BrainStorming 樊艳波

Outline Several papers on icml15 & cvpr15 PALM Information Theory Learning.

Multi-view Sparse Co-clustering via Proximal Alternating Linearized Minimization(CVPR15) Single view rank-one approximation.

Multi-view co-clustering Objective Function. Optimization: PALM.

Proximal Alternating Linearized Minimization for Nonconvex and Nonsmooth Problems(Bolte, Mathematical Programming14) General nonconvex nonsmooth function Example:

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.

Proposed PALM method Idea: linear expansion

Proposed PALM method Algorithm.

An example: Sparse NMF Generate

Entropic Graph-based Posterior Regularization. MaxwellW Libbrecht(ICML15) Objective Function. R: regularization term over, Existing ways ： L0, L1, L2...

Posterior Regularization Posterior regularization: –Nearby variables have simple posterior distributions. –More nature. Formulation.

Optimation & Simulations EM-like algorithm. has closed form.

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.

Just for Insights

Optimal Graph Learning with Partial Tags and Multiple Features for Image and Video Annotation.(CVPR15) Extensions: out of sample annotation; noise label information.

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...