Optimization

Estimating the “Wrong” Graphical Model: Benefits in the Computation-Limited Setting JMLR 2006 Evolutionary Function Approximation for Reinforcement Learning JMLR 2006 Exact 1-Norm Support Vector Machines Via Unconstrained Convex Differentiable Minimization JMLR 2006 Exploiting Locality in SLAM by Nested Dissection RSS 2006 Fast Computation of Graph Kernels NeurIPS 2006 Fast Iterative Kernel PCA NeurIPS 2006 Generalized Regularized Least-Squares Learning with Predefined Features in a Hilbert Space NeurIPS 2006 Graph Laplacian Regularization for Large-Scale Semidefinite Programming NeurIPS 2006 Hyperparameter Learning for Graph Based Semi-supervised Learning Algorithms NeurIPS 2006 implicit Online Learning with Kernels NeurIPS 2006 Integrated Planning and Control for Convex-bodied Nonholonomic systems using Local Feedback Control Policies RSS 2006 Large Margin Multi-channel Analog-to-Digital Conversion with Applications to Neural Prosthesis NeurIPS 2006 Large Scale Multiple Kernel Learning JMLR 2006 Large-Scale Sparsified Manifold Regularization NeurIPS 2006 Learning to Rank with Nonsmooth Cost Functions NeurIPS 2006 Linearly-solvable Markov decision problems NeurIPS 2006 Linear Programming Relaxations and Belief Propagation -- An Empirical Study JMLR 2006 Linear Programs for Hypotheses Selection in Probabilistic Inference Models JMLR 2006 Linear State-Space Models for Blind Source Separation JMLR 2006 Maximum-Gain Working Set Selection for SVMs JMLR 2006 Max-margin classification of incomplete data NeurIPS 2006 Multiple Instance Learning for Computer Aided Diagnosis NeurIPS 2006 New Algorithms for Efficient High-Dimensional Nonparametric Classification JMLR 2006 Nonnegative Sparse PCA NeurIPS 2006 Non-rigid point set registration: Coherent Point Drift NeurIPS 2006