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Optimization

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A Polylog Pivot Steps Simplex Algorithm for Classification NIPS 2012
Active Learning of Model Evidence Using Bayesian Quadrature NIPS 2012
Efficient Sampling for Bipartite Matching Problems NIPS 2012
On the (Non-)existence of Convex, Calibrated Surrogate Losses for Ranking NIPS 2012
Density Propagation and Improved Bounds on the Partition Function NIPS 2012
Isotropic Hashing NIPS 2012
On the Use of Non-Stationary Policies for Stationary Infinite-Horizon Markov Decision Processes NIPS 2012
Learning as MAP Inference in Discrete Graphical Models NIPS 2012
Stochastic optimization and sparse statistical recovery: Optimal algorithms for high dimensions NIPS 2012
A Simple and Practical Algorithm for Differentially Private Data Release NIPS 2012
Provable ICA with Unknown Gaussian Noise, with Implications for Gaussian Mixtures and Autoencoders NIPS 2012
Fast interior-point inference in high-dimensional sparse, penalized state-space models AISTATS 2012
Generalized Optimal Reverse Prediction AISTATS 2012
Sparsistency of the Edge Lasso over Graphs AISTATS 2012
Forward Basis Selection for Sparse Approximation over Dictionary AISTATS 2012
Sparse Additive Machine AISTATS 2012
Statistical Optimization in High Dimensions AISTATS 2012
Iterative Reweighted Algorithms for Matrix Rank Minimization JMLR 2012
Unified Algorithms for Online Learning and Competitive Analysis COLT 2012
Reconstruction from Anisotropic Random Measurements COLT 2012
Private Convex Empirical Risk Minimization and High-dimensional Regression COLT 2012
Krylov Subspace Descent for Deep Learning AISTATS 2012
SpeedBoost: Anytime Prediction with Uniform Near-Optimality AISTATS 2012
Open Problem: Is Averaging Needed for Strongly Convex Stochastic Gradient Descent? COLT 2012
Exact Covariance Thresholding into Connected Components for Large-Scale Graphical Lasso JMLR 2012