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» Approximation Algorithms for k-hurdle Problems
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NIPS
2008
15 years 3 months ago
An interior-point stochastic approximation method and an L1-regularized delta rule
The stochastic approximation method is behind the solution to many important, actively-studied problems in machine learning. Despite its farreaching application, there is almost n...
Peter Carbonetto, Mark Schmidt, Nando de Freitas
107
Voted
LATIN
2000
Springer
15 years 5 months ago
Worst-Case Complexity of the Optimal LLL Algorithm
In this paper, we consider the open problem of the complexity of the LLL algorithm in the case when the approximation parameter of the algorithm has its extreme value
Ali Akhavi
ISAAC
2005
Springer
90views Algorithms» more  ISAAC 2005»
15 years 7 months ago
Approximate Colored Range Queries
In this paper, we formulate a class of colored range query problems to model the multi-dimensional range queries in the presence of categorical information. By applying appropriate...
Ying Kit Lai, Chung Keung Poon, Benyun Shi
ICML
2010
IEEE
15 years 2 months ago
A scalable trust-region algorithm with application to mixed-norm regression
We present a new algorithm for minimizing a convex loss-function subject to regularization. Our framework applies to numerous problems in machine learning and statistics; notably,...
Dongmin Kim, Suvrit Sra, Inderjit S. Dhillon
132
Voted
APPROX
2006
Springer
124views Algorithms» more  APPROX 2006»
15 years 5 months ago
Combinatorial Algorithms for Data Migration to Minimize Average Completion Time
The data migration problem is to compute an efficient plan for moving data stored on devices in a network from one configuration to another. It is modeled by a transfer graph, wher...
Rajiv Gandhi, Julián Mestre