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Published byPeter Todd Modified over 9 years ago
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BrainStorming 樊艳波 2015-7-20
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Outline Several papers on icml15 & cvpr15 PALM Information Theory Learning.
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Multi-view Sparse Co-clustering via Proximal Alternating Linearized Minimization(CVPR15) Single view rank-one approximation.
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Multi-view co-clustering Objective Function. Optimization: PALM.
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Proximal Alternating Linearized Minimization for Nonconvex and Nonsmooth Problems(Bolte, Mathematical Programming14) General nonconvex nonsmooth function Example:
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Coordinate descent methods Gauss-Seidel iteration scheme: –Drawback: strict convexity assumption. Proximal regularization of the Gauss-Seidel scheme: –Existing problems: Hard to optimize each step exactly.
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Proposed PALM method Idea: linear expansion
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Proposed PALM method Algorithm.
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An example: Sparse NMF Generate
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Entropic Graph-based Posterior Regularization. MaxwellW Libbrecht(ICML15) Objective Function. R: regularization term over, Existing ways : L0, L1, L2...
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Posterior Regularization Posterior regularization: –Nearby variables have simple posterior distributions. –More nature. Formulation.
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Optimation & Simulations EM-like algorithm. has closed form.
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Unsupervised Simultaneous Orthogonal Basis Clustering Feature Selection.(CVPR15) Regularized regression model: Proposed Model. B: latent cluster center. E: encoding matrix. each row of E has only one non-zero term.
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Just for Insights
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Optimal Graph Learning with Partial Tags and Multiple Features for Image and Video Annotation.(CVPR15) Extensions: out of sample annotation; noise label information.
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Information-Theoretic Dictionary Learning for Image Classification(TPAMI14) Traditional Dictionary learning. ITL based Dictionary learning. –D^{0}: initialization by k-svd or others. –Dictionary compactness: –Dictionary discrimination: –Dictionary representation: Optimization: gauss process, kernel density estimates...
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