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» A Guided Monte Carlo Approach to Optimization Problems
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RECOMB
2007
Springer
15 years 10 months ago
Pairwise Global Alignment of Protein Interaction Networks by Matching Neighborhood Topology
We describe an algorithm, IsoRank, for global alignment of two protein-protein interaction (PPI) networks. IsoRank aims to maximize the overall match between the two networks; in c...
Rohit Singh, Jinbo Xu, Bonnie Berger
AGENTS
2001
Springer
15 years 2 months ago
Hierarchical multi-agent reinforcement learning
In this paper, we investigate the use of hierarchical reinforcement learning (HRL) to speed up the acquisition of cooperative multi-agent tasks. We introduce a hierarchical multi-a...
Rajbala Makar, Sridhar Mahadevan, Mohammad Ghavamz...
IJCNN
2007
IEEE
15 years 4 months ago
Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
Gavin C. Cawley, Nicola L. C. Talbot
MST
2000
57views more  MST 2000»
14 years 9 months ago
On Scheduling Parallel Tasks at Twilight
We consider the problem of processing a given number of tasks on a given number of processors as quickly as possible when only vague information about the processing time of a task...
Hannah Bast
ICCAD
2009
IEEE
131views Hardware» more  ICCAD 2009»
14 years 7 months ago
Scheduling with soft constraints
In a behavioral synthesis system, a typical approach used to guide the scheduler is to impose hard constraints on the relative timing between operations considering performance, a...
Jason Cong, Bin Liu, Zhiru Zhang