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Optimization

14,969 papers

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Papers

Exploiting Covariate Similarity in Sparse Regression via the Pairwise Elastic Net AISTATS 2010
Exploiting Feature Covariance in High-Dimensional Online Learning AISTATS 2010
Inductive Principles for Restricted Boltzmann Machine Learning AISTATS 2010
Exploiting Within-Clique Factorizations in Junction-Tree Algorithms AISTATS 2010
A Regularization Approach to Nonlinear Variable Selection AISTATS 2010
Convex Structure Learning in Log-Linear Models: Beyond Pairwise Potentials AISTATS 2010
Polynomial-Time Exact Inference in NP-Hard Binary MRFs via Reweighted Perfect Matching AISTATS 2010
On the Convergence Properties of Contrastive Divergence AISTATS 2010
Sufficient Dimension Reduction via Squared-loss Mutual Information Estimation AISTATS 2010
Bundle Methods for Regularized Risk Minimization JMLR 2010
Approximate Tree Kernels JMLR 2010
A Fast Hybrid Algorithm for Large-Scale -Regularized Logistic Regression JMLR 2010
Iterative Scaling and Coordinate Descent Methods for Maximum Entropy Models JMLR 2010
A Quasi-Newton Approach to Nonsmooth Convex Optimization Problems in Machine Learning JMLR 2010
Learning Translation Invariant Kernels for Classification JMLR 2010
Training and Testing Low-degree Polynomial Data Mappings via Linear SVM JMLR 2010
Quadratic Programming Feature Selection JMLR 2010
Consensus-Based Distributed Support Vector Machines JMLR 2010
Model-based Boosting 2.0 JMLR 2010
Spectral Regularization Algorithms for Learning Large Incomplete Matrices JMLR 2010
Dual Averaging Methods for Regularized Stochastic Learning and Online Optimization JMLR 2010
Topology Selection in Graphical Models of Autoregressive Processes JMLR 2010
Tree Decomposition for Large-Scale SVM Problems JMLR 2010
A Comparison of Optimization Methods and Software for Large-scale L1-regularized Linear Classification JMLR 2010
Approximate Riemannian Conjugate Gradient Learning for Fixed-Form Variational Bayes JMLR 2010