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CORR
2008
Springer
77views Education» more  CORR 2008»
15 years 4 months ago
Optimal hash functions for approximate closest pairs on the n-cube
One way to find closest pairs in large datasets is to use hash functions [6], [12]. In recent years locality-sensitive hash functions for various metrics have been given: projecti...
Daniel M. Gordon, Victor Miller, Peter Ostapenko
SIAMJO
2008
93views more  SIAMJO 2008»
15 years 4 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 4 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 3 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
14 years 11 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