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Continuous Optimization

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Papers

Rounding-based Moves for Semi-Metric Labeling JMLR 2016
Sparsity and Error Analysis of Empirical Feature-Based Regularization Schemes JMLR 2016
Iterative Hessian Sketch: Fast and Accurate Solution Approximation for Constrained Least-Squares JMLR 2016
Efficient Bregman Projections onto the Permutahedron and Related Polytopes AISTATS 2016
Megaman: Scalable Manifold Learning in Python JMLR 2016
New Perspectives on k-Support and Cluster Norms JMLR 2016
Optimal Estimation and Completion of Matrices with Biclustering Structures JMLR 2016
Gromov-Wasserstein Averaging of Kernel and Distance Matrices ICML 2016
Preconditioning Kernel Matrices ICML 2016
CMA-ES with Optimal Covariance Update and Storage Complexity NIPS 2016
Optimal spectral transportation with application to music transcription NIPS 2016
Sub-sampled Newton Methods with Non-uniform Sampling NIPS 2016
Solving Random Systems of Quadratic Equations via Truncated Generalized Gradient Flow NIPS 2016
Coordinate-wise Power Method NIPS 2016
A Multi-Batch L-BFGS Method for Machine Learning NIPS 2016
Learning Kernels with Random Features NIPS 2016
Agnostic Estimation for Misspecified Phase Retrieval Models NIPS 2016
SPALS: Fast Alternating Least Squares via Implicit Leverage Scores Sampling NIPS 2016
Faster Convex Optimization: Simulated Annealing with an Efficient Universal Barrier ICML 2016
A Convex Atomic-Norm Approach to Multiple Sequence Alignment and Motif Discovery ICML 2016
Cut Pursuit: Fast Algorithms to Learn Piecewise Constant Functions AISTATS 2016
Cross-Graph Learning of Multi-Relational Associations ICML 2016
Fast Dictionary Learning with a Smoothed Wasserstein Loss AISTATS 2016
On Graduated Optimization for Stochastic Non-Convex Problems ICML 2016
First-order Methods for Geodesically Convex Optimization COLT 2016