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» Sampling Bounds for Stochastic Optimization
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CPAIOR
2008
Springer
13 years 11 months ago
Amsaa: A Multistep Anticipatory Algorithm for Online Stochastic Combinatorial Optimization
The one-step anticipatory algorithm (1s-AA) is an online algorithm making decisions under uncertainty by ignoring future non-anticipativity constraints. It makes near-optimal decis...
Luc Mercier, Pascal Van Hentenryck
AAAI
2007
14 years 5 days ago
Stochastic Optimization for Collision Selection in High Energy Physics
Artificial intelligence has begun to play a critical role in basic science research. In high energy physics, AI methods can aid precision measurements that elucidate the underlyi...
Shimon Whiteson, Daniel Whiteson
TIT
2010
153views Education» more  TIT 2010»
13 years 4 months ago
On the information rates of the plenoptic function
The plenoptic function (Adelson and Bergen, 91) describes the visual information available to an observer at any point in space and time. Samples of the plenoptic function (POF) a...
Arthur L. da Cunha, Minh N. Do, Martin Vetterli
ALT
2010
Springer
13 years 11 months ago
Online Multiple Kernel Learning: Algorithms and Mistake Bounds
Online learning and kernel learning are two active research topics in machine learning. Although each of them has been studied extensively, there is a limited effort in addressing ...
Rong Jin, Steven C. H. Hoi, Tianbao Yang
ALT
1999
Springer
14 years 2 months ago
Extended Stochastic Complexity and Minimax Relative Loss Analysis
We are concerned with the problem of sequential prediction using a givenhypothesis class of continuously-manyprediction strategies. An e ectiveperformance measure is the minimax re...
Kenji Yamanishi