Continuous Optimization

Probabilistic Linear Multistep Methods NeurIPS 2016 Proper Inner Product with Mean Displacement for Gaussian Noise Invariant ICA ACML 2016 Properly Learning Poisson Binomial Distributions in Almost Polynomial Time COLT 2016 Provable Tensor Methods for Learning Mixtures of Generalized Linear Models AISTATS 2016 Proximal Riemannian Pursuit for Large-Scale Trace-Norm Minimization CVPR 2016 Pymanopt: A Python Toolbox for Optimization on Manifolds using Automatic Differentiation JMLR 2016 Quadratic Optimization with Orthogonality Constraints: Explicit Lojasiewicz Exponent and Linear Convergence of Line-Search Methods ICML 2016 Rate Optimal Denoising of Simultaneously Sparse and Low Rank Matrices JMLR 2016 Recovery guarantee of weighted low-rank approximation via alternating minimization ICML 2016 Regularized Nonlinear Acceleration NeurIPS 2016 Reshaped Wirtinger Flow for Solving Quadratic System of Equations NeurIPS 2016 Riemannian SVRG: Fast Stochastic Optimization on Riemannian Manifolds NeurIPS 2016 Rounding-based Moves for Semi-Metric Labeling JMLR 2016 Scalable and Sound Low-Rank Tensor Learning AISTATS 2016 Scalable Exemplar Clustering and Facility Location via Augmented Block Coordinate Descent with Column Generation AISTATS 2016 Scene Labeling Using Sparse Precision Matrix CVPR 2016 SDP Relaxation with Randomized Rounding for Energy Disaggregation NeurIPS 2016 Semidefinite Programs for Exact Recovery of a Hidden Community COLT 2016 Semiparametric Differential Graph Models NeurIPS 2016 Simplifying Gait Design via Shape Basis Optimization RSS 2016 Simultaneous Optical Flow and Intensity Estimation From an Event Camera CVPR 2016 Single Pass PCA of Matrix Products NeurIPS 2016 Sliced Wasserstein Kernels for Probability Distributions CVPR 2016 Solving Random Systems of Quadratic Equations via Truncated Generalized Gradient Flow NeurIPS 2016 Solving Ridge Regression using Sketched Preconditioned SVRG ICML 2016