Optimization

Learning with Transformation Invariant Kernels NeurIPS 2007 Linear programming analysis of loopy belief propagation for weighted matching NeurIPS 2007 Local Algorithms for Approximate Inference in Minor-Excluded Graphs NeurIPS 2007 McRank: Learning to Rank Using Multiple Classification and Gradient Boosting NeurIPS 2007 Message Passing for Max-weight Independent Set NeurIPS 2007 Minimax Regret Classifier for Imprecise Class Distributions JMLR 2007 Multi-Task Learning via Conic Programming NeurIPS 2007 New Outer Bounds on the Marginal Polytope NeurIPS 2007 Online Linear Regression and Its Application to Model-Based Reinforcement Learning NeurIPS 2007 Optimistic Linear Programming gives Logarithmic Regret for Irreducible MDPs NeurIPS 2007 Parallelizing Support Vector Machines on Distributed Computers NeurIPS 2007 Preventing Over-Fitting during Model Selection via Bayesian Regularisation of the Hyper-Parameters JMLR 2007 Progressive mixture rules are deviation suboptimal NeurIPS 2007 Random Features for Large-Scale Kernel Machines NeurIPS 2007 Random Sampling of States in Dynamic Programming NeurIPS 2007 Ranking the Best Instances JMLR 2007 Robust Regression with Twinned Gaussian Processes NeurIPS 2007 Selecting Observations against Adversarial Objectives NeurIPS 2007 Simplified Rules and Theoretical Analysis for Information Bottleneck Optimization and PCA with Spiking Neurons NeurIPS 2007 Simulated Annealing: Rigorous finite-time guarantees for optimization on continuous domains NeurIPS 2007 Spatially-Adaptive Learning Rates for Online Incremental SLAM RSS 2007 Stable Dual Dynamic Programming NeurIPS 2007 Stagewise Lasso JMLR 2007 Support Vector Machine Classification with Indefinite Kernels NeurIPS 2007 Temporal Difference Updating without a Learning Rate NeurIPS 2007