Sciweavers

FOCS
2004
IEEE
13 years 11 months ago
Stochastic Optimization is (Almost) as easy as Deterministic Optimization
Stochastic optimization problems attempt to model uncertainty in the data by assuming that (part of) the input is specified in terms of a probability distribution. We consider the...
David B. Shmoys, Chaitanya Swamy
FOCS
2004
IEEE
13 years 11 months ago
Maximum Matchings via Gaussian Elimination
Marcin Mucha, Piotr Sankowski
FOCS
2004
IEEE
13 years 11 months ago
Shuffling by Semi-Random Transpositions
In the cyclic-to-random shuffle, we are given n cards arranged in a circle. At step k, we exchange the k'th card along the circle with a uniformly chosen random card. The pro...
Elchanan Mossel, Yuval Peres, Alistair Sinclair
FOCS
2004
IEEE
13 years 11 months ago
Worst-Case to Average-Case Reductions Based on Gaussian Measures
We show that finding small solutions to random modular linear equations is at least as hard as approximating several lattice problems in the worst case within a factor almost line...
Daniele Micciancio, Oded Regev
FOCS
2004
IEEE
13 years 11 months ago
Random Edge Can Be Exponential on Abstract Cubes
DGE can be exponential on abstract cubes Jir
Jirí Matousek, Tibor Szabó
FOCS
2004
IEEE
13 years 11 months ago
Measured Descent: A New Embedding Method for Finite Metrics
We devise a new embedding technique, which we call measured descent, based on decomposing a metric space locally, at varying speeds, according to the density of some probability m...
Robert Krauthgamer, James R. Lee, Manor Mendel, As...