Optimization

A Constraint Generation Approach to Learning Stable Linear Dynamical Systems NeurIPS 2007 Better than least squares: comparison of objective functions for estimating linear-nonlinear models NeurIPS 2007 Efficient Principled Learning of Thin Junction Trees NeurIPS 2007 Learning Equivariant Functions with Matrix Valued Kernels JMLR 2007 Minimax Regret Classifier for Imprecise Class Distributions JMLR 2007 Optimistic Linear Programming gives Logarithmic Regret for Irreducible MDPs NeurIPS 2007 Progressive mixture rules are deviation suboptimal NeurIPS 2007 A Complexity-Distortion Approach to Joint Pattern Alignment NeurIPS 2006 An Efficient Method for Gradient-Based Adaptation of Hyperparameters in SVM Models NeurIPS 2006 A recipe for optimizing a time-histogram NeurIPS 2006 Balanced Graph Matching NeurIPS 2006 Doubly Stochastic Normalization for Spectral Clustering NeurIPS 2006 Fast Iterative Kernel PCA NeurIPS 2006 implicit Online Learning with Kernels NeurIPS 2006 Large Margin Multi-channel Analog-to-Digital Conversion with Applications to Neural Prosthesis NeurIPS 2006 Linear Programs for Hypotheses Selection in Probabilistic Inference Models JMLR 2006 Online Clustering of Moving Hyperplanes NeurIPS 2006 The Robustness-Performance Tradeoff in Markov Decision Processes NeurIPS 2006 Learning the Kernel with Hyperkernels JMLR 2005 Distributional Scaling: An Algorithm for Structure-Preserving Embedding of Metric and Nonmetric Spaces JMLR 2004 Prior Knowledge and Preferential Structures in Gradient Descent Learning Algorithms JMLR 2001