Optimization

An Inverse Power Method for Nonlinear Eigenproblems with Applications in 1-Spectral Clustering and Sparse PCA NeurIPS 2010 A Non-invasive Real-Time Method for Measuring Variable Stiffness RSS 2010 Approximate Riemannian Conjugate Gradient Learning for Fixed-Form Variational Bayes JMLR 2010 Approximate Tree Kernels JMLR 2010 A Primal-Dual Algorithm for Group Sparse Regularization with Overlapping Groups NeurIPS 2010 A Primal-Dual Message-Passing Algorithm for Approximated Large Scale Structured Prediction NeurIPS 2010 A Quasi-Newton Approach to Nonsmooth Convex Optimization Problems in Machine Learning JMLR 2010 A Regularization Approach to Nonlinear Variable Selection AISTATS 2010 Avoiding False Positive in Multi-Instance Learning NeurIPS 2010 Basis Construction from Power Series Expansions of Value Functions NeurIPS 2010 Batch Bayesian Optimization via Simulation Matching NeurIPS 2010 Boosted Optimization for Network Classification AISTATS 2010 Boosting Classifier Cascades NeurIPS 2010 Bundle Methods for Regularized Risk Minimization JMLR 2010 Collaborative Filtering in a Non-Uniform World: Learning with the Weighted Trace Norm NeurIPS 2010 Consensus-Based Distributed Support Vector Machines JMLR 2010 Convex Multiple-Instance Learning by Estimating Likelihood Ratio NeurIPS 2010 Convex Structure Learning in Log-Linear Models: Beyond Pairwise Potentials AISTATS 2010 Deciphering subsampled data: adaptive compressive sampling as a principle of brain communication NeurIPS 2010 Decomposing Isotonic Regression for Efficiently Solving Large Problems NeurIPS 2010 Descent Methods for Tuning Parameter Refinement AISTATS 2010 Direct Loss Minimization for Structured Prediction NeurIPS 2010 Distributed Optimization with Pairwise Constraints and its Application to Multi-robot Path Planning RSS 2010 Distributionally Robust Markov Decision Processes NeurIPS 2010 Dual Averaging Methods for Regularized Stochastic Learning and Online Optimization JMLR 2010