README: Matlab codes for l1 methods
EE364b Convex Optimization II, S. Boyd

written by Almir Mutapcic, Seung-Jean Kim, Kwangmoo Koh, 
Joelle Skaf, and Argyris Zymnis.

Regressor selection example (S6.4 in BV book) 
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regressor_cvx.m -- selects sparse regressor using l1-norm regularization

Sparse signal reconstruction example
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spike_example.m -- reconstructs a spike signal using l1 regularization

Total variation reconstruction example (S6.3.3 in BV book)
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tv_cvx.m -- reconstructs an 1D signal using total variation

2D total variation reconstruction example
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tv2d.m -- reconstructs a 2D signal using total variation

Sparse solution of linear inequality example
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sparse_solution.m -- computes a sparse solution of linear inequalities
sparse_infeas_dual.m -- finds small subset of infeasible linear inequalities
sparse_infeas.m -- finds a point that satisfies many linear inequalities

Time series model change detection example
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model_change_detection.m -- piecewise constant AR model via iterated l1 
heuristic

Factor modeling example
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trace_heuristic.m -- fits a factor model using trace heuristic