Convex Optimization

Efficient Structured Matrix Rank Minimization NeurIPS 2014 Optimization Methods for Sparse Pseudo-Likelihood Graphical Model Selection NeurIPS 2014 Partition-wise Linear Models NeurIPS 2014 Convex Two-Layer Modeling NeurIPS 2013 Learning with Invariance via Linear Functionals on Reproducing Kernel Hilbert Space NeurIPS 2013 Linear Convergence with Condition Number Independent Access of Full Gradients NeurIPS 2013 Maximum Volume Clustering: A New Discriminative Clustering Approach JMLR 2013 Mixed Optimization for Smooth Functions NeurIPS 2013 Non-strongly-convex smooth stochastic approximation with convergence rate O(1/n) NeurIPS 2013 On model selection consistency of penalized M-estimators: a geometric theory NeurIPS 2013 On the Linear Convergence of the Proximal Gradient Method for Trace Norm Regularization NeurIPS 2013 Sparse Overlapping Sets Lasso for Multitask Learning and its Application to fMRI Analysis NeurIPS 2013 Unsupervised Spectral Learning of Finite State Transducers NeurIPS 2013 A quasi-Newton proximal splitting method NeurIPS 2012 Convex Multi-view Subspace Learning NeurIPS 2012 Ensemble weighted kernel estimators for multivariate entropy estimation NeurIPS 2012 Mirror Descent Meets Fixed Share (and feels no regret) NeurIPS 2012 Multiclass Learning with Simplex Coding NeurIPS 2012 Recovery of Sparse Probability Measures via Convex Programming NeurIPS 2012 Sparse Prediction with the k-Support Norm NeurIPS 2012 Volume Regularization for Binary Classification NeurIPS 2012 Convergence Rates of Inexact Proximal-Gradient Methods for Convex Optimization NeurIPS 2011 Learning large-margin halfspaces with more malicious noise NeurIPS 2011 Maximum Margin Multi-Label Structured Prediction NeurIPS 2011 Non-Asymptotic Analysis of Stochastic Approximation Algorithms for Machine Learning NeurIPS 2011