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» New Algorithms for Optimal Online Checkpointing
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ICDCS
1996
IEEE
13 years 11 months ago
How to Recover Efficiently and Asynchronously when Optimism Fails
We propose a new algorithm for recovering asynchronously from failures in a distributed computation. Our algorithm is based on two novel concepts - a fault-tolerant vector clock t...
Om P. Damani, Vijay K. Garg
CRV
2009
IEEE
153views Robotics» more  CRV 2009»
14 years 2 months ago
Optimal Online Data Sampling or How to Hire the Best Secretaries
The problem of online sampling of data, can be seen as a generalization of the classical secretary problem. The goal is to maximize the probability of picking the k highest scorin...
Yogesh Girdhar, Gregory Dudek
CORR
2010
Springer
116views Education» more  CORR 2010»
13 years 7 months ago
Adaptive Bound Optimization for Online Convex Optimization
We introduce a new online convex optimization algorithm that adaptively chooses its regularization function based on the loss functions observed so far. This is in contrast to pre...
H. Brendan McMahan, Matthew J. Streeter
GECCO
2007
Springer
137views Optimization» more  GECCO 2007»
14 years 1 months ago
Learning and anticipation in online dynamic optimization with evolutionary algorithms: the stochastic case
The focus of this paper is on how to design evolutionary algorithms (EAs) for solving stochastic dynamic optimization problems online, i.e. as time goes by. For a proper design, t...
Peter A. N. Bosman, Han La Poutré
ICML
2006
IEEE
14 years 8 months ago
Learning algorithms for online principal-agent problems (and selling goods online)
In a principal-agent problem, a principal seeks to motivate an agent to take a certain action beneficial to the principal, while spending as little as possible on the reward. This...
Vincent Conitzer, Nikesh Garera