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Continuous Optimization

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Papers

Minimax Statistical Learning with Wasserstein distances NIPS 2018
Efficient High Dimensional Bayesian Optimization with Additivity and Quadrature Fourier Features NIPS 2018
Efficient Algorithms for Non-convex Isotonic Regression through Submodular Optimization NIPS 2018
Learning Bounds for Greedy Approximation with Explicit Feature Maps from Multiple Kernels NIPS 2018
Benefits of over-parameterization with EM NIPS 2018
Legendre Decomposition for Tensors NIPS 2018
Quadratic Decomposable Submodular Function Minimization NIPS 2018
Gradient Descent Meets Shift-and-Invert Preconditioning for Eigenvector Computation NIPS 2018
Bayesian Quadrature for Multiple Related Integrals ICML 2018
Improving Coverage and Runtime Complexity for Exact Inference in Non-Projective Transition-Based Dependency Parsers NAACL 2018
On Controllable Sparse Alternatives to Softmax NIPS 2018
Lyapunov Functions for First-Order Methods: Tight Automated Convergence Guarantees ICML 2018
Low-rank Interaction with Sparse Additive Effects Model for Large Data Frames NIPS 2018
Proximal SCOPE for Distributed Sparse Learning NIPS 2018
Adaptive Negative Curvature Descent with Applications in Non-convex Optimization NIPS 2018
How to tell when a clustering is (approximately) correct using convex relaxations NIPS 2018
An Efficient Pruning Algorithm for Robust Isotonic Regression NIPS 2018
Learning convex bounds for linear quadratic control policy synthesis NIPS 2018
Online Improper Learning with an Approximation Oracle NIPS 2018
A Unified Dynamic Approach to Sparse Model Selection AISTATS 2018
Labeled Graph Clustering via Projected Gradient Descent AISTATS 2018
A theory on the absence of spurious solutions for nonconvex and nonsmooth optimization NIPS 2018
Approximate message passing for amplitude based optimization ICML 2018
On Acceleration with Noise-Corrupted Gradients ICML 2018
Metron: NFV Service Chains at the True Speed of the Underlying Hardware NSDI 2018