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We provide an elementary proof of a simple, efficient algorithm for computing the Euclidean projection of a point onto the probability simplex.
An O ( n ) O(n) algorithm for quadratic knapsack problems
P. Brucker · 1984
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A finite algorithm for finding the projection of a point onto the canonical simplex of ℝ n \mathbb{R}^{n}
C. Michelot · 1986
Earlier work this paper cites.
An algorithm for a singly constrained class of quadratic programs subject to upper and lower bounds
P. M. Pardalos and N. Kovoor · 1990
Earlier work this paper cites.
Convex Optimization
S. Boyd and L. Vandenberghe · 2004
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Numerical Optimization
J. Nocedal and S. J. Wright · 2006
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Efficient learning of label ranking by soft projections onto polyhedra
S. Shalev-Shwartz and Y. Singer · 2006
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The K K -modes algorithm for clustering
M. Á. Carreira-Perpiñán and W. Wang
Cited in the paper.
A simple assignment model with Laplacian smoothing
M. Á. Carreira-Perpiñán and W. Wang
Cited in the paper.
Efficient projections onto the ℓ 1 \ell_{1} -ball for learning in high dimensions
J. Duchi, S. Shalev-Shwartz, Y. Singer, and T. Chandra · 2008
Later among the works it cites.
Y. Chen and X. Ye · 2011
Later among the works it cites.
Laplacian K K -modes clustering
W. Wang and M. Á. Carreira-Perpiñán · 2013
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