Greedy Algorithms for Structurally Constrained High Dimensional Problems
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Pradeep Ravikumar | Inderjit S. Dhillon | Ambuj Tewari | I. Dhillon | Ambuj Tewari | Pradeep Ravikumar
[1] Philip Wolfe,et al. An algorithm for quadratic programming , 1956 .
[2] G. Pisier. Martingales with values in uniformly convex spaces , 1975 .
[3] C. Darken,et al. Constructive Approximation Rates of Convex Approximation in Non-hilbert Spaces , 2022 .
[4] Tong Zhang,et al. Sequential greedy approximation for certain convex optimization problems , 2003, IEEE Trans. Inf. Theory.
[5] Robert E. Schapire,et al. The Boosting Approach to Machine Learning An Overview , 2003 .
[6] A. Pietsch. History of Banach Spaces and Linear Operators , 2007 .
[7] J. Borwein,et al. Uniformly convex functions on Banach spaces , 2008 .
[8] Kenneth L. Clarkson,et al. Coresets, sparse greedy approximation, and the Frank-Wolfe algorithm , 2008, SODA '08.
[9] Martin J. Wainwright,et al. A unified framework for high-dimensional analysis of $M$-estimators with decomposable regularizers , 2009, NIPS.
[10] Xi Chen,et al. Nonparametric Greedy Algorithms for the Sparse Learning Problem , 2009, NIPS.
[11] Naoki Abe,et al. Grouped Orthogonal Matching Pursuit for Variable Selection and Prediction , 2009, NIPS.
[12] Tong Zhang,et al. Trading Accuracy for Sparsity in Optimization Problems with Sparsity Constraints , 2010, SIAM J. Optim..
[13] Martin J. Wainwright,et al. Fast global convergence rates of gradient methods for high-dimensional statistical recovery , 2010, NIPS.
[14] Naoki Abe,et al. Group Orthogonal Matching Pursuit for Logistic Regression , 2011, AISTATS.
[15] Vladimir Temlyakov,et al. CAMBRIDGE MONOGRAPHS ON APPLIED AND COMPUTATIONAL MATHEMATICS , 2022 .
[16] Ohad Shamir,et al. Large-Scale Convex Minimization with a Low-Rank Constraint , 2011, ICML.
[17] Abhimanyu Das,et al. Submodular meets Spectral: Greedy Algorithms for Subset Selection, Sparse Approximation and Dictionary Selection , 2011, ICML.
[18] Pablo A. Parrilo,et al. The Convex Geometry of Linear Inverse Problems , 2010, Foundations of Computational Mathematics.
[19] Martin Jaggi,et al. Revisiting Frank-Wolfe: Projection-Free Sparse Convex Optimization , 2013, ICML.
[20] Christopher J. Hillar,et al. Most Tensor Problems Are NP-Hard , 2009, JACM.