References & Further Reading

References

1. I. Daubechies, M. Defrise, and C. De Mol, An Iterative Thresholding Algorithm for Linear Inverse Problems with a Sparsity Constraint, 2004

   Originates ISTA.

2. A. Beck and M. Teboulle, A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems, 2009

   FISTA with $O(1/k^2)$ convergence.

3. Y. Nesterov, A Method of Solving a Convex Programming Problem with Convergence Rate $O(1/k^2)$, 1983

   Nesterov acceleration.

4. S. Boyd, N. Parikh, E. Chu, B. Peleato, and J. Eckstein, Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers, 2011

   Canonical ADMM monograph.

5. N. Parikh and S. Boyd, Proximal Algorithms, 2014

   Proximal operator framework.

6. J. A. Tropp, Greed is Good: Algorithmic Results for Sparse Approximation, 2004

   OMP analysis and coherence-based guarantees.

7. D. Needell and J. A. Tropp, CoSaMP: Iterative Signal Recovery from Incomplete and Inaccurate Samples, 2009

   CoSaMP algorithm and RIP-based guarantees.

8. T. Blumensath and M. E. Davies, Iterative Hard Thresholding for Compressed Sensing, 2009

   IHT algorithm and guarantees.

9. M. E. Tipping, Sparse Bayesian Learning and the Relevance Vector Machine, 2001

   Sparse Bayesian Learning (SBL).

10. D. P. Wipf and B. D. Rao, Sparse Bayesian Learning for Basis Selection, 2004

    SBL for sparse recovery, connection to LASSO.

11. M. A. T. Figueiredo, Adaptive Sparseness for Supervised Learning, 2003

    EM approach to sparse Bayesian regression.