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Optimization

1184 directly classified papers

Papers per year

Papers

Fast Energy Minimization Using Learned State Filters CVPR 2013
Learning to Estimate and Remove Non-uniform Image Blur CVPR 2013
SWIGS: A Swift Guided Sampling Method CVPR 2013
Scoring anomalies: a M-estimation formulation AISTATS 2013
High-dimensional Inference via Lipschitz Sparsity-Yielding Regularizers AISTATS 2013
Affine Independent Variational Inference NIPS 2012
Lifted Linear Programming AISTATS 2012
Krylov Subspace Descent for Deep Learning AISTATS 2012
Weighted Likelihood Policy Search with Model Selection NIPS 2012
Minimax Multi-Task Learning and a Generalized Loss-Compositional Paradigm for MTL NIPS 2012
Minimizing Sparse High-Order Energies by Submodular Vertex-Cover NIPS 2012
Forging The Graphs: A Low Rank and Positive Semidefinite Graph Learning Approach NIPS 2012
Tensor Decomposition for Fast Parsing with Latent-Variable PCFGs NIPS 2012
Active Learning of Multi-Index Function Models NIPS 2012
Approximating Concavely Parameterized Optimization Problems NIPS 2012
SpeedBoost: Anytime Prediction with Uniform Near-Optimality AISTATS 2012
Matrix reconstruction with the local max norm NIPS 2012
Finding Exemplars from Pairwise Dissimilarities via Simultaneous Sparse Recovery NIPS 2012
Non-parametric Approximate Dynamic Programming via the Kernel Method NIPS 2012
Approximate Message Passing with Consistent Parameter Estimation and Applications to Sparse Learning NIPS 2012
Near-Optimal MAP Inference for Determinantal Point Processes NIPS 2012
Lifted coordinate descent for learning with trace-norm regularization AISTATS 2012
Generic Methods for Optimization-Based Modeling AISTATS 2012
There’s a Hole in My Data Space: Piecewise Predictors for Heterogeneous Learning Problems AISTATS 2012
Majorization for CRFs and Latent Likelihoods NIPS 2012