Optimization

Learning Translation Invariant Kernels for Classification JMLR 2010 Learning via Gaussian Herding NeurIPS 2010 Linear Complementarity for Regularized Policy Evaluation and Improvement NeurIPS 2010 Lower Bounds on Rate of Convergence of Cutting Plane Methods NeurIPS 2010 LSTD with Random Projections NeurIPS 2010 MAP Estimation for Graphical Models by Likelihood Maximization NeurIPS 2010 MAP estimation in Binary MRFs via Bipartite Multi-cuts NeurIPS 2010 Model-based Boosting 2.0 JMLR 2010 Moreau-Yosida Regularization for Grouped Tree Structure Learning NeurIPS 2010 Multi-label Multiple Kernel Learning by Stochastic Approximation: Application to Visual Object Recognition NeurIPS 2010 Multiple Kernel Learning and the SMO Algorithm NeurIPS 2010 Multi-Priority Cartesian Impedance Control RSS 2010 Multi-Stage Dantzig Selector NeurIPS 2010 Natural Policy Gradient Methods with Parameter-based Exploration for Control Tasks NeurIPS 2010 Network Flow Algorithms for Structured Sparsity NeurIPS 2010 Occlusion Detection and Motion Estimation with Convex Optimization NeurIPS 2010 On Herding and the Perceptron Cycling Theorem NeurIPS 2010 Online Learning in The Manifold of Low-Rank Matrices NeurIPS 2010 On the Convergence Properties of Contrastive Divergence AISTATS 2010 On the Convexity of Latent Social Network Inference NeurIPS 2010 On the Impact of Kernel Approximation on Learning Accuracy AISTATS 2010 Optimal Allocation Strategies for the Dark Pool Problem AISTATS 2010 Parallelized Stochastic Gradient Descent NeurIPS 2010 Parametric Bandits: The Generalized Linear Case NeurIPS 2010 Penalized Principal Component Regression on Graphs for Analysis of Subnetworks NeurIPS 2010