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SIAMJO
2008
93views more  SIAMJO 2008»
15 years 6 months ago
Smooth Optimization with Approximate Gradient
We show that the optimal complexity of Nesterov's smooth first-order optimization algorithm is preserved when the gradient is only computed up to a small, uniformly bounded er...
Alexandre d'Aspremont
TALG
2008
86views more  TALG 2008»
15 years 6 months ago
Embeddings of negative-type metrics and an improved approximation to generalized sparsest cut
In this paper, we study the metrics of negative type, which are metrics (V, d) such that d is an Euclidean metric; these metrics are thus also known as " 2-squared" met...
Shuchi Chawla, Anupam Gupta, Harald Räcke
TFS
2008
109views more  TFS 2008»
15 years 5 months ago
Comments on "Fuzzy Probabilistic Approximation Spaces and Their Information Measures"
Some errors in our original paper in defining relative reduct with information measures are pointed out in this paper. It is shown that in our original work, Theorems 10 and 19 hol...
Qinghua Hu, Zongxia Xie, Daren Yu
ORL
2011
15 years 1 months ago
Convex approximations to sparse PCA via Lagrangian duality
We derive a convex relaxation for cardinality constrained Principal Component Analysis (PCA) by using a simple representation of the L1 unit ball and standard Lagrangian duality. ...
Ronny Luss, Marc Teboulle
ICCV
1999
IEEE
16 years 8 months ago
Fast Approximate Energy Minimization via Graph Cuts
In this paper we address the problem of minimizing a large class of energy functions that occur in early vision. The major restriction is that the energy function's smoothnes...
Yuri Boykov, Olga Veksler, Ramin Zabih