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Optimization

14,207 papers

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Papers

Collaboratively Learning Preferences from Ordinal Data NIPS 2015
A Universal Primal-Dual Convex Optimization Framework NIPS 2015
Structured Estimation with Atomic Norms: General Bounds and Applications NIPS 2015
Exactness of Approximate MAP Inference in Continuous MRFs NIPS 2015
Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks NIPS 2015
Path-SGD: Path-Normalized Optimization in Deep Neural Networks NIPS 2015
Variance Reduced Stochastic Gradient Descent with Neighbors NIPS 2015
HONOR: Hybrid Optimization for NOn-convex Regularized problems NIPS 2015
Fast Randomized Kernel Ridge Regression with Statistical Guarantees NIPS 2015
Collaborative Filtering with Graph Information: Consistency and Scalable Methods NIPS 2015
Preconditioned Spectral Descent for Deep Learning NIPS 2015
Accelerated Mirror Descent in Continuous and Discrete Time NIPS 2015
Accelerated Proximal Gradient Methods for Nonconvex Programming NIPS 2015
Monotone k-Submodular Function Maximization with Size Constraints NIPS 2015
Spherical Random Features for Polynomial Kernels NIPS 2015
A Dual Augmented Block Minimization Framework for Learning with Limited Memory NIPS 2015
Decomposition Bounds for Marginal MAP NIPS 2015
Maximum Margin Partial Label Learning ACML 2015
Robust Multivariate Regression with Grossly Corrupted Observations and Its Application to Personality Prediction ACML 2015
Proximal Average Approximated Incremental Gradient Method for Composite Penalty Regularized Empirical Risk Minimization ACML 2015
Regularized Policy Gradients: Direct Variance Reduction in Policy Gradient Estimation ACML 2015
One-Pass Multi-View Learning ACML 2015
Parameter Estimation of Generalized Linear Models without Assuming their Link Function AISTATS 2015
Unifying Local Consistency and MAX SAT Relaxations for Scalable Inference with Rounding Guarantees AISTATS 2015
Stochastic Spectral Descent for Restricted Boltzmann Machines AISTATS 2015