Lanckriet et al., 2004; El Ghaoui et al., 2003; Kim et al., 2006; Globerson & Roweis, 2006).”
Differentiating plant species within and across diverse ecosystems with imaging spectroscopy (2015, methodology): “Likewise, extensions to LDA have been proposed and tested, such as Robust Fisher's Discriminant Analysis, which directly incorporate measures of class uncertainty (Kim et al., 2005).”
Optimization for machine learning (2010, methodology): “, learning and planning (Nilim and El Ghaoui, 2005), Fisher linear discriminant analysis (Kim et al., 2005), PCA (d’Aspremont”
Dataset Shift in Machine Learning (2009, background): “Robust minimax approaches to learning classifiers have recently attracted interest in the machine learning community [Lanckriet et al., 2004; El Ghaoui et al., 2003; Kim et al., 2006].”
GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium (2019, background): “When it comes to solving saddle-point problems, it is the key (Kim et al., 2006) to achieve encompasses learning and the recreation of images (Chambolle & Pock, 2011).”
Theory and Applications of Robust Optimization (2010, background): “Lorenz and Boyd [99] consider the problem of building an array antenna with minimum variance when the underlying array response is not known exactly.”