Optimization

Efficient variable selection in support vector machines via the alternating direction method of multipliers AISTATS 2011 Empirical Risk Minimization of Graphical Model Parameters Given Approximate Inference, Decoding, and Model Structure AISTATS 2011 Exploiting Variable Stiffness in Explosive Movement Tasks RSS 2011 Faster Algorithms for Max-Product Message-Passing JMLR 2011 Follow-the-Regularized-Leader and Mirror Descent: Equivalence Theorems and L1 Regularization AISTATS 2011 Generalised Coupled Tensor Factorisation NeurIPS 2011 Generative Kernels for Exponential Families AISTATS 2011 Greedy Algorithms for Structurally Constrained High Dimensional Problems NeurIPS 2011 Greedy Model Averaging NeurIPS 2011 Group Lasso Estimation of High-dimensional Covariance Matrices JMLR 2011 Hashing Algorithms for Large-Scale Learning NeurIPS 2011 High-dimensional regression with noisy and missing data: Provable guarantees with non-convexity NeurIPS 2011 Higher-Order Correlation Clustering for Image Segmentation NeurIPS 2011 Hogwild!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent NeurIPS 2011 Hyper-Sparse Optimal Aggregation JMLR 2011 Iterative Learning for Reliable Crowdsourcing Systems NeurIPS 2011 Large-Scale Sparse Principal Component Analysis with Application to Text Data NeurIPS 2011 Learning in Hilbert vs. Banach Spaces: A Measure Embedding Viewpoint NeurIPS 2011 Learning large-margin halfspaces with more malicious noise NeurIPS 2011 Learning Sparse Representations of High Dimensional Data on Large Scale Dictionaries NeurIPS 2011 Learning to Locate Relative Outliers ACML 2011 Learning to Search Efficiently in High Dimensions NeurIPS 2011 Learning with Structured Sparsity JMLR 2011 Learning with the weighted trace-norm under arbitrary sampling distributions NeurIPS 2011 Linearized Alternating Direction Method with Adaptive Penalty for Low-Rank Representation NeurIPS 2011