Part 1: Optimization and Applications

[1]  Pablo A. Parrilo,et al.  Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization , 2007, SIAM Rev..

[2]  Edoardo Amaldi,et al.  On the Approximability of Minimizing Nonzero Variables or Unsatisfied Relations in Linear Systems , 1998, Theor. Comput. Sci..

[3]  Stephen J. Wright,et al.  Simultaneous Variable Selection , 2005, Technometrics.

[4]  S. Mallat,et al.  Adaptive greedy approximations , 1997 .

[5]  Emmanuel J. Candès,et al.  Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information , 2004, IEEE Transactions on Information Theory.

[6]  S. Frick,et al.  Compressed Sensing , 2014, Computer Vision, A Reference Guide.

[7]  Wotao Yin,et al.  Extracting Salient Features From Less Data via ! 1 -Minimization , 2008 .

[8]  Julien Mairal,et al.  Network Flow Algorithms for Structured Sparsity , 2010, NIPS.

[9]  Robert D. Nowak,et al.  Signal Reconstruction From Noisy Random Projections , 2006, IEEE Transactions on Information Theory.

[10]  Mark W. Schmidt,et al.  Convex Structure Learning in Log-Linear Models: Beyond Pairwise Potentials , 2010, AISTATS.

[11]  Noah A. Smith,et al.  Structured Sparsity in Structured Prediction , 2011, EMNLP.

[12]  R. Tibshirani Regression Shrinkage and Selection via the Lasso , 1996 .

[13]  Stephen J. Wright,et al.  Sparse Reconstruction by Separable Approximation , 2008, IEEE Transactions on Signal Processing.

[14]  P. Zhao,et al.  Grouped and Hierarchical Model Selection through Composite Absolute Penalties , 2007 .

[15]  Rich Caruana,et al.  Multitask Learning , 1998, Encyclopedia of Machine Learning and Data Mining.

[16]  Robert D. Nowak,et al.  Space–time event sparse penalization for magneto-/electroencephalography , 2009, NeuroImage.

[17]  Sergey Bakin,et al.  Adaptive regression and model selection in data mining problems , 1999 .

[18]  Julien Mairal,et al.  Structured sparsity through convex optimization , 2011, ArXiv.

[19]  Ben Taskar,et al.  Joint covariate selection and joint subspace selection for multiple classification problems , 2010, Stat. Comput..

[20]  Shiqian Ma,et al.  Fixed point and Bregman iterative methods for matrix rank minimization , 2009, Math. Program..

[21]  Eric P. Xing,et al.  Tree-Guided Group Lasso for Multi-Task Regression with Structured Sparsity , 2009, ICML.

[22]  Eric P. Xing,et al.  Discovering Sociolinguistic Associations with Structured Sparsity , 2011, ACL.

[23]  E. Candès,et al.  Stable signal recovery from incomplete and inaccurate measurements , 2005, math/0503066.

[24]  Emmanuel J. Candès,et al.  A Singular Value Thresholding Algorithm for Matrix Completion , 2008, SIAM J. Optim..

[25]  Pablo A. Parrilo,et al.  The Convex Geometry of Linear Inverse Problems , 2010, Foundations of Computational Mathematics.

[26]  M. Yuan,et al.  Model selection and estimation in regression with grouped variables , 2006 .

[27]  Andrej Yu. Garnaev,et al.  On widths of the Euclidean Ball , 1984 .

[28]  Babak Hassibi,et al.  On the Reconstruction of Block-Sparse Signals With an Optimal Number of Measurements , 2008, IEEE Transactions on Signal Processing.

[29]  Marc E. Pfetsch,et al.  The Computational Complexity of RIP, NSP, and Related Concepts in Compressed Sensing , 2012, ArXiv.

[30]  Michael A. Saunders,et al.  Atomic Decomposition by Basis Pursuit , 1998, SIAM J. Sci. Comput..

[31]  S. Muthukrishnan,et al.  Data streams: algorithms and applications , 2005, SODA '03.

[32]  Ben Taskar,et al.  Posterior vs Parameter Sparsity in Latent Variable Models , 2009, NIPS.

[33]  Trevor Darrell,et al.  An Efficient Projection for l 1 , ∞ Regularization , 2009 .