Optimization

Efficient algorithms for learning kernels from multiple similarity matrices with general convex loss functions NeurIPS 2010 Efficient and Robust Feature Selection via Joint ℓ2,1-Norms Minimization NeurIPS 2010 Efficient Minimization of Decomposable Submodular Functions NeurIPS 2010 Ellipsoidal Support Vector Machines ACML 2010 Energy Disaggregation via Discriminative Sparse Coding NeurIPS 2010 Error Propagation for Approximate Policy and Value Iteration NeurIPS 2010 Exploiting Covariate Similarity in Sparse Regression via the Pairwise Elastic Net AISTATS 2010 Exploiting Feature Covariance in High-Dimensional Online Learning AISTATS 2010 Exploiting Within-Clique Factorizations in Junction-Tree Algorithms AISTATS 2010 Fast Active-set-type Algorithms for l1-regularized Linear Regression AISTATS 2010 Fast detection of multiple change-points shared by many signals using group LARS NeurIPS 2010 Fast global convergence rates of gradient methods for high-dimensional statistical recovery NeurIPS 2010 Fast Large-scale Mixture Modeling with Component-specific Data Partitions NeurIPS 2010 Generalized roof duality and bisubmodular functions NeurIPS 2010 Global Analytic Solution for Variational Bayesian Matrix Factorization NeurIPS 2010 Guaranteed Rank Minimization via Singular Value Projection NeurIPS 2010 Implicit Differentiation by Perturbation NeurIPS 2010 Individualized ROI Optimization via Maximization of Group-wise Consistency of Structural and Functional Profiles NeurIPS 2010 Inductive Principles for Restricted Boltzmann Machine Learning AISTATS 2010 Iterative Scaling and Coordinate Descent Methods for Maximum Entropy Models JMLR 2010 Learning Bayesian Network Structure using LP Relaxations AISTATS 2010 Learning Kernels with Radiuses of Minimum Enclosing Balls NeurIPS 2010 Learning Multiple Tasks using Manifold Regularization NeurIPS 2010 Learning Nonlinear Dynamic Models from Non-sequenced Data AISTATS 2010 Learning Polyhedral Classifiers Using Logistic Function ACML 2010