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» Introduction to Randomized Algorithms
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STOC
2010
ACM
189views Algorithms» more  STOC 2010»
16 years 1 months ago
Near-optimal extractors against quantum storage
We give near-optimal constructions of extractors secure against quantum bounded-storage adversaries. One instantiation gives the first such extractor to achieve an output length (...
Anindya De and Thomas Vidick
CVPR
2010
IEEE
15 years 10 months ago
Weakly-Supervised Hashing in Kernel Space
The explosive growth of the vision data motivates the recent studies on efficient data indexing methods such as locality-sensitive hashing (LSH). Most existing approaches perform...
Yadong Mu, Jialie Shen, Shuicheng Yan
APPROX
2005
Springer
111views Algorithms» more  APPROX 2005»
15 years 10 months ago
Sampling Bounds for Stochastic Optimization
A large class of stochastic optimization problems can be modeled as minimizing an objective function f that depends on a choice of a vector x ∈ X, as well as on a random external...
Moses Charikar, Chandra Chekuri, Martin Pál
131
Voted
WAOA
2005
Springer
142views Algorithms» more  WAOA 2005»
15 years 10 months ago
On the Minimum Load Coloring Problem
Given a graph G = (V, E) with n vertices, m edges and maximum vertex degree ∆, the load distribution of a coloring ϕ : V → {red, blue} is a pair dϕ = (rϕ, bϕ), where rϕ i...
Nitin Ahuja, Andreas Baltz, Benjamin Doerr, Ales P...
ICA
2004
Springer
15 years 9 months ago
Postnonlinear Overcomplete Blind Source Separation Using Sparse Sources
Abstract. We present an approach for blindly decomposing an observed random vector x into f(As) where f is a diagonal function i.e. f = f1 × . . . × fm with one-dimensional funct...
Fabian J. Theis, Shun-ichi Amari