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JOTA
2010
117views more  JOTA 2010»
15 years 5 months ago
Distributed Stochastic Subgradient Projection Algorithms for Convex Optimization
We consider a distributed multi-agent network system where the goal is to minimize a sum of agent objective functions subject to a common set of constraints. For this problem, we p...
S. Sundhar Ram, Angelia Nedic, Venugopal V. Veerav...
198
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ICWS
2009
IEEE
15 years 4 months ago
Discovery of Optimized Web Service Configurations Using a Hybrid Semantic and Statistical Approach
We present a Semantic Optimized Service Discovery (SemOSD) approach capable of handling Web service search requests on a fine-grained level of detail where we augment semantic ser...
Maciej Zaremba, Jacek Migdal, Manfred Hauswirth
TIP
2011
164views more  TIP 2011»
15 years 1 months ago
Multiregion Image Segmentation by Parametric Kernel Graph Cuts
Abstract—The purpose of this study is to investigate multiregion graph cut image partitioning via kernel mapping of the image data. The image data is transformed implicitly by a ...
Mohamed Ben Salah, Amar Mitiche, Ismail Ben Ayed
ICASSP
2010
IEEE
15 years 1 months ago
Temporally constrained SCA with applications to EEG data
In this paper we propose an iterative algorithm for solving the problem of extracting a sparse source signal when a reference signal for the desired source signal is available. In...
Nasser Mourad, James P. Reilly, Gary Hasey, Duncan...
ICASSP
2011
IEEE
14 years 10 months ago
Application specific loss minimization using gradient boosting
Gradient boosting is a flexible machine learning technique that produces accurate predictions by combining many weak learners. In this work, we investigate its use in two applica...
Bin Zhang, Abhinav Sethy, Tara N. Sainath, Bhuvana...