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» A framework for distributed simulation optimization
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JMLR
2012
13 years 9 months ago
Marginal Regression For Multitask Learning
Variable selection is an important and practical problem that arises in analysis of many high-dimensional datasets. Convex optimization procedures that arise from relaxing the NP-...
Mladen Kolar, Han Liu
ICRA
1998
IEEE
142views Robotics» more  ICRA 1998»
15 years 10 months ago
Lagrangian Relaxation Neural Networks for Job Shop Scheduling
Abstract--Manufacturing scheduling is an important but difficult task. In order to effectively solve such combinatorial optimization problems, this paper presents a novel Lagrangia...
Peter B. Luh, Xing Zhao, Yajun Wang
TON
2002
81views more  TON 2002»
15 years 6 months ago
Robust rate control for integrated services packet networks
Abstract--Research on congestion-control algorithms has traditionally focused more on performance than on robustness of the closed-loop system to changes in network conditions. As ...
Franco Blanchini, Renato Lo Cigno, Roberto Tempo
ISCA
2011
IEEE
225views Hardware» more  ISCA 2011»
14 years 10 months ago
FlexBulk: intelligently forming atomic blocks in blocked-execution multiprocessors to minimize squashes
Blocked-execution multiprocessor architectures continuously run atomic blocks of instructions — also called Chunks. Such architectures can boost both performance and software pr...
Rishi Agarwal, Josep Torrellas
ICDCS
2009
IEEE
16 years 1 months ago
Stochastic Multicast with Network Coding
The usage of network resources by content providers is commonly governed by Service Level Agreements (SLA) between the content provider and the network service provider. Resource ...
Ajay Gopinathan, Zongpeng Li