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Continuous Optimization

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Papers

Learning Sparse Gaussian Graphical Models with Overlapping Blocks NIPS 2016
Blind Image Deconvolution by Automatic Gradient Activation CVPR 2016
LazySVD: Even Faster SVD Decomposition Yet Without Agonizing Pain NIPS 2016
A Non-generative Framework and Convex Relaxations for Unsupervised Learning NIPS 2016
Rate Optimal Denoising of Simultaneously Sparse and Low Rank Matrices JMLR 2016
On Robustness of Kernel Clustering NIPS 2016
Structured Matrix Recovery via the Generalized Dantzig Selector NIPS 2016
SDP Relaxation with Randomized Rounding for Energy Disaggregation NIPS 2016
Exploiting Spectral-Spatial Correlation for Coded Hyperspectral Image Restoration CVPR 2016
Dual Decomposed Learning with Factorwise Oracle for Structural SVM of Large Output Domain NIPS 2016
Bayesian Intermittent Demand Forecasting for Large Inventories NIPS 2016
Convergence guarantees for kernel-based quadrature rules in misspecified settings NIPS 2016
Global Optimality of Local Search for Low Rank Matrix Recovery NIPS 2016
Fast Algorithms for Robust PCA via Gradient Descent NIPS 2016
Scalable and Sound Low-Rank Tensor Learning AISTATS 2016
Simplifying Gait Design via Shape Basis Optimization RSS 2016
Incremental Task and Motion Planning: A Constraint-Based Approach RSS 2016
Mixed Linear Regression with Multiple Components NIPS 2016
Reshaped Wirtinger Flow for Solving Quadratic System of Equations NIPS 2016
Near-Optimal Smoothing of Structured Conditional Probability Matrices NIPS 2016
Convergence of an Alternating Maximization Procedure JMLR 2016
Efficient and Robust Color Consistency for Community Photo Collections CVPR 2016
Large-Scale Optimization Algorithms for Sparse Conditional Gaussian Graphical Models AISTATS 2016
On the Iteration Complexity of Oblivious First-Order Optimization Algorithms ICML 2016
Riemannian SVRG: Fast Stochastic Optimization on Riemannian Manifolds NIPS 2016