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INFOCOM
2005
IEEE
14 years 1 months ago
Online time-constrained scheduling in linear networks
— We consider the problem of scheduling a sequence of packets over a linear network, where every packet has a source and a target, as well as a release time and a deadline by whi...
Joseph Naor, Adi Rosén, Gabriel Scalosub
ALT
2010
Springer
13 years 9 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
AOR
2007
107views more  AOR 2007»
13 years 7 months ago
Job Shop Scheduling with Unit Length Tasks: Bounds and Algorithms
We consider the job shop scheduling problem unit−Jm, where each job is processed once on each of m given machines. Every job consists of a permutation of tasks for all machines....
Juraj Hromkovic, Tobias Mömke, Kathleen Stein...
ECML
2005
Springer
14 years 1 months ago
Active Learning for Probability Estimation Using Jensen-Shannon Divergence
Active selection of good training examples is an important approach to reducing data-collection costs in machine learning; however, most existing methods focus on maximizing classi...
Prem Melville, Stewart M. Yang, Maytal Saar-Tsecha...
CISIS
2011
IEEE
12 years 7 months ago
Improving Scheduling Techniques in Heterogeneous Systems with Dynamic, On-Line Optimisations
—Computational performance increasingly depends on parallelism, and many systems rely on heterogeneous resources such as GPUs and FPGAs to accelerate computationally intensive ap...
Marcin Bogdanski, Peter R. Lewis, Tobias Becker, X...