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Papers (including subtopics)

Dueling Bandits: Beyond Condorcet Winners to General Tournament Solutions NeurIPS 2016 d-VMP: Distributed Variational Message Passing PGM 2016 EC-Cache: Load-Balanced, Low-Latency Cluster Caching with Online Erasure Coding OSDI 2016 Efficient Algorithms for Large-scale Generalized Eigenvector Computation and Canonical Correlation Analysis ICML 2016 Efficient and Robust Color Consistency for Community Photo Collections CVPR 2016 Efficient approaches for escaping higher order saddle points in non-convex optimization COLT 2016 Efficient Bregman Projections onto the Permutahedron and Related Polytopes AISTATS 2016 Efficient Globally Convergent Stochastic Optimization for Canonical Correlation Analysis NeurIPS 2016 Efficient Globally Optimal 2D-To-3D Deformable Shape Matching CVPR 2016 Efficient Nonparametric Smoothness Estimation NeurIPS 2016 Efficient Point Process Inference for Large-Scale Object Detection CVPR 2016 Efficient Second Order Online Learning by Sketching NeurIPS 2016 Entropy Coding of Spectral Envelopes for Speech and Audio Coding Using Distribution Quantization Interspeech 2016 e-PAL: An Active Learning Approach to the Multi-Objective Optimization Problem JMLR 2016 Epigraph projections for fast general convex programming ICML 2016 Equivalence of Graphical Lasso and Thresholding for Sparse Graphs JMLR 2016 Estimating Maximum Expected Value through Gaussian Approximation ICML 2016 Estimating Sparse Signals With Smooth Support via Convex Programming and Block Sparsity CVPR 2016 Estimation from Indirect Supervision with Linear Moments ICML 2016 Even Faster Accelerated Coordinate Descent Using Non-Uniform Sampling ICML 2016 Exact Inference on Gaussian Graphical Models of Arbitrary Topology using Path-Sums JMLR 2016 Exact Recovery of Hard Thresholding Pursuit NeurIPS 2016 Experimental Design on a Budget for Sparse Linear Models and Applications ICML 2016 Exploiting Spectral-Spatial Correlation for Coded Hyperspectral Image Restoration CVPR 2016 Exploiting the Structure: Stochastic Gradient Methods Using Raw Clusters NeurIPS 2016